From 5fc003899e327c8f7c6edf0f984568d2955ac93d Mon Sep 17 00:00:00 2001 From: "patched.codes[bot]" <298395+patched.codes[bot]@users.noreply.github.com> Date: Fri, 4 Oct 2024 21:35:55 +0000 Subject: [PATCH 001/136] Patched /tmp/tmpl03oclpk/style.md --- style.md | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 style.md diff --git a/style.md b/style.md new file mode 100644 index 00000000..82d2db0f --- /dev/null +++ b/style.md @@ -0,0 +1,27 @@ + +# Refined Code Style Guidelines + +## 1. Code Structure +- **JSON Output Format**: Use a specific JSON output format for entity and relation extraction. + - Entities should have "label" and "attributes" fields. + - Relations should have "label", "source", "target", and "attributes" fields. +- **Code Organization**: Maintain a consistent and logical structure throughout the codebase. +- **Import Statement Simplification**: Optimize and simplify import statements for better readability and performance. + +## 2. Documentation +- **Documentation Clarity and Formatting**: + - Ensure all documentation is clear, concise, and well-formatted. + - Use proper Markdown formatting for consistency and readability. +- **Documentation Improvement**: Continuously update and improve documentation to reflect the current state of the project. + +## 3. Version Control and Dependency Management +- **Version Control and Semantic Versioning**: + - Use semantic versioning (MAJOR.MINOR.PATCH) for release management. + - Follow consistent version control practices. +- **Dependency Management**: + - Keep dependencies up-to-date and properly managed. + - Regularly review and update project dependencies. + +## 4. Project Management +- **Contributing Guidelines**: Provide clear guidelines for contributors to ensure consistency and quality of contributions. +- **Open Source Licensing**: Ensure proper open-source licensing is in place and clearly communicated. From 8f148cc2df22a71b8649cd577e554bbec0b60ffc Mon Sep 17 00:00:00 2001 From: Sibeliu Date: Sun, 8 Dec 2024 14:22:49 +0700 Subject: [PATCH 002/136] add delay to avoid rate limits --- graphrag_sdk/kg.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/kg.py b/graphrag_sdk/kg.py index 831a05d3..53b0052e 100644 --- a/graphrag_sdk/kg.py +++ b/graphrag_sdk/kg.py @@ -1,5 +1,6 @@ import logging import warnings +import time from falkordb import FalkorDB from graphrag_sdk.ontology import Ontology from graphrag_sdk.source import AbstractSource @@ -133,13 +134,14 @@ def list_sources(self) -> list[AbstractSource]: return [s.source for s in self.sources] def process_sources( - self, sources: list[AbstractSource], instructions: str = None + self, sources: list[AbstractSource], instructions: str = None, delay: float = 0 ) -> None: """ Add entities and relations found in sources into the knowledge-graph Parameters: sources (list[AbstractSource]): list of sources to extract knowledge from + delay (float): seconds to delay each iteration through sources to avoid rate limits """ if self.ontology is None: @@ -151,6 +153,7 @@ def process_sources( # Add processed sources for src in sources: self.sources.add(src) + time.sleep(delay) def _create_graph_with_sources( self, sources: list[AbstractSource] | None = None, instructions: str = None From 4b5df23e0b1c438a8ab8d986abb9d54ce5b1ccba Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Dec 2024 17:51:34 +0200 Subject: [PATCH 003/136] replace-tests-deepeval --- poetry.lock | 1922 +++++++++++++---- pyproject.toml | 3 +- tests/test_kg_gemini.py | 108 - tests/test_kg_ollama.py | 109 - tests/test_kg_openai.py | 102 - ...{test_kg_litellm_openai.py => test_rag.py} | 58 +- 6 files changed, 1513 insertions(+), 789 deletions(-) delete mode 100644 tests/test_kg_gemini.py delete mode 100644 tests/test_kg_ollama.py delete mode 100644 tests/test_kg_openai.py rename tests/{test_kg_litellm_openai.py => test_rag.py} 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authors = ["FalkorDB "] @@ -22,6 +22,7 @@ ratelimit = "^2.2.1" python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" ipykernel = "^6.29.5" +deepeval = { version = "^2.0.9", python = ">=3.9,<3.13" } vertexai = { version = "^1.49.0", optional = true } ollama = { version = "^0.2.1", optional = true } openai = { version = "^1.35.9", optional = true } diff --git a/tests/test_kg_gemini.py b/tests/test_kg_gemini.py deleted file mode 100644 index cbfdf2b1..00000000 --- a/tests/test_kg_gemini.py +++ /dev/null @@ -1,108 +0,0 @@ -import re -import os -import logging -import unittest -import vertexai -from falkordb import FalkorDB -from dotenv import load_dotenv -from graphrag_sdk.entity import Entity -from graphrag_sdk.source import Source -from graphrag_sdk.ontology import Ontology -from graphrag_sdk.relation import Relation -from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk.models.gemini import GeminiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig - -load_dotenv() - -logging.basicConfig(level=logging.DEBUG) -logger = logging.getLogger(__name__) - -vertexai.init(project=os.getenv("PROJECT_ID"), location=os.getenv("REGION")) - - -class TestKGGemini(unittest.TestCase): - """ - Test Knowledge Graph - """ - - @classmethod - def setUpClass(cls): - - cls.ontology = Ontology([], []) - - cls.ontology.add_entity( - Entity( - label="Actor", - attributes=[ - Attribute( - name="name", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_entity( - Entity( - label="Movie", - attributes=[ - Attribute( - name="title", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_relation( - Relation( - label="ACTED_IN", - source="Actor", - target="Movie", - attributes=[ - Attribute( - name="role", - attr_type=AttributeType.STRING, - unique=False, - required=False, - ), - ], - ) - ) - - cls.graph_name = "IMDB_gemini" - - model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001") - cls.kg = KnowledgeGraph( - name=cls.graph_name, - ontology=cls.ontology, - model_config=KnowledgeGraphModelConfig.with_model(model), - ) - - def test_kg_creation(self): - file_path = "tests/data/madoff.txt" - - sources = [Source(file_path)] - - self.kg.process_sources(sources) - - chat = self.kg.chat_session() - answer = chat.send_message("How many actors acted in a movie?") - answer = answer['response'] - - logger.info(f"Answer: {answer}") - - actors_count = re.findall(r'\d+', answer) - num_actors = 0 if len(actors_count) == 0 else int(actors_count[0]) - - assert num_actors > 10, "The number of actors found should be greater than 10" - - def test_kg_delete(self): - self.kg.delete() - - db = FalkorDB() - graphs = db.list_graphs() - self.assertNotIn(self.graph_name, graphs) diff --git a/tests/test_kg_ollama.py b/tests/test_kg_ollama.py deleted file mode 100644 index 06ec03ee..00000000 --- a/tests/test_kg_ollama.py +++ /dev/null @@ -1,109 +0,0 @@ -import re -import logging -import unittest -from falkordb import FalkorDB -from dotenv import load_dotenv -from graphrag_sdk.entity import Entity -from graphrag_sdk.source import Source -from graphrag_sdk.ontology import Ontology -from graphrag_sdk.relation import Relation -from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk.models.ollama import OllamaGenerativeModel -from graphrag_sdk.models.openai import OpenAiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig - -load_dotenv() - - -logging.basicConfig(level=logging.DEBUG) -logger = logging.getLogger(__name__) - -class TestKGOllama(unittest.TestCase): - """ - Test Knowledge Graph - """ - - @classmethod - def setUpClass(cls): - - cls.ontology = Ontology([], []) - - cls.ontology.add_entity( - Entity( - label="Actor", - attributes=[ - Attribute( - name="name", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_entity( - Entity( - label="Movie", - attributes=[ - Attribute( - name="title", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_relation( - Relation( - label="ACTED_IN", - source="Actor", - target="Movie", - attributes=[ - Attribute( - name="role", - attr_type=AttributeType.STRING, - unique=False, - required=False, - ), - ], - ) - ) - - cls.graph_name = "IMDB_ollama" - - model_ollama = OllamaGenerativeModel(model_name="llama3:8b", generation_config=GenerativeModelConfig(temperature=0)) - model_openai = OpenAiGenerativeModel(model_name="gpt-3.5-turbo") - - cls.kg = KnowledgeGraph( - name=cls.graph_name, - ontology=cls.ontology, - model_config=KnowledgeGraphModelConfig(extract_data=model_openai, cypher_generation=model_ollama, qa=model_ollama), - ) - - def test_kg_creation(self): - - file_path = "tests/data/madoff.txt" - - sources = [Source(file_path)] - - self.kg.process_sources(sources) - - chat = self.kg.chat_session() - answer = chat.send_message("How many actors acted in a movie?") - answer = answer['response'] - - logger.info(f"Answer: {answer}") - - actors_count = re.findall(r'\d+', answer) - num_actors = 0 if len(actors_count) == 0 else int(actors_count[0]) - - assert num_actors > 5, "The number of actors found should be greater than 5" - - def test_kg_delete(self): - - self.kg.delete() - - db = FalkorDB() - graphs = db.list_graphs() - self.assertNotIn(self.graph_name, graphs) diff --git a/tests/test_kg_openai.py b/tests/test_kg_openai.py deleted file mode 100644 index 785a28df..00000000 --- a/tests/test_kg_openai.py +++ /dev/null @@ -1,102 +0,0 @@ -import re -import logging -import unittest -from falkordb import FalkorDB -from dotenv import load_dotenv -from graphrag_sdk.entity import Entity -from graphrag_sdk.source import Source -from graphrag_sdk.relation import Relation -from graphrag_sdk.ontology import Ontology -from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk.models.openai import OpenAiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig - -load_dotenv() - -logging.basicConfig(level=logging.DEBUG) -logger = logging.getLogger(__name__) - -class TestKGOpenAI(unittest.TestCase): - """ - Test Knowledge Graph - """ - - @classmethod - def setUpClass(cls): - - cls.ontology = Ontology([], []) - - cls.ontology.add_entity( - Entity( - label="Actor", - attributes=[ - Attribute( - name="name", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_entity( - Entity( - label="Movie", - attributes=[ - Attribute( - name="title", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) - ) - cls.ontology.add_relation( - Relation( - label="ACTED_IN", - source="Actor", - target="Movie", - attributes=[ - Attribute( - name="role", - attr_type=AttributeType.STRING, - unique=False, - required=False, - ), - ], - ) - ) - cls.graph_name = "IMDB_openai" - model = OpenAiGenerativeModel(model_name="gpt-3.5-turbo-0125") - cls.kg = KnowledgeGraph( - name=cls.graph_name, - ontology=cls.ontology, - model_config=KnowledgeGraphModelConfig.with_model(model), - ) - - def test_kg_creation(self): - - file_path = "tests/data/madoff.txt" - - sources = [Source(file_path)] - - self.kg.process_sources(sources) - - chat = self.kg.chat_session() - answer = chat.send_message("How many actors acted in a movie?") - answer = answer['response'] - - logger.info(f"Answer: {answer}") - - actors_count = re.findall(r'\d+', answer) - num_actors = 0 if len(actors_count) == 0 else int(actors_count[0]) - - assert num_actors > 10, "The number of actors found should be greater than 10" - - def test_kg_delete(self): - self.kg.delete() - - db = FalkorDB() - graphs = db.list_graphs() - self.assertNotIn(self.graph_name, graphs) diff --git a/tests/test_kg_litellm_openai.py b/tests/test_rag.py similarity index 52% rename from tests/test_kg_litellm_openai.py rename to tests/test_rag.py index 2ec80f49..86eb53be 100644 --- a/tests/test_kg_litellm_openai.py +++ b/tests/test_rag.py @@ -1,15 +1,17 @@ -import re import logging import unittest -from falkordb import FalkorDB from dotenv import load_dotenv +from deepeval import assert_test from graphrag_sdk.entity import Entity from graphrag_sdk.source import Source +from deepeval.test_case import LLMTestCase from graphrag_sdk.relation import Relation from graphrag_sdk.ontology import Ontology -from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk.models.litellm import LiteModel +from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from deepeval.metrics import AnswerRelevancyMetric, ContextualPrecisionMetric, ContextualRecallMetric, ContextualRelevancyMetric + load_dotenv() @@ -67,13 +69,21 @@ def setUpClass(cls): ], ) ) - cls.graph_name = "IMDB_openai" + cls.graph_name = "IMDB" model = LiteModel(model_name="gpt-4o") - cls.kg = KnowledgeGraph( + + cls.kg_openai = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, model_config=KnowledgeGraphModelConfig.with_model(model), ) + + cls.kg_gemini = KnowledgeGraph( + name=cls.graph_name, + ontology=cls.ontology, + model_config=KnowledgeGraphModelConfig.with_model(model), + ) + def test_kg_creation(self): @@ -81,15 +91,37 @@ def test_kg_creation(self): sources = [Source(file_path)] - self.kg.process_sources(sources) + self.kg_gemini.process_sources(sources) + input = "How many actors acted in a movie?" + + chat = self.kg_gemini.chat_session() + answer = chat.send_message(input) + answer_relevancy_metric = AnswerRelevancyMetric(threshold=0.5) + answer_cp_metric = ContextualPrecisionMetric(threshold=0.5) + answer_crecall_metric = ContextualRecallMetric(threshold=0.5) + answer_crelevancy_metric = ContextualRelevancyMetric(threshold=0.5) - chat = self.kg.chat_session() - answer = chat.send_message("How many actors acted in a movie?") - answer = answer['response'] - logger.info(f"Answer: {answer}") - actors_count = re.findall(r'\d+', answer) - num_actors = 0 if len(actors_count) == 0 else int(actors_count[0]) + test_case = LLMTestCase( + input=input, + actual_output=answer['response'], + retrieval_context=[answer['context']], + context=[answer['context']], + name="gemini", + expected_output="Over than 10 actors acted in a movie." + ) + assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crecall_metric, answer_crelevancy_metric]) + + chat = self.kg_openai.chat_session() + answer = chat.send_message(input) + test_case = LLMTestCase( + input=input, + actual_output=answer['response'], + retrieval_context=[answer['context']], + context=[answer['context']], + name="openai", + expected_output="Over than 10 actors acted in a movie." + ) - assert num_actors > 10, "The number of actors found should be greater than 10" \ No newline at end of file + assert_test(test_case, [answer_relevancy_metric,answer_cp_metric, answer_crecall_metric, answer_crelevancy_metric]) \ No newline at end of file From faa3b78842747c3e653d53f72c45d96284d0478c Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Thu, 26 Dec 2024 10:15:08 +0200 Subject: [PATCH 004/136] rm-cre --- tests/test_rag.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_rag.py b/tests/test_rag.py index 86eb53be..447e69b2 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -111,7 +111,7 @@ def test_kg_creation(self): name="gemini", expected_output="Over than 10 actors acted in a movie." ) - assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crecall_metric, answer_crelevancy_metric]) + assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crelevancy_metric]) chat = self.kg_openai.chat_session() answer = chat.send_message(input) @@ -124,4 +124,4 @@ def test_kg_creation(self): expected_output="Over than 10 actors acted in a movie." ) - assert_test(test_case, [answer_relevancy_metric,answer_cp_metric, answer_crecall_metric, answer_crelevancy_metric]) \ No newline at end of file + assert_test(test_case, [answer_relevancy_metric,answer_cp_metric, answer_crelevancy_metric]) \ No newline at end of file From 00ff51a2df59d6b509bae6d073ea9abf5bdc4f18 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 8 Jan 2025 15:52:32 +0200 Subject: [PATCH 005/136] custom_metric_graph --- custom_metric.py | 329 ++++++++++++++++++++++++++++++++++++++++++++++ tests/test_rag.py | 121 +++++++++++++---- 2 files changed, 428 insertions(+), 22 deletions(-) create mode 100644 custom_metric.py diff --git a/custom_metric.py b/custom_metric.py new file mode 100644 index 00000000..32bc2453 --- /dev/null +++ b/custom_metric.py @@ -0,0 +1,329 @@ +from typing import Optional +from deepeval.metrics import BaseMetric, AnswerRelevancyMetric, FaithfulnessMetric +from deepeval.test_case import LLMTestCase +from typing import Optional, List, Union + +from deepeval.utils import get_or_create_event_loop, prettify_list +from deepeval.metrics.utils import ( + construct_verbose_logs, + trimAndLoadJson, + check_llm_test_case_params, + initialize_model, +) +from deepeval.test_case import ( + LLMTestCase, + LLMTestCaseParams, + ConversationalTestCase, +) +from deepeval.metrics import BaseMetric +from deepeval.models import DeepEvalBaseLLM +from deepeval.metrics.contextual_recall.template import ContextualRecallTemplate +from deepeval.metrics.indicator import metric_progress_indicator +from deepeval.metrics.contextual_recall.schema import * + +required_params: List[LLMTestCaseParams] = [ + LLMTestCaseParams.INPUT, + LLMTestCaseParams.ACTUAL_OUTPUT, + LLMTestCaseParams.RETRIEVAL_CONTEXT, + LLMTestCaseParams.EXPECTED_OUTPUT, +] + +class FaithfulRelevancyGraphContextualMetric(BaseMetric): + def __init__( + self, + threshold: float = 0.5, + evaluation_model: Optional[str] = "gpt-4o", + include_reason: bool = True, + async_mode: bool = True, + strict_mode: bool = False, + ): + self.threshold = 1 if strict_mode else threshold + self.evaluation_model = evaluation_model + self.include_reason = include_reason + self.async_mode = async_mode + self.strict_mode = strict_mode + + def measure(self, test_case: LLMTestCase): + try: + relevancy_metric, faithfulness_metric, graph_context_recall_metric = self.initialize_metrics() + # Remember, deepeval's default metrics follow the same pattern as your custom metric! + graph_context_recall_metric.measure(test_case) + relevancy_metric.measure(test_case) + faithfulness_metric.measure(test_case) + + # Custom logic to set score, reason, and success + self.set_score_reason_success(relevancy_metric, faithfulness_metric, graph_context_recall_metric) + return self.score + except Exception as e: + # Set and re-raise error + self.error = str(e) + raise + + + def is_successful(self) -> bool: + if self.error is not None: + self.success = False + else: + return self.success + + @property + def __name__(self): + return "Composite Relevancy Faithfulness Metric" + + + ###################### + ### Helper methods ### + ###################### + def initialize_metrics(self): + graph_context_recall_metric = GraphContextualRecall( + threshold=self.threshold, + model=self.evaluation_model, + include_reason=self.include_reason, + strict_mode=self.strict_mode + ) + + relevancy_metric = AnswerRelevancyMetric( + threshold=self.threshold, + model=self.evaluation_model, + include_reason=self.include_reason, + async_mode=self.async_mode, + strict_mode=self.strict_mode + ) + faithfulness_metric = FaithfulnessMetric( + threshold=self.threshold, + model=self.evaluation_model, + include_reason=self.include_reason, + async_mode=self.async_mode, + strict_mode=self.strict_mode + ) + return relevancy_metric, faithfulness_metric, graph_context_recall_metric + + def set_score_reason_success( + self, + relevancy_metric: BaseMetric, + faithfulness_metric: BaseMetric, + graph_context_recall_metric: BaseMetric + ): + # Get scores and reasons for both + relevancy_score = relevancy_metric.score + relevancy_reason = relevancy_metric.reason + faithfulness_score = faithfulness_metric.score + faithfulness_reason = faithfulness_metric.reason + graph_context_recall_metric_score = graph_context_recall_metric.score + graph_context_recall_metric_reason = graph_context_recall_metric.reason + + # Custom logic to set score + composite_score = min(relevancy_score, faithfulness_score, graph_context_recall_metric_score) + self.score = 0 if self.strict_mode and composite_score < self.threshold else composite_score + + # Custom logic to set reason + if self.include_reason: + self.reason = relevancy_reason + "\n" + faithfulness_reason + "\n" + graph_context_recall_metric_reason + + # Custom logic to set success + self.success = self.score >= self.threshold + + + +class GraphContextualRecall(BaseMetric): + def __init__( + self, + threshold: float = 0.5, + model: Optional[Union[str, DeepEvalBaseLLM]] = None, + include_reason: bool = True, + strict_mode: bool = False, + verbose_mode: bool = False, + ): + self.threshold = 1 if strict_mode else threshold + self.model, self.using_native_model = initialize_model(model) + self.evaluation_model = self.model.get_model_name() + self.include_reason = include_reason + self.strict_mode = strict_mode + self.verbose_mode = verbose_mode + + def measure( + self, + test_case: LLMTestCase, + _show_indicator: bool = True, + ) -> float: + check_llm_test_case_params(test_case, required_params, self) + + self.evaluation_cost = 0 if self.using_native_model else None + with metric_progress_indicator(self, _show_indicator=_show_indicator): + self.verdicts: List[ContextualRecallVerdict] = ( + self._generate_verdicts( + test_case.expected_output, test_case.retrieval_context, test_case.additional_metadata + ) + ) + self.score = self._calculate_score() + self.reason = self._generate_reason(test_case.expected_output) + self.success = self.score >= self.threshold + self.verbose_logs = construct_verbose_logs( + self, + steps=[ + f"Verdicts:\n{prettify_list(self.verdicts)}", + f"Score: {self.score}\nReason: {self.reason}", + ], + ) + + return self.score + + def _generate_reason(self, expected_output: str): + if self.include_reason is False: + return None + + supportive_reasons = [] + unsupportive_reasons = [] + for verdict in self.verdicts: + if verdict.verdict.lower() == "yes": + supportive_reasons.append(verdict.reason) + else: + unsupportive_reasons.append(verdict.reason) + + prompt = GraphContextualRecallTemplate.generate_reason( + expected_output=expected_output, + supportive_reasons=supportive_reasons, + unsupportive_reasons=unsupportive_reasons, + score=format(self.score, ".2f"), + ) + + if self.using_native_model: + res, cost = self.model.generate(prompt) + self.evaluation_cost += cost + data = trimAndLoadJson(res, self) + return data["reason"] + else: + try: + res: Reason = self.model.generate(prompt, schema=Reason) + return res.reason + except TypeError: + res = self.model.generate(prompt) + data = trimAndLoadJson(res, self) + return data["reason"] + + def _calculate_score(self): + number_of_verdicts = len(self.verdicts) + if number_of_verdicts == 0: + return 0 + + justified_sentences = 0 + for verdict in self.verdicts: + if verdict.verdict.lower() == "yes": + justified_sentences += 1 + + score = justified_sentences / number_of_verdicts + return 0 if self.strict_mode and score < self.threshold else score + + def _generate_verdicts( + self, expected_output: str, retrieval_context: List[str], cypher_query: Optional[str] = None + ) -> List[ContextualRecallVerdict]: + prompt = GraphContextualRecallTemplate.generate_verdicts( + expected_output=expected_output, retrieval_context=retrieval_context, cypher_query=cypher_query + ) + if self.using_native_model: + res, cost = self.model.generate(prompt) + self.evaluation_cost += cost + data = trimAndLoadJson(res, self) + verdicts = [ + ContextualRecallVerdict(**item) for item in data["verdicts"] + ] + return verdicts + else: + try: + res: Verdicts = self.model.generate(prompt, schema=Verdicts) + verdicts: Verdicts = [item for item in res.verdicts] + return verdicts + except TypeError: + res = self.model.generate(prompt) + data = trimAndLoadJson(res, self) + verdicts = [ + ContextualRecallVerdict(**item) for item in data["verdicts"] + ] + return verdicts + + def is_successful(self) -> bool: + if self.error is not None: + self.success = False + else: + try: + self.success = self.score >= self.threshold + except: + self.success = False + return self.success + + @property + def __name__(self): + return "Graph Contextual Recall" + +class GraphContextualRecallTemplate: + @staticmethod + def generate_reason( + expected_output, supportive_reasons, unsupportive_reasons, score + ): + return f""" +Given the original expected output, a list of supportive reasons, and a list of unsupportive reasons (which is deduced directly from the 'expected output'), and a contextual recall score (closer to 1 the better), summarize a CONCISE reason for the score. +A supportive reason is the reason why a certain sentence in the original expected output can be attributed to the node in the retrieval context. +An unsupportive reason is the reason why a certain sentence in the original expected output cannot be attributed to anything in the retrieval context. +In your reason, you should related supportive/unsupportive reasons to the sentence number in expected output, and info regarding the node number in retrieval context to support your final reason. The first mention of "node(s)" should specify "node(s) in retrieval context)". + +** +IMPORTANT: Please make sure to only return in JSON format, with the 'reason' key providing the reason. +Example JSON: +{{ + "reason": "The score is because ." +}} + +DO NOT mention 'supportive reasons' and 'unsupportive reasons' in your reason, these terms are just here for you to understand the broader scope of things. +If the score is 1, keep it short and say something positive with an upbeat encouraging tone (but don't overdo it otherwise it gets annoying). +** + +Contextual Recall Score: +{score} + +Expected Output: +{expected_output} + +Supportive Reasons: +{supportive_reasons} + +Unsupportive Reasons: +{unsupportive_reasons} + +JSON: +""" + + @staticmethod + def generate_verdicts(expected_output, retrieval_context, cypher_query): + return f""" +For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts that generated from the cypher query. Please generate a list of JSON with two keys: `verdict` and `reason`. +The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context and the cypher query, else answer 'no'. +The `reason` key should provide a reason why to the verdict. In the reason, you should aim to include the node(s) count in the retrieval context (eg., 1st node, and 2nd node in the retrieval context) that is attributed to said sentence. You should also aim to quote the specific part of the retrieval context to justify your verdict, but keep it extremely concise and cut short the quote with an ellipsis if possible. + + +** +IMPORTANT: Please make sure to only return in JSON format, with the 'verdicts' key as a list of JSON objects, each with two keys: `verdict` and `reason`. + +{{ + "verdicts": [ + {{ + "verdict": "yes", + "reason": "..." + }}, + ... + ] +}} + +Since you are going to generate a verdict for each sentence, the number of 'verdicts' SHOULD BE STRICTLY EQUAL to the number of sentences in of `expected output`. +** + +Expected Output: +{expected_output} + +Cypher Query: +{cypher_query} + +Retrieval Context: +{retrieval_context} + +JSON: +""" diff --git a/tests/test_rag.py b/tests/test_rag.py index 447e69b2..6238726c 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -11,12 +11,108 @@ from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig from deepeval.metrics import AnswerRelevancyMetric, ContextualPrecisionMetric, ContextualRecallMetric, ContextualRelevancyMetric - +from custom_metric import FaithfulRelevancyGraphContextualMetric load_dotenv() logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) +ontology = Ontology() + +ontology.add_entity( + Entity( + label="Actor", + attributes=[ + Attribute( + name="name", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], + ) +) +ontology.add_entity( + Entity( + label="Movie", + attributes=[ + Attribute( + name="title", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], + ) +) +ontology.add_relation( + Relation( + label="ACTED_IN", + source="Actor", + target="Movie", + attributes=[ + Attribute( + name="role", + attr_type=AttributeType.STRING, + unique=False, + required=False, + ), + ], + ) +) +graph_name = "IMDB_deep" +model = LiteModel(model_name="gemini/gemini-2.0-flash-exp") + +kg_gemini = KnowledgeGraph( + name=graph_name, + ontology=ontology, + model_config=KnowledgeGraphModelConfig.with_model(model), +) +file_path = "tests/data/madoff.txt" + +sources = [Source(file_path)] + +kg_gemini.process_sources(sources) + +answer_relevancy_metric = AnswerRelevancyMetric(threshold=0.5) +answer_cp_metric = ContextualPrecisionMetric(threshold=0.5) +answer_crecall_metric = ContextualRecallMetric(threshold=0.5) +answer_crelevancy_metric = ContextualRelevancyMetric(threshold=0.5) + +inputs = ["How many actors acted in a movie?", + "Which actors acted in the movie Madoff: The Monster of Wall Street?", + "What is the role of Joseph Scotto in Madoff: The Monster of Wall Street?", + "Did Donna Pastorello act in Madoff: The Monster of Wall Street?", + "Who played the role of Mark Madoff in Madoff: The Monster of Wall Street?", + "Did Melony Feliciano have a named role in Madoff: The Monster of Wall Street?"] + +expected_outputs = ["Over than 10 actors acted in a movie.", + "Joseph Scotto, Melony Feliciano, and Donna Pastorello acted in the movie Madoff: The Monster of Wall Street.", + "Joseph Scotto played the role of Bernie Madoff in Madoff: The Monster of Wall Street.", + "Yes, Donna Pastorello acted in Madoff: The Monster of Wall Street as Eleanor Squillari.", + "Alex Olson played the role of Mark Madoff in Madoff: The Monster of Wall Street.", + "No, Melony Feliciano acted as a background extra in Madoff: The Monster of Wall Street."] + +answer_faithful_relevancy_metric = FaithfulRelevancyGraphContextualMetric(threshold=0.5) +scores = [] +for input, expected_output in zip(inputs, expected_outputs): + chat = kg_gemini.chat_session() + answer = chat.send_message(input) + + test_case = LLMTestCase( + input=input, + actual_output=answer['response'], + retrieval_context=[answer['context']], + context=[answer['context']], + name="gemini", + expected_output=expected_output, + additional_metadata={"cypher_query": answer['cypher']} + ) + + score = answer_faithful_relevancy_metric.measure(test_case) + scores.append(score) + +assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crelevancy_metric]) class TestKGLiteLLM(unittest.TestCase): """ @@ -69,15 +165,9 @@ def setUpClass(cls): ], ) ) - cls.graph_name = "IMDB" + cls.graph_name = "IMDB_deep" model = LiteModel(model_name="gpt-4o") - cls.kg_openai = KnowledgeGraph( - name=cls.graph_name, - ontology=cls.ontology, - model_config=KnowledgeGraphModelConfig.with_model(model), - ) - cls.kg_gemini = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, @@ -111,17 +201,4 @@ def test_kg_creation(self): name="gemini", expected_output="Over than 10 actors acted in a movie." ) - assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crelevancy_metric]) - - chat = self.kg_openai.chat_session() - answer = chat.send_message(input) - test_case = LLMTestCase( - input=input, - actual_output=answer['response'], - retrieval_context=[answer['context']], - context=[answer['context']], - name="openai", - expected_output="Over than 10 actors acted in a movie." - ) - - assert_test(test_case, [answer_relevancy_metric,answer_cp_metric, answer_crelevancy_metric]) \ No newline at end of file + assert_test(test_case, [answer_relevancy_metric, answer_cp_metric, answer_crelevancy_metric]) \ No newline at end of file From 21698754c4266014ffee246be79d905c69f42d71 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 22 Jan 2025 08:54:08 +0200 Subject: [PATCH 006/136] add-cont-rel --- .../custom_metric.py | 223 +++++++++++++++++- tests/test_rag.py | 2 +- 2 files changed, 222 insertions(+), 3 deletions(-) rename custom_metric.py => graphrag_sdk/custom_metric.py (60%) diff --git a/custom_metric.py b/graphrag_sdk/custom_metric.py similarity index 60% rename from custom_metric.py rename to graphrag_sdk/custom_metric.py index 32bc2453..78b570e7 100644 --- a/custom_metric.py +++ b/graphrag_sdk/custom_metric.py @@ -1,5 +1,5 @@ from typing import Optional -from deepeval.metrics import BaseMetric, AnswerRelevancyMetric, FaithfulnessMetric +from deepeval.metrics import BaseMetric, AnswerRelevancyMetric, FaithfulnessMetric, ContextualRelevancyMetric from deepeval.test_case import LLMTestCase from typing import Optional, List, Union @@ -15,6 +15,8 @@ LLMTestCaseParams, ConversationalTestCase, ) + +from deepeval.metrics.contextual_relevancy.schema import * from deepeval.metrics import BaseMetric from deepeval.models import DeepEvalBaseLLM from deepeval.metrics.contextual_recall.template import ContextualRecallTemplate @@ -28,7 +30,7 @@ LLMTestCaseParams.EXPECTED_OUTPUT, ] -class FaithfulRelevancyGraphContextualMetric(BaseMetric): +class CombineMetrics(BaseMetric): def __init__( self, threshold: float = 0.5, @@ -75,6 +77,13 @@ def __name__(self): ### Helper methods ### ###################### def initialize_metrics(self): + graph_context_recall_metric = GraphContextualRelevancy( + threshold=self.threshold, + model=self.evaluation_model, + include_reason=self.include_reason, + strict_mode=self.strict_mode + ) + graph_context_recall_metric = GraphContextualRecall( threshold=self.threshold, model=self.evaluation_model, @@ -327,3 +336,213 @@ def generate_verdicts(expected_output, retrieval_context, cypher_query): JSON: """ + +class GraphContextualRelevancy(BaseMetric): + def __init__( + self, + threshold: float = 0.5, + model: Optional[Union[str, DeepEvalBaseLLM]] = None, + include_reason: bool = True, + async_mode: bool = True, + strict_mode: bool = False, + verbose_mode: bool = False, + ): + self.threshold = 1 if strict_mode else threshold + self.model, self.using_native_model = initialize_model(model) + self.evaluation_model = self.model.get_model_name() + self.include_reason = include_reason + self.async_mode = async_mode + self.strict_mode = strict_mode + self.verbose_mode = verbose_mode + + def measure( + self, + test_case: Union[LLMTestCase, ConversationalTestCase], + _show_indicator: bool = True, + ) -> float: + if isinstance(test_case, ConversationalTestCase): + test_case = test_case.turns[0] + check_llm_test_case_params(test_case, required_params, self) + + self.evaluation_cost = 0 if self.using_native_model else None + with metric_progress_indicator(self, _show_indicator=_show_indicator): + if self.async_mode: + loop = get_or_create_event_loop() + loop.run_until_complete( + self.a_measure(test_case, _show_indicator=False) + ) + else: + self.verdicts_list: List[ContextualRelevancyVerdicts] = [ + (self._generate_verdicts(test_case.input, context)) + for context in test_case.retrieval_context + ] + self.score = self._calculate_score() + self.reason = self._generate_reason(test_case.input) + self.success = self.score >= self.threshold + self.verbose_logs = construct_verbose_logs( + self, + steps=[ + f"Verdicts:\n{prettify_list(self.verdicts_list)}", + f"Score: {self.score}\nReason: {self.reason}", + ], + ) + + return self.score + + def _generate_reason(self, input: str): + if self.include_reason is False: + return None + + irrelevancies = [] + relevant_statements = [] + for verdicts in self.verdicts_list: + for verdict in verdicts.verdicts: + if verdict.verdict.lower() == "no": + irrelevancies.append(verdict.reason) + else: + relevant_statements.append(verdict.statement) + + prompt: dict = GraphContextualRelevancyTemplate.generate_reason( + input=input, + irrelevancies=irrelevancies, + relevant_statements=relevant_statements, + score=format(self.score, ".2f"), + ) + if self.using_native_model: + res, cost = self.model.generate(prompt) + self.evaluation_cost += cost + data = trimAndLoadJson(res, self) + return data["reason"] + else: + try: + res: Reason = self.model.generate(prompt, schema=Reason) + return res.reason + except TypeError: + res = self.model.generate(prompt) + data = trimAndLoadJson(res, self) + return data["reason"] + + def _calculate_score(self): + total_verdicts = 0 + relevant_statements = 0 + for verdicts in self.verdicts_list: + for verdict in verdicts.verdicts: + total_verdicts += 1 + if verdict.verdict.lower() == "yes": + relevant_statements += 1 + + if total_verdicts == 0: + return 0 + + score = relevant_statements / total_verdicts + return 0 if self.strict_mode and score < self.threshold else score + + def _generate_verdicts( + self, input: str, context: str + ) -> ContextualRelevancyVerdicts: + prompt = GraphContextualRelevancyTemplate.generate_verdicts( + input=input, context=context + ) + if self.using_native_model: + res, cost = self.model.generate(prompt) + self.evaluation_cost += cost + data = trimAndLoadJson(res, self) + return ContextualRelevancyVerdicts(**data) + else: + try: + res = self.model.generate( + prompt, schema=ContextualRelevancyVerdicts + ) + return res + except TypeError: + res = self.model.generate(prompt) + data = trimAndLoadJson(res, self) + return ContextualRelevancyVerdicts(**data) + + def is_successful(self) -> bool: + if self.error is not None: + self.success = False + else: + try: + self.success = self.score >= self.threshold + except: + self.success = False + return self.success + + @property + def __name__(self): + return "Graph Contextual Relevancy" + +class GraphContextualRelevancyTemplate: + @staticmethod + def generate_reason( + input: str, + irrelevancies: List[str], + relevant_statements: List[str], + score: float, + ): + return f"""Based on the given input, reasons for why the retrieval context is irrelevant to the input, the statements in the retrieval context that is actually relevant to the retrieval context, and the contextual relevancy score (the closer to 1 the better), please generate a CONCISE reason for the score. +In your reason, you should quote data provided in the reasons for irrelevancy and relevant statements to support your point. + +** +IMPORTANT: Please make sure to only return in JSON format, with the 'reason' key providing the reason. +Example JSON: +{{ + "reason": "The score is because ." +}} + +If the score is 1, keep it short and say something positive with an upbeat encouraging tone (but don't overdo it otherwise it gets annoying). +** + + +Contextual Relevancy Score: +{score} + +Input: +{input} + +Reasons for why the retrieval context is irrelevant to the input: +{irrelevancies} + +Statement in the retrieval context that is relevant to the input: +{relevant_statements} + +JSON: +""" + + @staticmethod + def generate_verdicts(input: str, context: str): + return f"""Based on the input and context, please generate a JSON object to indicate whether each statement found in the context is relevant to the provided input. The JSON will be a list of 'verdicts', with 2 mandatory fields: 'verdict' and 'statement', and 1 optional field: 'reason'. +You should first extract statements found in the context, which are high level information found in the context, before deciding on a verdict and optionally a reason for each statement. +The 'verdict' key should STRICTLY be either 'yes' or 'no', and states whether the statement is relevant to the input. +Provide a 'reason' ONLY IF verdict is no. You MUST quote the irrelevant parts of the statement to back up your reason. + +** +IMPORTANT: Please make sure to only return in JSON format. +Example Context: "Einstein won the Nobel Prize for his discovery of the photoelectric effect. He won the Nobel Prize in 1968. There was a cat." +Example Input: "What were some of Einstein's achievements?" + +Example: +{{ + "verdicts": [ + {{ + "verdict": "yes", + "statement": "Einstein won the Nobel Prize for his discovery of the photoelectric effect in 1968", + }}, + {{ + "verdict": "no", + "statement": "There was a cat.", + "reason": "The retrieval context contained the information 'There was a cat' when it has nothing to do with Einstein's achievements." + }} + ] +}} +** + +Input: +{input} + +Context: +{context} + +JSON: +""" diff --git a/tests/test_rag.py b/tests/test_rag.py index 6238726c..5fefa476 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -11,7 +11,7 @@ from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig from deepeval.metrics import AnswerRelevancyMetric, ContextualPrecisionMetric, ContextualRecallMetric, ContextualRelevancyMetric -from custom_metric import FaithfulRelevancyGraphContextualMetric +from graphrag_sdk.custom_metric import FaithfulRelevancyGraphContextualMetric load_dotenv() From ec4093272898c8e18745f58f83b12bc287eb9fbd Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 22 Jan 2025 14:37:03 +0200 Subject: [PATCH 007/136] update-tests --- graphrag_sdk/custom_metric.py | 548 ---------------------------------- 1 file changed, 548 deletions(-) delete mode 100644 graphrag_sdk/custom_metric.py diff --git a/graphrag_sdk/custom_metric.py b/graphrag_sdk/custom_metric.py deleted file mode 100644 index 78b570e7..00000000 --- a/graphrag_sdk/custom_metric.py +++ /dev/null @@ -1,548 +0,0 @@ -from typing import Optional -from deepeval.metrics import BaseMetric, AnswerRelevancyMetric, FaithfulnessMetric, ContextualRelevancyMetric -from deepeval.test_case import LLMTestCase -from typing import Optional, List, Union - -from deepeval.utils import get_or_create_event_loop, prettify_list -from deepeval.metrics.utils import ( - construct_verbose_logs, - trimAndLoadJson, - check_llm_test_case_params, - initialize_model, -) -from deepeval.test_case import ( - LLMTestCase, - LLMTestCaseParams, - ConversationalTestCase, -) - -from deepeval.metrics.contextual_relevancy.schema import * -from deepeval.metrics import BaseMetric -from deepeval.models import DeepEvalBaseLLM -from deepeval.metrics.contextual_recall.template import ContextualRecallTemplate -from deepeval.metrics.indicator import metric_progress_indicator -from deepeval.metrics.contextual_recall.schema import * - -required_params: List[LLMTestCaseParams] = [ - LLMTestCaseParams.INPUT, - LLMTestCaseParams.ACTUAL_OUTPUT, - LLMTestCaseParams.RETRIEVAL_CONTEXT, - LLMTestCaseParams.EXPECTED_OUTPUT, -] - -class CombineMetrics(BaseMetric): - def __init__( - self, - threshold: float = 0.5, - evaluation_model: Optional[str] = "gpt-4o", - include_reason: bool = True, - async_mode: bool = True, - strict_mode: bool = False, - ): - self.threshold = 1 if strict_mode else threshold - self.evaluation_model = evaluation_model - self.include_reason = include_reason - self.async_mode = async_mode - self.strict_mode = strict_mode - - def measure(self, test_case: LLMTestCase): - try: - relevancy_metric, faithfulness_metric, graph_context_recall_metric = self.initialize_metrics() - # Remember, deepeval's default metrics follow the same pattern as your custom metric! - graph_context_recall_metric.measure(test_case) - relevancy_metric.measure(test_case) - faithfulness_metric.measure(test_case) - - # Custom logic to set score, reason, and success - self.set_score_reason_success(relevancy_metric, faithfulness_metric, graph_context_recall_metric) - return self.score - except Exception as e: - # Set and re-raise error - self.error = str(e) - raise - - - def is_successful(self) -> bool: - if self.error is not None: - self.success = False - else: - return self.success - - @property - def __name__(self): - return "Composite Relevancy Faithfulness Metric" - - - ###################### - ### Helper methods ### - ###################### - def initialize_metrics(self): - graph_context_recall_metric = GraphContextualRelevancy( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - strict_mode=self.strict_mode - ) - - graph_context_recall_metric = GraphContextualRecall( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - strict_mode=self.strict_mode - ) - - relevancy_metric = AnswerRelevancyMetric( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - async_mode=self.async_mode, - strict_mode=self.strict_mode - ) - faithfulness_metric = FaithfulnessMetric( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - async_mode=self.async_mode, - strict_mode=self.strict_mode - ) - return relevancy_metric, faithfulness_metric, graph_context_recall_metric - - def set_score_reason_success( - self, - relevancy_metric: BaseMetric, - faithfulness_metric: BaseMetric, - graph_context_recall_metric: BaseMetric - ): - # Get scores and reasons for both - relevancy_score = relevancy_metric.score - relevancy_reason = relevancy_metric.reason - faithfulness_score = faithfulness_metric.score - faithfulness_reason = faithfulness_metric.reason - graph_context_recall_metric_score = graph_context_recall_metric.score - graph_context_recall_metric_reason = graph_context_recall_metric.reason - - # Custom logic to set score - composite_score = min(relevancy_score, faithfulness_score, graph_context_recall_metric_score) - self.score = 0 if self.strict_mode and composite_score < self.threshold else composite_score - - # Custom logic to set reason - if self.include_reason: - self.reason = relevancy_reason + "\n" + faithfulness_reason + "\n" + graph_context_recall_metric_reason - - # Custom logic to set success - self.success = self.score >= self.threshold - - - -class GraphContextualRecall(BaseMetric): - def __init__( - self, - threshold: float = 0.5, - model: Optional[Union[str, DeepEvalBaseLLM]] = None, - include_reason: bool = True, - strict_mode: bool = False, - verbose_mode: bool = False, - ): - self.threshold = 1 if strict_mode else threshold - self.model, self.using_native_model = initialize_model(model) - self.evaluation_model = self.model.get_model_name() - self.include_reason = include_reason - self.strict_mode = strict_mode - self.verbose_mode = verbose_mode - - def measure( - self, - test_case: LLMTestCase, - _show_indicator: bool = True, - ) -> float: - check_llm_test_case_params(test_case, required_params, self) - - self.evaluation_cost = 0 if self.using_native_model else None - with metric_progress_indicator(self, _show_indicator=_show_indicator): - self.verdicts: List[ContextualRecallVerdict] = ( - self._generate_verdicts( - test_case.expected_output, test_case.retrieval_context, test_case.additional_metadata - ) - ) - self.score = self._calculate_score() - self.reason = self._generate_reason(test_case.expected_output) - self.success = self.score >= self.threshold - self.verbose_logs = construct_verbose_logs( - self, - steps=[ - f"Verdicts:\n{prettify_list(self.verdicts)}", - f"Score: {self.score}\nReason: {self.reason}", - ], - ) - - return self.score - - def _generate_reason(self, expected_output: str): - if self.include_reason is False: - return None - - supportive_reasons = [] - unsupportive_reasons = [] - for verdict in self.verdicts: - if verdict.verdict.lower() == "yes": - supportive_reasons.append(verdict.reason) - else: - unsupportive_reasons.append(verdict.reason) - - prompt = GraphContextualRecallTemplate.generate_reason( - expected_output=expected_output, - supportive_reasons=supportive_reasons, - unsupportive_reasons=unsupportive_reasons, - score=format(self.score, ".2f"), - ) - - if self.using_native_model: - res, cost = self.model.generate(prompt) - self.evaluation_cost += cost - data = trimAndLoadJson(res, self) - return data["reason"] - else: - try: - res: Reason = self.model.generate(prompt, schema=Reason) - return res.reason - except TypeError: - res = self.model.generate(prompt) - data = trimAndLoadJson(res, self) - return data["reason"] - - def _calculate_score(self): - number_of_verdicts = len(self.verdicts) - if number_of_verdicts == 0: - return 0 - - justified_sentences = 0 - for verdict in self.verdicts: - if verdict.verdict.lower() == "yes": - justified_sentences += 1 - - score = justified_sentences / number_of_verdicts - return 0 if self.strict_mode and score < self.threshold else score - - def _generate_verdicts( - self, expected_output: str, retrieval_context: List[str], cypher_query: Optional[str] = None - ) -> List[ContextualRecallVerdict]: - prompt = GraphContextualRecallTemplate.generate_verdicts( - expected_output=expected_output, retrieval_context=retrieval_context, cypher_query=cypher_query - ) - if self.using_native_model: - res, cost = self.model.generate(prompt) - self.evaluation_cost += cost - data = trimAndLoadJson(res, self) - verdicts = [ - ContextualRecallVerdict(**item) for item in data["verdicts"] - ] - return verdicts - else: - try: - res: Verdicts = self.model.generate(prompt, schema=Verdicts) - verdicts: Verdicts = [item for item in res.verdicts] - return verdicts - except TypeError: - res = self.model.generate(prompt) - data = trimAndLoadJson(res, self) - verdicts = [ - ContextualRecallVerdict(**item) for item in data["verdicts"] - ] - return verdicts - - def is_successful(self) -> bool: - if self.error is not None: - self.success = False - else: - try: - self.success = self.score >= self.threshold - except: - self.success = False - return self.success - - @property - def __name__(self): - return "Graph Contextual Recall" - -class GraphContextualRecallTemplate: - @staticmethod - def generate_reason( - expected_output, supportive_reasons, unsupportive_reasons, score - ): - return f""" -Given the original expected output, a list of supportive reasons, and a list of unsupportive reasons (which is deduced directly from the 'expected output'), and a contextual recall score (closer to 1 the better), summarize a CONCISE reason for the score. -A supportive reason is the reason why a certain sentence in the original expected output can be attributed to the node in the retrieval context. -An unsupportive reason is the reason why a certain sentence in the original expected output cannot be attributed to anything in the retrieval context. -In your reason, you should related supportive/unsupportive reasons to the sentence number in expected output, and info regarding the node number in retrieval context to support your final reason. The first mention of "node(s)" should specify "node(s) in retrieval context)". - -** -IMPORTANT: Please make sure to only return in JSON format, with the 'reason' key providing the reason. -Example JSON: -{{ - "reason": "The score is because ." -}} - -DO NOT mention 'supportive reasons' and 'unsupportive reasons' in your reason, these terms are just here for you to understand the broader scope of things. -If the score is 1, keep it short and say something positive with an upbeat encouraging tone (but don't overdo it otherwise it gets annoying). -** - -Contextual Recall Score: -{score} - -Expected Output: -{expected_output} - -Supportive Reasons: -{supportive_reasons} - -Unsupportive Reasons: -{unsupportive_reasons} - -JSON: -""" - - @staticmethod - def generate_verdicts(expected_output, retrieval_context, cypher_query): - return f""" -For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts that generated from the cypher query. Please generate a list of JSON with two keys: `verdict` and `reason`. -The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context and the cypher query, else answer 'no'. -The `reason` key should provide a reason why to the verdict. In the reason, you should aim to include the node(s) count in the retrieval context (eg., 1st node, and 2nd node in the retrieval context) that is attributed to said sentence. You should also aim to quote the specific part of the retrieval context to justify your verdict, but keep it extremely concise and cut short the quote with an ellipsis if possible. - - -** -IMPORTANT: Please make sure to only return in JSON format, with the 'verdicts' key as a list of JSON objects, each with two keys: `verdict` and `reason`. - -{{ - "verdicts": [ - {{ - "verdict": "yes", - "reason": "..." - }}, - ... - ] -}} - -Since you are going to generate a verdict for each sentence, the number of 'verdicts' SHOULD BE STRICTLY EQUAL to the number of sentences in of `expected output`. -** - -Expected Output: -{expected_output} - -Cypher Query: -{cypher_query} - -Retrieval Context: -{retrieval_context} - -JSON: -""" - -class GraphContextualRelevancy(BaseMetric): - def __init__( - self, - threshold: float = 0.5, - model: Optional[Union[str, DeepEvalBaseLLM]] = None, - include_reason: bool = True, - async_mode: bool = True, - strict_mode: bool = False, - verbose_mode: bool = False, - ): - self.threshold = 1 if strict_mode else threshold - self.model, self.using_native_model = initialize_model(model) - self.evaluation_model = self.model.get_model_name() - self.include_reason = include_reason - self.async_mode = async_mode - self.strict_mode = strict_mode - self.verbose_mode = verbose_mode - - def measure( - self, - test_case: Union[LLMTestCase, ConversationalTestCase], - _show_indicator: bool = True, - ) -> float: - if isinstance(test_case, ConversationalTestCase): - test_case = test_case.turns[0] - check_llm_test_case_params(test_case, required_params, self) - - self.evaluation_cost = 0 if self.using_native_model else None - with metric_progress_indicator(self, _show_indicator=_show_indicator): - if self.async_mode: - loop = get_or_create_event_loop() - loop.run_until_complete( - self.a_measure(test_case, _show_indicator=False) - ) - else: - self.verdicts_list: List[ContextualRelevancyVerdicts] = [ - (self._generate_verdicts(test_case.input, context)) - for context in test_case.retrieval_context - ] - self.score = self._calculate_score() - self.reason = self._generate_reason(test_case.input) - self.success = self.score >= self.threshold - self.verbose_logs = construct_verbose_logs( - self, - steps=[ - f"Verdicts:\n{prettify_list(self.verdicts_list)}", - f"Score: {self.score}\nReason: {self.reason}", - ], - ) - - return self.score - - def _generate_reason(self, input: str): - if self.include_reason is False: - return None - - irrelevancies = [] - relevant_statements = [] - for verdicts in self.verdicts_list: - for verdict in verdicts.verdicts: - if verdict.verdict.lower() == "no": - irrelevancies.append(verdict.reason) - else: - relevant_statements.append(verdict.statement) - - prompt: dict = GraphContextualRelevancyTemplate.generate_reason( - input=input, - irrelevancies=irrelevancies, - relevant_statements=relevant_statements, - score=format(self.score, ".2f"), - ) - if self.using_native_model: - res, cost = self.model.generate(prompt) - self.evaluation_cost += cost - data = trimAndLoadJson(res, self) - return data["reason"] - else: - try: - res: Reason = self.model.generate(prompt, schema=Reason) - return res.reason - except TypeError: - res = self.model.generate(prompt) - data = trimAndLoadJson(res, self) - return data["reason"] - - def _calculate_score(self): - total_verdicts = 0 - relevant_statements = 0 - for verdicts in self.verdicts_list: - for verdict in verdicts.verdicts: - total_verdicts += 1 - if verdict.verdict.lower() == "yes": - relevant_statements += 1 - - if total_verdicts == 0: - return 0 - - score = relevant_statements / total_verdicts - return 0 if self.strict_mode and score < self.threshold else score - - def _generate_verdicts( - self, input: str, context: str - ) -> ContextualRelevancyVerdicts: - prompt = GraphContextualRelevancyTemplate.generate_verdicts( - input=input, context=context - ) - if self.using_native_model: - res, cost = self.model.generate(prompt) - self.evaluation_cost += cost - data = trimAndLoadJson(res, self) - return ContextualRelevancyVerdicts(**data) - else: - try: - res = self.model.generate( - prompt, schema=ContextualRelevancyVerdicts - ) - return res - except TypeError: - res = self.model.generate(prompt) - data = trimAndLoadJson(res, self) - return ContextualRelevancyVerdicts(**data) - - def is_successful(self) -> bool: - if self.error is not None: - self.success = False - else: - try: - self.success = self.score >= self.threshold - except: - self.success = False - return self.success - - @property - def __name__(self): - return "Graph Contextual Relevancy" - -class GraphContextualRelevancyTemplate: - @staticmethod - def generate_reason( - input: str, - irrelevancies: List[str], - relevant_statements: List[str], - score: float, - ): - return f"""Based on the given input, reasons for why the retrieval context is irrelevant to the input, the statements in the retrieval context that is actually relevant to the retrieval context, and the contextual relevancy score (the closer to 1 the better), please generate a CONCISE reason for the score. -In your reason, you should quote data provided in the reasons for irrelevancy and relevant statements to support your point. - -** -IMPORTANT: Please make sure to only return in JSON format, with the 'reason' key providing the reason. -Example JSON: -{{ - "reason": "The score is because ." -}} - -If the score is 1, keep it short and say something positive with an upbeat encouraging tone (but don't overdo it otherwise it gets annoying). -** - - -Contextual Relevancy Score: -{score} - -Input: -{input} - -Reasons for why the retrieval context is irrelevant to the input: -{irrelevancies} - -Statement in the retrieval context that is relevant to the input: -{relevant_statements} - -JSON: -""" - - @staticmethod - def generate_verdicts(input: str, context: str): - return f"""Based on the input and context, please generate a JSON object to indicate whether each statement found in the context is relevant to the provided input. The JSON will be a list of 'verdicts', with 2 mandatory fields: 'verdict' and 'statement', and 1 optional field: 'reason'. -You should first extract statements found in the context, which are high level information found in the context, before deciding on a verdict and optionally a reason for each statement. -The 'verdict' key should STRICTLY be either 'yes' or 'no', and states whether the statement is relevant to the input. -Provide a 'reason' ONLY IF verdict is no. You MUST quote the irrelevant parts of the statement to back up your reason. - -** -IMPORTANT: Please make sure to only return in JSON format. -Example Context: "Einstein won the Nobel Prize for his discovery of the photoelectric effect. He won the Nobel Prize in 1968. There was a cat." -Example Input: "What were some of Einstein's achievements?" - -Example: -{{ - "verdicts": [ - {{ - "verdict": "yes", - "statement": "Einstein won the Nobel Prize for his discovery of the photoelectric effect in 1968", - }}, - {{ - "verdict": "no", - "statement": "There was a cat.", - "reason": "The retrieval context contained the information 'There was a cat' when it has nothing to do with Einstein's achievements." - }} - ] -}} -** - -Input: -{input} - -Context: -{context} - -JSON: -""" From ee5244a970c122533bf3f7e48ced7c240213de97 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 29 Jan 2025 11:01:57 +0200 Subject: [PATCH 008/136] update-poetry --- poetry.lock | 250 ++++++++++++++++++++++++++----------------------- pyproject.toml | 5 +- 2 files changed, 135 insertions(+), 120 deletions(-) diff --git a/poetry.lock b/poetry.lock index 12ee0572..d3eeed57 100644 --- a/poetry.lock +++ b/poetry.lock @@ -698,18 +698,18 @@ files = [ [[package]] name = "deepeval" 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{file = "opentelemetry_proto-1.27.0-py3-none-any.whl", hash = "sha256:b133873de5581a50063e1e4b29cdcf0c5e253a8c2d8dc1229add20a4c3830ace"}, - {file = "opentelemetry_proto-1.27.0.tar.gz", hash = "sha256:33c9345d91dafd8a74fc3d7576c5a38f18b7fdf8d02983ac67485386132aedd6"}, + {file = "opentelemetry_proto-1.29.0-py3-none-any.whl", hash = "sha256:495069c6f5495cbf732501cdcd3b7f60fda2b9d3d4255706ca99b7ca8dec53ff"}, + {file = "opentelemetry_proto-1.29.0.tar.gz", hash = "sha256:3c136aa293782e9b44978c738fff72877a4b78b5d21a64e879898db7b2d93e5d"}, ] [package.dependencies] -protobuf = ">=3.19,<5.0" +protobuf = ">=5.0,<6.0" [[package]] name = "opentelemetry-sdk" -version = "1.27.0" +version = "1.29.0" description = "OpenTelemetry Python SDK" optional = false python-versions = ">=3.8" files = [ - {file = "opentelemetry_sdk-1.27.0-py3-none-any.whl", hash = "sha256:365f5e32f920faf0fd9e14fdfd92c086e317eaa5f860edba9cdc17a380d9197d"}, - {file = "opentelemetry_sdk-1.27.0.tar.gz", hash = "sha256:d525017dea0ccce9ba4e0245100ec46ecdc043f2d7b8315d56b19aff0904fa6f"}, + {file = "opentelemetry_sdk-1.29.0-py3-none-any.whl", hash = "sha256:173be3b5d3f8f7d671f20ea37056710217959e774e2749d984355d1f9391a30a"}, + {file = "opentelemetry_sdk-1.29.0.tar.gz", hash = "sha256:b0787ce6aade6ab84315302e72bd7a7f2f014b0fb1b7c3295b88afe014ed0643"}, ] [package.dependencies] -opentelemetry-api = "1.27.0" -opentelemetry-semantic-conventions = "0.48b0" +opentelemetry-api = "1.29.0" +opentelemetry-semantic-conventions = "0.50b0" typing-extensions = ">=3.7.4" [[package]] name = "opentelemetry-semantic-conventions" -version = "0.48b0" +version = "0.50b0" description = "OpenTelemetry Semantic Conventions" optional = false python-versions = ">=3.8" files = [ - {file = "opentelemetry_semantic_conventions-0.48b0-py3-none-any.whl", hash = "sha256:a0de9f45c413a8669788a38569c7e0a11ce6ce97861a628cca785deecdc32a1f"}, - {file = "opentelemetry_semantic_conventions-0.48b0.tar.gz", hash = "sha256:12d74983783b6878162208be57c9effcb89dc88691c64992d70bb89dc00daa1a"}, + {file = "opentelemetry_semantic_conventions-0.50b0-py3-none-any.whl", hash = "sha256:e87efba8fdb67fb38113efea6a349531e75ed7ffc01562f65b802fcecb5e115e"}, + {file = "opentelemetry_semantic_conventions-0.50b0.tar.gz", hash = "sha256:02dc6dbcb62f082de9b877ff19a3f1ffaa3c306300fa53bfac761c4567c83d38"}, ] [package.dependencies] deprecated = ">=1.2.6" -opentelemetry-api = "1.27.0" +opentelemetry-api = "1.29.0" [[package]] name = "orjson" @@ -3255,9 +3273,9 @@ files = [ [package.dependencies] numpy = [ - {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, - {version = ">=1.23.2", markers = "python_version == \"3.11\""}, {version = ">=1.22.4", markers = "python_version < \"3.11\""}, + {version = ">=1.23.2", markers = "python_version == \"3.11\""}, + {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, ] python-dateutil = ">=2.8.2" pytz = ">=2020.1" @@ -3931,9 +3949,6 @@ files = [ {file = "python_json_logger-3.2.1.tar.gz", hash = "sha256:8eb0554ea17cb75b05d2848bc14fb02fbdbd9d6972120781b974380bfa162008"}, ] -[package.dependencies] -typing_extensions = {version = "*", markers = "python_version < \"3.10\""} - [package.extras] dev = ["backports.zoneinfo", "black", "build", "freezegun", "mdx_truly_sane_lists", "mike", "mkdocs", "mkdocs-awesome-pages-plugin", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-material (>=8.5)", "mkdocstrings[python]", "msgspec", "msgspec-python313-pre", "mypy", "orjson", "pylint", "pytest", "tzdata", "validate-pyproject[all]"] @@ -4745,7 +4760,6 @@ babel = ">=2.13" colorama = {version = ">=0.4.6", markers = "sys_platform == \"win32\""} docutils = ">=0.20,<0.22" imagesize = ">=1.3" -importlib-metadata = {version = ">=6.0", markers = "python_version < \"3.10\""} Jinja2 = ">=3.1" packaging = ">=23.0" Pygments = ">=2.17" @@ -5652,5 +5666,5 @@ vertexai = ["vertexai"] [metadata] lock-version = "2.0" -python-versions = "^3.9.0" -content-hash = "9d74dd952f3ff059eb933b4e814ea450d21b725ab8fbce5008dbb9817ae37868" +python-versions = ">=3.10.0,<3.14" +content-hash = "2d7951ca5051488cc9fa02c12251d8ccd6e4ea4a88e8abba021130c079b2c2b7" diff --git a/pyproject.toml b/pyproject.toml index 267f8c75..3411e2fa 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,7 +10,7 @@ homepage = "http://RAG-SDK.readthedocs.io" keywords = ['RAG', 'Graph-RAG', 'KnowledgeGraph'] [tool.poetry.dependencies] -python = "^3.9.0" +python = ">=3.10.0,<3.14" falkordb = "^1.0.9" typing-extensions = "^4.12.1" bs4 = "^0.0.2" @@ -21,8 +21,9 @@ python-abc = "^0.2.0" ratelimit = "^2.2.1" python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" +rich = "^13.9.4" ipykernel = "^6.29.5" -deepeval = { version = "^2.0.9", python = ">=3.9,<3.13" } +deepeval = "^2.2.6" vertexai = { version = "^1.49.0", optional = true } ollama = { version = "^0.2.1", optional = true } openai = { version = "^1.35.9", optional = true } From 5bf6681ebb169b73a9203220caf4ea3b3ddff4f9 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 29 Jan 2025 11:10:24 +0200 Subject: [PATCH 009/136] provider-fix --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 52f454af..e59cfe98 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -27,7 +27,7 @@ jobs: strategy: matrix: - model: [gemini-1.5-flash-001, gpt-4o] # List of models + model: [gemini/gemini-1.5-flash-001, openai/gpt-4o] # List of models steps: - uses: actions/checkout@v4 From 4f599af0fdf3a35b1f84eb3ab6e0d2a1d04b3514 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 29 Jan 2025 11:52:27 +0200 Subject: [PATCH 010/136] key --- .github/workflows/test.yml | 1 + graphrag_sdk/test_metrics.py | 14 ++++---------- tests/test_rag.py | 10 +++++----- 3 files changed, 10 insertions(+), 15 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index e59cfe98..fec17723 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -77,5 +77,6 @@ jobs: REGION: ${{ vars.REGION }} OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} + GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} TEST_MODEL: ${{ matrix.model }} # Pass the model as an environment variable run: poetry run pytest diff --git a/graphrag_sdk/test_metrics.py b/graphrag_sdk/test_metrics.py index 7c17174f..a3de61ae 100644 --- a/graphrag_sdk/test_metrics.py +++ b/graphrag_sdk/test_metrics.py @@ -229,7 +229,7 @@ def _generate_verdicts( self, expected_output: str, retrieval_context: List[str], cypher_query: Optional[str] = None ) -> List[ContextualRecallVerdict]: prompt = GraphContextualRecallTemplate.generate_verdicts( - expected_output=expected_output, retrieval_context=retrieval_context, cypher_query=cypher_query + expected_output=expected_output, retrieval_context=retrieval_context ) if self.using_native_model: res, cost = self.model.generate(prompt) @@ -304,7 +304,7 @@ def generate_reason( """ @staticmethod - def generate_verdicts(expected_output, retrieval_context, cypher_query): + def generate_verdicts(expected_output, retrieval_context): return f""" For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts that generated from the cypher query. Please generate a list of JSON with two keys: `verdict` and `reason`. The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context and the cypher query, else answer 'no'. @@ -330,9 +330,6 @@ def generate_verdicts(expected_output, retrieval_context, cypher_query): Expected Output: {expected_output} -Cypher Query: -{cypher_query} - Retrieval Context: {retrieval_context} @@ -435,7 +432,7 @@ def _generate_verdicts( self, input: str, context: str, cypher_query: Optional[str] = None ) -> ContextualRelevancyVerdicts: prompt = GraphContextualRelevancyTemplate.generate_verdicts( - input=input, context=context, cypher_query=cypher_query + input=input, context=context ) if self.using_native_model: res, cost = self.model.generate(prompt) @@ -505,7 +502,7 @@ def generate_reason( """ @staticmethod - def generate_verdicts(input: str, context: str, cypher_query): + def generate_verdicts(input: str, context: str): return f"""Based on the input and context (cypher and query output), please generate a JSON object to indicate whether each statement found in the context is relevant to the provided input. The JSON will be a list of 'verdicts', with 2 mandatory fields: 'verdict' and 'statement', and 1 optional field: 'reason'. You should first extract statements found in the context, which are high level information found in the context, before deciding on a verdict and optionally a reason for each statement. The 'verdict' key should STRICTLY be either 'yes' or 'no', and states whether the statement is relevant to the input. @@ -535,9 +532,6 @@ def generate_verdicts(input: str, context: str, cypher_query): Input: {input} -Cypher Query: -{cypher_query} - Context: {context} diff --git a/tests/test_rag.py b/tests/test_rag.py index 3474c15c..ab784f4e 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -107,7 +107,7 @@ def test_llm(self): "No, Melony Feliciano acted as a background extra in Madoff: The Monster of Wall Street.", ] - answer_faithful_relevancy_metric = CombineMetrics(threshold=0.5) + answer_combined_metric = CombineMetrics(threshold=0.5) scores = [] for input_text, expected_output in zip(inputs, expected_outputs): @@ -117,14 +117,14 @@ def test_llm(self): test_case = LLMTestCase( input=input_text, actual_output=answer["response"], - retrieval_context=[answer["context"]], - context=[answer["context"]], + retrieval_context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], + context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], name="kg_test", expected_output=expected_output, - additional_metadata={"cypher_query": answer["cypher"]}, + additional_metadata=None, ) - score = answer_faithful_relevancy_metric.measure(test_case) + score = answer_combined_metric.measure(test_case) scores.append(score) assert np.mean(scores) >= 0.8 From 478e6734beb9258c164ade76db863afcfc9dc229 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 29 Jan 2025 12:04:09 +0200 Subject: [PATCH 011/136] dec-threshold --- tests/test_rag.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_rag.py b/tests/test_rag.py index ab784f4e..c53fcc32 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -119,7 +119,7 @@ def test_llm(self): actual_output=answer["response"], retrieval_context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], - name="kg_test", + name="kg_rag_test", expected_output=expected_output, additional_metadata=None, ) @@ -127,4 +127,4 @@ def test_llm(self): score = answer_combined_metric.measure(test_case) scores.append(score) - assert np.mean(scores) >= 0.8 + assert np.mean(scores) >= 0.5 From 7f611f7de952f3cd2b24f32a75901e6717a9101d Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 29 Jan 2025 12:24:43 +0200 Subject: [PATCH 012/136] fix-temp --- tests/test_rag.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/tests/test_rag.py b/tests/test_rag.py index c53fcc32..9543a2f9 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -10,7 +10,7 @@ from graphrag_sdk.ontology import Ontology from graphrag_sdk.models.litellm import LiteModel from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig from graphrag_sdk.test_metrics import CombineMetrics os.environ["DEEPEVAL_ENABLE_TELEMETRY"] = "NO" @@ -75,7 +75,8 @@ def setUpClass(cls): cls.graph_name = "IMDB_deep" # Use the model name from the environment variable - model = LiteModel(model_name=model_name) + model = LiteModel(model_name=model_name, generation_config=GenerativeModelConfig(temperature=0)) + cls.kg = KnowledgeGraph( name=cls.graph_name, From 24e92114688ef021f3eeb9f836da71899ae838e1 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 4 Feb 2025 15:19:45 +0200 Subject: [PATCH 013/136] update-tests --- graphrag_sdk/fixtures/prompts.py | 10 ++--- graphrag_sdk/models/litellm.py | 2 +- graphrag_sdk/test_metrics.py | 70 ++++++++++++++++---------------- tests/test_rag.py | 11 +++-- 4 files changed, 43 insertions(+), 50 deletions(-) diff --git a/graphrag_sdk/fixtures/prompts.py b/graphrag_sdk/fixtures/prompts.py index 929af0af..1f79c5d8 100644 --- a/graphrag_sdk/fixtures/prompts.py +++ b/graphrag_sdk/fixtures/prompts.py @@ -433,12 +433,9 @@ For example, given the question "Which managers own Neo4j stocks?", the OpenCypher statement should look like this: -``` MATCH (m:Manager)-[:OWNS]->(s:Stock) WHERE s.name CONTAINS 'Neo4j' -RETURN m, s -``` -""" +RETURN m, s""" CYPHER_GEN_PROMPT = """ Using the ontology provided, generate an OpenCypher statement to query the graph database returning all relevant entities, relationships, and attributes to answer the question below. @@ -447,7 +444,7 @@ Please think if your answer is a valid Cypher query, and correct it if it is not. Question: {question} -""" +Your generated Cypher: """ CYPHER_GEN_PROMPT_WITH_ERROR = """ @@ -472,9 +469,8 @@ Respect the order of the relationships; the arrows should always point from the "source" to the "target". Last Answer: {last_answer} - Question: {question} -""" +Your generated Cypher: """ GRAPH_QA_SYSTEM = """ You are an assistant that helps to form nice and human understandable answers. diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 288e6a1d..4052ffb8 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -74,7 +74,7 @@ def check_valid_key(self, model: str): model=model, messages=messages, max_tokens=10 ) return True - except: + except Exception as e: return False def check_and_pull_model(self) -> None: diff --git a/graphrag_sdk/test_metrics.py b/graphrag_sdk/test_metrics.py index a3de61ae..be264969 100644 --- a/graphrag_sdk/test_metrics.py +++ b/graphrag_sdk/test_metrics.py @@ -47,15 +47,14 @@ def __init__( def measure(self, test_case: LLMTestCase): try: - relevancy_metric, faithfulness_metric, graph_context_recall_metric, graph_context_relevancy_metric = self.initialize_metrics() + graph_context_recall_metric, graph_context_relevancy_metric = self.initialize_metrics() # Remember, deepeval's default metrics follow the same pattern as your custom metric! + # relevancy_metric.measure(test_case) graph_context_relevancy_metric.measure(test_case) graph_context_recall_metric.measure(test_case) - relevancy_metric.measure(test_case) - faithfulness_metric.measure(test_case) - + # Custom logic to set score, reason, and success - self.set_score_reason_success(relevancy_metric, faithfulness_metric, graph_context_recall_metric, graph_context_relevancy_metric) + self.set_score_reason_success(graph_context_recall_metric, graph_context_relevancy_metric) return self.score except Exception as e: # Set and re-raise error @@ -71,7 +70,7 @@ def is_successful(self) -> bool: @property def __name__(self): - return "Composite Relevancy Faithfulness Metric" + return "Composite Graph Context Metric" ###################### @@ -92,46 +91,39 @@ def initialize_metrics(self): strict_mode=self.strict_mode ) - relevancy_metric = AnswerRelevancyMetric( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - async_mode=self.async_mode, - strict_mode=self.strict_mode - ) - faithfulness_metric = FaithfulnessMetric( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - async_mode=self.async_mode, - strict_mode=self.strict_mode - ) - return relevancy_metric, faithfulness_metric, graph_context_recall_metric, graph_context_relevancy_metric + # relevancy_metric = AnswerRelevancyMetric( + # threshold=self.threshold, + # model=self.evaluation_model, + # include_reason=self.include_reason, + # async_mode=self.async_mode, + # strict_mode=self.strict_mode + # ) + # faithfulness_metric = FaithfulnessMetric( + # threshold=self.threshold, + # model=self.evaluation_model, + # include_reason=self.include_reason, + # async_mode=self.async_mode, + # strict_mode=self.strict_mode + # ) + return graph_context_recall_metric, graph_context_relevancy_metric def set_score_reason_success( self, - relevancy_metric: BaseMetric, - faithfulness_metric: BaseMetric, graph_context_recall_metric: BaseMetric, graph_context_relevancy_metric: BaseMetric, ): - # Get scores and reasons for both - relevancy_score = relevancy_metric.score - relevancy_reason = relevancy_metric.reason - faithfulness_score = faithfulness_metric.score - faithfulness_reason = faithfulness_metric.reason graph_context_recall_metric_score = graph_context_recall_metric.score graph_context_recall_metric_reason = graph_context_recall_metric.reason graph_context_relevancy_metric_score = graph_context_relevancy_metric.score graph_context_relevancy_metric_reason = graph_context_relevancy_metric.reason # Custom logic to set score - composite_score = min(relevancy_score, faithfulness_score, graph_context_recall_metric_score, graph_context_relevancy_metric_score) + composite_score = min(graph_context_recall_metric_score, graph_context_relevancy_metric_score) self.score = 0 if self.strict_mode and composite_score < self.threshold else composite_score # Custom logic to set reason if self.include_reason: - self.reason = relevancy_reason + "\n" + faithfulness_reason + "\n" + graph_context_recall_metric_reason + "\n" + graph_context_relevancy_metric_reason + self.reason = graph_context_recall_metric_reason + "\n" + graph_context_relevancy_metric_reason # Custom logic to set success self.success = self.score >= self.threshold @@ -229,7 +221,7 @@ def _generate_verdicts( self, expected_output: str, retrieval_context: List[str], cypher_query: Optional[str] = None ) -> List[ContextualRecallVerdict]: prompt = GraphContextualRecallTemplate.generate_verdicts( - expected_output=expected_output, retrieval_context=retrieval_context + expected_output=expected_output, retrieval_context=retrieval_context, cypher_query=cypher_query ) if self.using_native_model: res, cost = self.model.generate(prompt) @@ -304,10 +296,10 @@ def generate_reason( """ @staticmethod - def generate_verdicts(expected_output, retrieval_context): + def generate_verdicts(expected_output, retrieval_context, cypher_query): return f""" -For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts that generated from the cypher query. Please generate a list of JSON with two keys: `verdict` and `reason`. -The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context and the cypher query, else answer 'no'. +For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts (cypher query and its output). Please generate a list of JSON with two keys: `verdict` and `reason`. +The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context (cypher query and its output), else answer 'no'. The `reason` key should provide a reason why to the verdict. In the reason, you should aim to include the node(s) count in the retrieval context (eg., 1st node, and 2nd node in the retrieval context) that is attributed to said sentence. You should also aim to quote the specific part of the retrieval context to justify your verdict, but keep it extremely concise and cut short the quote with an ellipsis if possible. @@ -330,6 +322,9 @@ def generate_verdicts(expected_output, retrieval_context): Expected Output: {expected_output} +Cypher Query: +{cypher_query} + Retrieval Context: {retrieval_context} @@ -432,7 +427,7 @@ def _generate_verdicts( self, input: str, context: str, cypher_query: Optional[str] = None ) -> ContextualRelevancyVerdicts: prompt = GraphContextualRelevancyTemplate.generate_verdicts( - input=input, context=context + input=input, context=context, cypher_query=cypher_query ) if self.using_native_model: res, cost = self.model.generate(prompt) @@ -502,7 +497,7 @@ def generate_reason( """ @staticmethod - def generate_verdicts(input: str, context: str): + def generate_verdicts(input: str, context: str, cypher_query: Optional[str] = None): return f"""Based on the input and context (cypher and query output), please generate a JSON object to indicate whether each statement found in the context is relevant to the provided input. The JSON will be a list of 'verdicts', with 2 mandatory fields: 'verdict' and 'statement', and 1 optional field: 'reason'. You should first extract statements found in the context, which are high level information found in the context, before deciding on a verdict and optionally a reason for each statement. The 'verdict' key should STRICTLY be either 'yes' or 'no', and states whether the statement is relevant to the input. @@ -532,6 +527,9 @@ def generate_verdicts(input: str, context: str): Input: {input} +Cypher Query: +{cypher_query} + Context: {context} diff --git a/tests/test_rag.py b/tests/test_rag.py index 9543a2f9..b758e699 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -29,7 +29,7 @@ def setUpClass(cls): # Get the model name from the environment variable model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash-exp") - cls.ontology = Ontology([], []) + cls.ontology = Ontology() cls.ontology.add_entity( Entity( @@ -67,7 +67,7 @@ def setUpClass(cls): name="role", attr_type=AttributeType.STRING, unique=False, - required=False, + required=True, ), ], ) @@ -85,15 +85,15 @@ def setUpClass(cls): ) def test_llm(self): - file_path = "tests/data/madoff.txt" + url = "https://www.imdb.com/title/tt23732458/" - sources = [Source(file_path)] + sources = [Source(url)] self.kg.process_sources(sources) inputs = [ "How many actors acted in a movie?", "Which actors acted in the movie Madoff: The Monster of Wall Street?", - "What is the role of Joseph Scotto in Madoff: The Monster of Wall Street?", + "What is the role of Joseph Scotto in the movie Madoff: The Monster of Wall Street?", "Did Donna Pastorello act in Madoff: The Monster of Wall Street?", "Who played the role of Mark Madoff in Madoff: The Monster of Wall Street?", "Did Melony Feliciano have a named role in Madoff: The Monster of Wall Street?", @@ -107,7 +107,6 @@ def test_llm(self): "Alex Olson played the role of Mark Madoff in Madoff: The Monster of Wall Street.", "No, Melony Feliciano acted as a background extra in Madoff: The Monster of Wall Street.", ] - answer_combined_metric = CombineMetrics(threshold=0.5) scores = [] From 2ed1b9b642821e2b29ce28a57600c4584de76750 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 4 Feb 2025 16:21:33 +0200 Subject: [PATCH 014/136] fix-test-case --- requirements.txt | 54 ----------------------------------------------- tests/test_rag.py | 20 +++++++++--------- 2 files changed, 10 insertions(+), 64 deletions(-) delete mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 4fddf276..00000000 --- a/requirements.txt +++ /dev/null @@ -1,54 +0,0 @@ -appnope==0.1.4 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and platform_system == "Darwin" -asttokens==2.4.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -async-timeout==5.0.1 ; python_full_version >= "3.9.0" and python_full_version < "3.11.3" -backoff==2.2.1 ; python_full_version >= "3.9.0" and python_version < "4.0" -beautifulsoup4==4.12.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -bs4==0.0.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -certifi==2024.8.30 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -cffi==1.17.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" -charset-normalizer==3.4.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -colorama==0.4.6 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform == "win32" -comm==0.2.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -debugpy==1.8.8 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -decorator==5.1.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -exceptiongroup==1.2.2 ; python_version >= "3.9" and python_version < "3.11" -executing==2.1.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -falkordb==1.0.9 ; python_full_version >= "3.9.0" and python_version < "4.0" -fix-busted-json==0.0.18 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -idna==3.10 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -importlib-metadata==8.5.0 ; python_full_version >= "3.9.0" and python_version < "3.10" -ipykernel==6.29.5 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ipython==8.18.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -jedi==0.19.2 ; python_version >= "3.9" and python_full_version < "4.0.0" -jupyter-client==8.6.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -jupyter-core==5.7.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -matplotlib-inline==0.1.7 ; python_version >= "3.9" and python_full_version < "4.0.0" -nest-asyncio==1.6.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -packaging==24.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -parso==0.8.4 ; python_version >= "3.9" and python_full_version < "4.0.0" -pexpect==4.9.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" -platformdirs==4.3.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -prompt-toolkit==3.0.48 ; python_version >= "3.9" and python_full_version < "4.0.0" -psutil==6.1.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ptyprocess==0.7.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" -pure-eval==0.2.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -pycparser==2.22 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" -pygments==2.18.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -pypdf==4.3.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-abc==0.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-dateutil==2.9.0.post0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-dotenv==1.0.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -pywin32==308 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_full_version >= "3.9.0" and python_full_version < "4.0.0" -pyzmq==26.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ratelimit==2.2.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -redis==5.2.0 ; python_full_version >= "3.9.0" and python_version < "4.0" -requests==2.32.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -six==1.16.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -soupsieve==2.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -stack-data==0.6.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -tornado==6.4.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -traitlets==5.14.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -typing-extensions==4.12.2 ; python_version >= "3.9" and python_full_version < "4.0.0" -urllib3==2.2.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -wcwidth==0.2.13 ; python_version >= "3.9" and python_full_version < "4.0.0" -zipp==3.21.0 ; python_version >= "3.9" and python_version < "3.10" diff --git a/tests/test_rag.py b/tests/test_rag.py index b758e699..4e002598 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -27,7 +27,7 @@ class TestKGLiteLLM(unittest.TestCase): @classmethod def setUpClass(cls): # Get the model name from the environment variable - model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash-exp") + model_name = os.getenv("TEST_MODEL", "gemini/gemini-1.5-flash-001") cls.ontology = Ontology() @@ -72,7 +72,7 @@ def setUpClass(cls): ], ) ) - cls.graph_name = "IMDB_deep" + cls.graph_name = model_name.split("/")[0] # Use the model name from the environment variable model = LiteModel(model_name=model_name, generation_config=GenerativeModelConfig(temperature=0)) @@ -115,16 +115,16 @@ def test_llm(self): answer = chat.send_message(input_text) test_case = LLMTestCase( - input=input_text, - actual_output=answer["response"], - retrieval_context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], - context=["Cypher Query: " + answer["cypher"] + " Output: " + answer["context"]], - name="kg_rag_test", - expected_output=expected_output, - additional_metadata=None, + input=input_text, + actual_output=answer["response"], + retrieval_context=[answer["context"]], + context=[answer["context"]], + name="kg_rag_test", + expected_output=expected_output, + additional_metadata=answer["cypher"], ) - score = answer_combined_metric.measure(test_case) scores.append(score) + self.kg.delete() assert np.mean(scores) >= 0.5 From 687cc234b8d7678650838d31ec877a55fff68e88 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 4 Feb 2025 19:53:07 +0200 Subject: [PATCH 015/136] update-tests --- tests/test_rag.py | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/tests/test_rag.py b/tests/test_rag.py index 4e002598..de936587 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -27,7 +27,7 @@ class TestKGLiteLLM(unittest.TestCase): @classmethod def setUpClass(cls): # Get the model name from the environment variable - model_name = os.getenv("TEST_MODEL", "gemini/gemini-1.5-flash-001") + model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash-exp") cls.ontology = Ontology() @@ -92,20 +92,20 @@ def test_llm(self): self.kg.process_sources(sources) inputs = [ "How many actors acted in a movie?", - "Which actors acted in the movie Madoff: The Monster of Wall Street?", - "What is the role of Joseph Scotto in the movie Madoff: The Monster of Wall Street?", - "Did Donna Pastorello act in Madoff: The Monster of Wall Street?", - "Who played the role of Mark Madoff in Madoff: The Monster of Wall Street?", - "Did Melony Feliciano have a named role in Madoff: The Monster of Wall Street?", + "Which actors acted in a movie?", + "What is the role of Joseph Scotto in a movie?", + "Did Donna Pastorello act in a movie?", + "Who played the role of Mark Madoff in a movie?", + "Did Melony Feliciano have a named role in a movie?", ] expected_outputs = [ "Over than 10 actors acted in a movie.", - "Joseph Scotto, Melony Feliciano, and Donna Pastorello acted in the movie Madoff: The Monster of Wall Street.", - "Joseph Scotto played the role of Bernie Madoff in Madoff: The Monster of Wall Street.", - "Yes, Donna Pastorello acted in Madoff: The Monster of Wall Street as Eleanor Squillari.", - "Alex Olson played the role of Mark Madoff in Madoff: The Monster of Wall Street.", - "No, Melony Feliciano acted as a background extra in Madoff: The Monster of Wall Street.", + "Joseph Scotto, Melony Feliciano, and Donna Pastorello acted in a movie", + "Joseph Scotto played the role of Bernie Madoff in a movie.", + "Yes, Donna Pastorello acted in a movie as Eleanor Squillari.", + "Alex Olson played the role of Mark Madoff in a movie.", + "No, Melony Feliciano acted as a background extra in a movie.", ] answer_combined_metric = CombineMetrics(threshold=0.5) scores = [] From 1ed80d3b41e6074dcf7a36f7c96910f58a227b0a Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 4 Feb 2025 20:03:27 +0200 Subject: [PATCH 016/136] gemini-2 --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index fec17723..39625ef6 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -27,7 +27,7 @@ jobs: strategy: matrix: - model: [gemini/gemini-1.5-flash-001, openai/gpt-4o] # List of models + model: [gemini/gemini-2.0-flash-exp, openai/gpt-4o] # List of models steps: - uses: actions/checkout@v4 From ba759e638986674a1f1db4e692ae7b4e89b044df Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Mon, 24 Feb 2025 13:08:49 +0200 Subject: [PATCH 017/136] Update README.md to gemini-2.0-flash --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 328822b7..4d3cad29 100644 --- a/README.md +++ b/README.md @@ -35,9 +35,9 @@ pip install graphrag_sdk[litellm] ### Configure Credentials. See [.env](.env.template) for examples. * [LiteLLM](https://docs.litellm.ai): A framework supporting inference of large language models, allowing flexibility in deployment and use cases. - To choose vendor use the prefix "specific_vendor/your_model", for example "gemini/gemini-2.0-flash-exp". + To choose vendor use the prefix "specific_vendor/your_model", for example "gemini/gemini-2.0-flash". * [OpenAI](https://openai.com/index/openai-api) Recommended model:`gpt-4o` -* [Google](https://makersuite.google.com/app/apikey) Recommended model:`gemini-2.0-flash-exp` +* [Google](https://makersuite.google.com/app/apikey) Recommended model:`gemini-2.0-flash` * [Azure-OpenAI](https://ai.azure.com) Recommended model:`gpt-4o` * [Ollama](https://ollama.com/) Available only to the Q&A step. Recommended models: `llama3`. Ollama models are suitable for the Q&A step only (after the knowledge graph (KG) created). @@ -68,8 +68,8 @@ urls = ["https://www.rottentomatoes.com/m/side_by_side_2012", sources = [URL(url) for url in urls] -# Model - vendor: gemini, model: gemini-2.0-flash-exp -> gemini/gemini-2.0-flash-exp -model = LiteModel(model_name="gemini/gemini-2.0-flash-exp") +# Model - vendor: gemini, model: gemini-2.0-flash -> gemini/gemini-2.0-flash +model = LiteModel(model_name="gemini/gemini-2.0-flash") # Ontology Auto-Detection ontology = Ontology.from_sources( @@ -143,7 +143,7 @@ See the [Step 1](#how-to-use) section to understand how to create Knowledge Grap ```python # Define the model -model = LiteModel(model_name="gemini/gemini-2.0-flash-exp") +model = LiteModel(model_name="gemini/gemini-2.0-flash") # Create the Knowledge Graph from the predefined ontology. # In this example, we will use the restaurants agent and the attractions agent. From 21859d8e9b0f33e2d5ff82f297a1c53f8706ba24 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 25 Feb 2025 18:24:17 +0200 Subject: [PATCH 018/136] standardize-project --- graphrag_sdk/agents/agent.py | 2 - graphrag_sdk/agents/kg_agent.py | 34 ++-- graphrag_sdk/attribute.py | 18 +- graphrag_sdk/chat_session.py | 12 +- graphrag_sdk/document_loaders/html.py | 2 +- graphrag_sdk/document_loaders/pdf.py | 2 +- graphrag_sdk/document_loaders/string.py | 2 +- graphrag_sdk/document_loaders/text.py | 2 +- graphrag_sdk/document_loaders/url.py | 2 +- graphrag_sdk/entity.py | 17 +- graphrag_sdk/helpers.py | 100 +++++++-- graphrag_sdk/kg.py | 88 +++++--- graphrag_sdk/model_config.py | 2 +- graphrag_sdk/models/azure_openai.py | 72 +++---- graphrag_sdk/models/gemini.py | 126 ++++++++---- graphrag_sdk/models/litellm.py | 55 ++--- graphrag_sdk/models/model.py | 36 ++-- graphrag_sdk/models/ollama.py | 45 ++--- graphrag_sdk/models/openai.py | 125 ++++++++---- graphrag_sdk/ontology.py | 34 ++-- graphrag_sdk/orchestrator/execution_plan.py | 26 ++- graphrag_sdk/orchestrator/orchestrator.py | 74 +++++-- .../orchestrator/orchestrator_decision.py | 43 +++- .../orchestrator/orchestrator_runner.py | 189 ++++++++++++++++-- graphrag_sdk/orchestrator/step.py | 32 +++ graphrag_sdk/orchestrator/steps/agent.py | 96 ++++++++- graphrag_sdk/orchestrator/steps/parallel.py | 89 ++++++++- graphrag_sdk/orchestrator/steps/summary.py | 63 +++++- graphrag_sdk/orchestrator/steps/user_input.py | 86 +++++++- graphrag_sdk/relation.py | 25 ++- graphrag_sdk/source.py | 7 +- graphrag_sdk/steps/Step.py | 2 +- graphrag_sdk/steps/create_ontology_step.py | 95 +++++++-- graphrag_sdk/steps/extract_data_step.py | 101 ++++++++-- graphrag_sdk/steps/graph_query_step.py | 33 ++- graphrag_sdk/steps/qa_step.py | 28 ++- tests/test_kg_gemini.py | 6 +- 37 files changed, 1340 insertions(+), 431 deletions(-) diff --git a/graphrag_sdk/agents/agent.py b/graphrag_sdk/agents/agent.py index 54c95fa0..d896c08c 100644 --- a/graphrag_sdk/agents/agent.py +++ b/graphrag_sdk/agents/agent.py @@ -1,6 +1,4 @@ from abc import ABC, abstractmethod -from graphrag_sdk.models.model import GenerativeModelChatSession - class AgentResponseCode: """ diff --git a/graphrag_sdk/agents/kg_agent.py b/graphrag_sdk/agents/kg_agent.py index 908303ac..ee5d8bc4 100644 --- a/graphrag_sdk/agents/kg_agent.py +++ b/graphrag_sdk/agents/kg_agent.py @@ -1,6 +1,5 @@ -from graphrag_sdk.kg import KnowledgeGraph from .agent import Agent -from graphrag_sdk.models import GenerativeModelChatSession +from graphrag_sdk.kg import KnowledgeGraph class KGAgent(Agent): @@ -56,15 +55,12 @@ def agent_id(self) -> str: return self._agent_id @agent_id.setter - def agent_id(self, value): + def agent_id(self, value) -> None: """ Sets the agent ID. - Parameters: - value (str): The ID of the agent. - - Returns: - None + Args: + value (str): The ID of the agent. """ self._agent_id = value @@ -73,21 +69,18 @@ def introduction(self) -> str: """ Returns the introduction of the agent. - :return: The introduction of the agent. - :rtype: str + Returns: + str: The introduction of the agent. """ return self._introduction @introduction.setter - def introduction(self, value): + def introduction(self, value) -> None: """ Sets the introduction of the agent. - Parameters: - value (str): The introduction of the agent. - - Returns: - None + Args: + value (str): The introduction of the agent. """ self._introduction = value @@ -112,15 +105,12 @@ def kg(self) -> KnowledgeGraph: return self._kg @kg.setter - def kg(self, value: KnowledgeGraph): + def kg(self, value: KnowledgeGraph) -> None: """ Sets the knowledge graph for the agent. - Parameters: + Args: value (KnowledgeGraph): The knowledge graph to be set. - - Returns: - None """ self._kg = value @@ -138,7 +128,7 @@ def run(self, params: dict) -> str: output = self.chat_session.send_message(params["prompt"]) return output['response'] - def __repr__(self): + def __repr__(self) -> str: """ Returns a string representation of the KGAgent object. diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index 402a10f5..522706d0 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -1,11 +1,11 @@ import re import json import logging -from typing import Union +from typing import Union, Optional from graphrag_sdk.fixtures.regex import * -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) class AttributeType: """ @@ -35,7 +35,7 @@ class AttributeType: } @staticmethod - def from_string(txt: str): + def from_string(txt: str) -> "AttributeType": """ Converts a string representation of an attribute type to its corresponding AttributeType value. @@ -73,7 +73,7 @@ class Attribute: """ def __init__( - self, name: str, attr_type: AttributeType, unique: bool = False, required: bool = False + self, name: str, attr_type: AttributeType, unique: Optional[bool] = False, required: Optional[bool] = False ): """ Initialize a new Attribute object. @@ -81,8 +81,8 @@ def __init__( Args: name (str): The name of the attribute. attr_type (AttributeType): The type of the attribute. - unique (bool, optional): Indicates whether the attribute should be unique. Defaults to False. - required (bool, optional): Indicates whether the attribute is required. Defaults to False. + unique (Optional[bool]): Indicates whether the attribute should be unique. Defaults to False. + required (Optional[bool]): Indicates whether the attribute is required. Defaults to False. """ self.name = re.sub(r"([^a-zA-Z0-9_])", "_", name) self.type = attr_type @@ -90,7 +90,7 @@ def __init__( self.required = required @staticmethod - def from_json(txt: Union[str, dict]): + def from_json(txt: Union[str, dict]) -> "Attribute": """ Creates an Attribute object from a JSON string or dictionary. @@ -111,7 +111,7 @@ def from_json(txt: Union[str, dict]): ) @staticmethod - def from_string(txt: str): + def from_string(txt: str) -> "Attribute": """ Parses an attribute from a string. The "!" symbol indicates that the attribute is unique. @@ -138,7 +138,7 @@ def from_string(txt: str): return Attribute(name, AttributeType.from_string(attr_type), unique, required) - def to_json(self): + def to_json(self) -> dict: """ Converts the attribute object to a JSON representation. diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index a4cce9e4..c04dfbce 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -56,17 +56,15 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, self.qa_prompt = qa_prompt self.cypher_prompt_with_history = cypher_gen_prompt_history - self.cypher_chat_session = ( - model_config.cypher_generation.with_system_instruction( + self.cypher_chat_session = model_config.cypher_generation.start_chat( cypher_system_instruction - ).start_chat() - ) - self.qa_chat_session = model_config.qa.with_system_instruction( + ) + self.qa_chat_session = model_config.qa.start_chat( qa_system_instruction - ).start_chat() + ) self.last_answer = None - def send_message(self, message: str): + def send_message(self, message: str) -> str: """ Sends a message to the chat session. diff --git a/graphrag_sdk/document_loaders/html.py b/graphrag_sdk/document_loaders/html.py index 04ea4dc3..f7899eaa 100644 --- a/graphrag_sdk/document_loaders/html.py +++ b/graphrag_sdk/document_loaders/html.py @@ -14,7 +14,7 @@ def __init__(self, path: str) -> None: """ Initialize loader - Parameters: + Args: path (str): path to HTML. """ diff --git a/graphrag_sdk/document_loaders/pdf.py b/graphrag_sdk/document_loaders/pdf.py index 538b9eeb..c5000024 100644 --- a/graphrag_sdk/document_loaders/pdf.py +++ b/graphrag_sdk/document_loaders/pdf.py @@ -10,7 +10,7 @@ def __init__(self, path: str) -> None: """ Initialize loader - Parameters: + Args: path (str): path to PDF. """ diff --git a/graphrag_sdk/document_loaders/string.py b/graphrag_sdk/document_loaders/string.py index 166fb86a..e65753c9 100644 --- a/graphrag_sdk/document_loaders/string.py +++ b/graphrag_sdk/document_loaders/string.py @@ -10,7 +10,7 @@ def __init__(self, string: str) -> None: """ Initialize loader - Parameters: + Args: string (str): string from memory. """ self.string = string diff --git a/graphrag_sdk/document_loaders/text.py b/graphrag_sdk/document_loaders/text.py index 930a2202..79c3b26b 100644 --- a/graphrag_sdk/document_loaders/text.py +++ b/graphrag_sdk/document_loaders/text.py @@ -10,7 +10,7 @@ def __init__(self, path: str) -> None: """ Initialize loader - Parameters: + Args: path (str): path to Text. """ diff --git a/graphrag_sdk/document_loaders/url.py b/graphrag_sdk/document_loaders/url.py index 496ea5a5..5a39e107 100644 --- a/graphrag_sdk/document_loaders/url.py +++ b/graphrag_sdk/document_loaders/url.py @@ -13,7 +13,7 @@ def __init__(self, url: str) -> None: """ Initialize loader - Parameters: + Args: url (str): url. """ diff --git a/graphrag_sdk/entity.py b/graphrag_sdk/entity.py index 34cc533f..291ed063 100644 --- a/graphrag_sdk/entity.py +++ b/graphrag_sdk/entity.py @@ -1,15 +1,14 @@ +import re import json import logging from typing import Union from .attribute import Attribute from falkordb import Node as GraphNode -import re -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) descriptionKey = "__description__" - class Entity: """ Represents an entity in the knowledge graph. @@ -42,7 +41,7 @@ def __init__(self, label: str, attributes: list[Attribute], description: str = " self.description = description @staticmethod - def from_graph(entity: GraphNode): + def from_graph(entity: GraphNode) -> "Entity": """ Converts a GraphNode object to an Entity object. @@ -65,12 +64,12 @@ def from_graph(entity: GraphNode): ) @staticmethod - def from_json(txt: Union[dict, str]): + def from_json(txt: Union[dict, str]) -> "Entity": """ Create an Entity object from a JSON representation. Args: - txt Union[dict, str]: The JSON representation of the Entity. It can be either a dictionary or a string. + txt (Union[dict, str]): The JSON representation of the Entity. It can be either a dictionary or a string. Returns: Entity: The Entity object created from the JSON representation. @@ -100,7 +99,7 @@ def to_json(self) -> dict: "description": self.description, } - def merge(self, entity2: "Entity"): + def merge(self, entity2: "Entity") -> "Entity": """Overwrite attributes of self with attributes of entity2. Args: @@ -122,7 +121,7 @@ def merge(self, entity2: "Entity"): return self - def get_unique_attributes(self): + def get_unique_attributes(self) -> list[Attribute]: """ Returns a list of unique attributes for the entity. @@ -131,7 +130,7 @@ def get_unique_attributes(self): """ return [attr for attr in self.attributes if attr.unique] - def to_graph_query(self): + def to_graph_query(self) -> str: """ Generates a Cypher query string for creating or updating a node in a graph database. diff --git a/graphrag_sdk/helpers.py b/graphrag_sdk/helpers.py index 9794954f..9e1d982b 100644 --- a/graphrag_sdk/helpers.py +++ b/graphrag_sdk/helpers.py @@ -1,13 +1,23 @@ import re import logging -import graphrag_sdk -from typing import Union +from graphrag_sdk import Ontology +from typing import Union, Optional from fix_busted_json import repair_json -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) def extract_json(text: Union[str, dict], skip_repair=False) -> str: + """ + Extracts JSON from a string or dictionary, optionally skipping JSON repair. + + Args: + text (Union[str, dict]): The input text or dictionary. + skip_repair (bool): Flag to skip JSON repair. Defaults to False. + + Returns: + str: The extracted JSON as a string. + """ if not isinstance(text, str): text = str(text) regex = r"(?:```)?(?:json)?([^`]*)(?:\\n)?(?:```)?" @@ -20,7 +30,16 @@ def extract_json(text: Union[str, dict], skip_repair=False) -> str: return "".join(matches) -def map_dict_to_cypher_properties(d: dict): +def map_dict_to_cypher_properties(d: dict) -> str: + """ + Maps a dictionary to Cypher query properties. + + Args: + d (dict): The dictionary to map. + + Returns: + str: A Cypher-formatted string of properties. + """ cypher = "{" if isinstance(d, list): if len(d) == 0: @@ -50,7 +69,16 @@ def map_dict_to_cypher_properties(d: dict): return cypher -def stringify_falkordb_response(response): +def stringify_falkordb_response(response: Union[list, str]) -> str: + """ + Converts FalkorDB response to a string. + + Args: + response (Union[list, str]): The response to stringify. + + Returns: + str: The stringified response. + """ if not isinstance(response, list) or len(response) == 0: data = str(response).strip() elif not isinstance(response[0], list): @@ -67,7 +95,16 @@ def stringify_falkordb_response(response): return data -def extract_cypher(text: str): +def extract_cypher(text: str) -> str: + """ + Extracts Cypher query from a text block. + + Args: + text (str): The text containing a Cypher query. + + Returns: + str: The extracted Cypher query. + """ if not text.startswith("```"): return text @@ -79,8 +116,16 @@ def extract_cypher(text: str): def validate_cypher( - cypher: str, ontology: graphrag_sdk.Ontology -) -> Union[list[str], None]: + cypher: str, ontology: Ontology +) -> Optional[list[str]]: + """ + Validates a Cypher query against the ontology. + Args: + cypher (str): The Cypher query. + ontology (Ontology): The ontology to validate against. + Returns: + Optional[list[str]]: A list of validation errors, or None if valid. + """ try: if not cypher or len(cypher) == 0: return ["Cypher statement is empty"] @@ -105,7 +150,17 @@ def validate_cypher( return None -def validate_cypher_entities_exist(cypher: str, ontology: graphrag_sdk.Ontology): +def validate_cypher_entities_exist(cypher: str, ontology: Ontology) -> list[str]: + """ + Validates whether entities in the Cypher query exist in the ontology. + + Args: + cypher (str): The Cypher query. + ontology (Ontology): The ontology to validate against. + + Returns: + list[str]: A list of errors if entities are not found. + """ # Check if entities exist in ontology not_found_entity_labels = [] entity_labels = re.findall(r"\(:(.*?)\)", cypher) @@ -120,7 +175,17 @@ def validate_cypher_entities_exist(cypher: str, ontology: graphrag_sdk.Ontology) ] -def validate_cypher_relations_exist(cypher: str, ontology: graphrag_sdk.Ontology): +def validate_cypher_relations_exist(cypher: str, ontology: Ontology) -> list[str]: + """ + Validates whether relations in the Cypher query exist in the ontology. + + Args: + cypher (str): The Cypher query. + ontology (Ontology): The ontology to validate against. + + Returns: + list[str]: A list of errors if relations are not found. + """ # Check if relations exist in ontology not_found_relation_labels = [] relation_labels = re.findall(r"\[:(.*?)\]", cypher) @@ -141,9 +206,18 @@ def validate_cypher_relations_exist(cypher: str, ontology: graphrag_sdk.Ontology def validate_cypher_relation_directions( - cypher: str, ontology: graphrag_sdk.Ontology -): - + cypher: str, ontology: Ontology +) -> list[str]: + """ + Validates relation directions in a Cypher query. + + Args: + cypher (str): The Cypher query. + ontology (Ontology): The ontology to validate against. + + Returns: + list[str]: A list of errors if relation directions are incorrect. + """ errors = [] relations = list(re.finditer(r"\[.*?\]", cypher)) i = 0 diff --git a/graphrag_sdk/kg.py b/graphrag_sdk/kg.py index 4f966265..752bbeb6 100644 --- a/graphrag_sdk/kg.py +++ b/graphrag_sdk/kg.py @@ -12,10 +12,10 @@ from graphrag_sdk.fixtures.prompts import (GRAPH_QA_SYSTEM, CYPHER_GEN_SYSTEM, CYPHER_GEN_PROMPT, GRAPH_QA_PROMPT, CYPHER_GEN_PROMPT_WITH_HISTORY) + logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) - class KnowledgeGraph: """Knowledge Graph model data as a network of entities and relations To create one it is best to provide a ontology which will define the graph's ontology @@ -40,19 +40,19 @@ def __init__( """ Initialize Knowledge Graph - Parameters: + Args: name (str): Knowledge graph name. model (GenerativeModel): The Google GenerativeModel to use. host (str): FalkorDB hostname. port (int): FalkorDB port number. - username (Union[str, None]): FalkorDB username. - password (Union[str, None]): FalkorDB password. - ontology (Union[Ontology, None]): Ontology to use. - cypher_system_instruction (Union[str, None]): Cypher system instruction. Make sure you have {ontology} in the instruction. - qa_system_instruction (Union[str, None]): QA system instruction. - cypher_gen_prompt (Union[str, None]): Cypher generation prompt. Make sure you have {question} in the prompt. - qa_prompt (Union[str, None]): QA prompt. Make sure you have {question}, {context} and {cypher} in the prompt. - cypher_gen_prompt_history (Union[str, None]): Cypher generation prompt with history. Make sure you have {question} and {last_answer} in the prompt. + username (Optional[str]): FalkorDB username. + password (Optional[str]): FalkorDB password. + ontology (Optional[str]): Ontology to use. + cypher_system_instruction (Optional[str]): Cypher system instruction. Make sure you have {ontology} in the instruction. + qa_system_instruction (Optional[str]): QA system instruction. + cypher_gen_prompt (Optional[str]): Cypher generation prompt. Make sure you have {question} in the prompt. + qa_prompt (Optional[str]): QA prompt. Make sure you have {question}, {context} and {cypher} in the prompt. + cypher_gen_prompt_history (Optional[str]): Cypher generation prompt with history. Make sure you have {question} and {last_answer} in the prompt. """ if not isinstance(name, str) or name == "": @@ -146,15 +146,15 @@ def list_sources(self) -> list[AbstractSource]: return [s.source for s in self.sources] def process_sources( - self, sources: list[AbstractSource], instructions: str = None, hide_progress: bool = False + self, sources: list[AbstractSource], instructions: Optional[str] = None, hide_progress: Optional[bool] = False ) -> None: """ Add entities and relations found in sources into the knowledge-graph - Parameters: + Args: sources (list[AbstractSource]): list of sources to extract knowledge from - instructions (str): instructions to use for extraction - hide_progress (bool): hide progress bar + instructions (Optional[str]): Instructions for processing. + hide_progress (Optional[bool]): hide progress bar """ if self.ontology is None: @@ -165,9 +165,15 @@ def process_sources( def _create_graph_with_sources( - self, sources: Union[list[AbstractSource], None] = None, instructions: str = None, hide_progress: bool = False -) -> None: - + self, sources: Optional[list[AbstractSource]] = None, instructions: Optional[str] = None, hide_progress: Optional[bool] = False + ) -> None: + """ + Create a graph using the provided sources. + + Args: + sources (Optional[list[AbstractSource]]): List of sources. + instructions (Optional[str]): Instructions for the graph creation. + """ step = ExtractDataStep( sources=list(sources), ontology=self.ontology, @@ -195,14 +201,20 @@ def delete(self) -> None: setattr(self, key, None) def chat_session(self) -> ChatSession: + """ + Create a new chat session. + + Returns: + ChatSession: A new chat session instance. + """ chat_session = ChatSession(self._model_config, self.ontology, self.graph, self.cypher_system_instruction, self.qa_system_instruction, self.cypher_gen_prompt, self.qa_prompt, self.cypher_gen_prompt_history) return chat_session - def add_node(self, entity: str, attributes: dict): + def add_node(self, entity: str, attributes: dict) -> None: """ Add a node to the knowledge graph, checking if it matches the ontology - Parameters: + Args: label (str): label of the node attributes (dict): node attributes """ @@ -219,20 +231,20 @@ def add_edge( relation: str, source: str, target: str, - source_attr: dict = None, - target_attr: dict = None, - attributes: dict = None, - ): + source_attr: Optional[dict] = None, + target_attr: Optional[dict] = None, + attributes: Optional[dict] = None, + ) -> None: """ Add an edge to the knowledge graph, checking if it matches the ontology - Parameters: + Args: relation (str): relation label source (str): source entity label target (str): target entity label - source_attr (dict): source entity attributes - target_attr (dict): target entity attributes - attributes (dict): relation attributes + source_attr (Optional[dict]): Source entity attributes. + target_attr (Optional[dict]): Target entity attributes. + attributes (Optional[dict]): Relation attributes. """ source_attr = source_attr or {} @@ -248,7 +260,14 @@ def add_edge( f"MATCH (s:{source} {map_dict_to_cypher_properties(source_attr)}) MATCH (t:{target} {map_dict_to_cypher_properties(target_attr)}) MERGE (s)-[r:{relation} {map_dict_to_cypher_properties(attributes)}]->(t)" ) - def _validate_entity(self, entity: str, attributes: str): + def _validate_entity(self, entity: str, attributes: str) -> None: + """ + Validate if the entity exists in the ontology and check its attributes. + + Args: + entity (str): Entity label. + attributes (dict): Entity attributes. + """ ontology_entity = self.ontology.get_entity_with_label(entity) if ontology_entity is None: @@ -264,7 +283,18 @@ def _validate_relation( source_attr: dict, target_attr: dict, attributes: dict, - ): + ) -> None: + """ + Validate if the relation exists in the ontology and check its attributes. + + Args: + relation (str): Relation label. + source (str): Source entity label. + target (str): Target entity label. + source_attr (dict): Source entity attributes. + target_attr (dict): Target entity attributes. + attributes (dict): Relation attributes. + """ ontology_relations = self.ontology.get_relations_with_label(relation) found_relation = [ diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index e1f0722a..2e2e5842 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -31,7 +31,7 @@ def __init__( self.qa = qa @staticmethod - def with_model(model: GenerativeModel): + def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ Creates a new KnowledgeGraphModelConfig instance with the given generative model. diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index 222e657f..253a3336 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -10,6 +10,7 @@ GenerativeModelChatSession, ) + class AzureOpenAiGenerativeModel(GenerativeModel): """ A generative model that interfaces with Azure's OpenAI API for chat completions. @@ -46,41 +47,17 @@ def __init__( ) - def _connect_to_model(self) -> None: - """ - Establish a connection to the Azure OpenAI model by initializing the AzureOpenAI client. - """ - self.client = AzureOpenAI(azure_endpoint=self.azure_endpoint, - api_version=self.api_version, - api_key=self.api_key, - ) - - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - """ - Set or update the system instruction and connect to the Azure OpenAI model. - - Args: - system_instruction (str): System instructions for the model. - - Returns: - GenerativeModel: The updated model instance. - """ - self.system_instruction = system_instruction - self._connect_to_model() - - return self - - def start_chat(self, args: Optional[dict] = None) -> GenerativeModelChatSession: + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ Start a new chat session. - + Args: - args (Optional[dict]): Additional arguments for the chat session. - + system_instruction (Optional[str]): Optional system instruction to guide the chat session. + Returns: GenerativeModelChatSession: A new instance of the chat session. """ - return AzureOpenAiChatSession(self, args) + return AzureOpenAiChatSession(self, system_instruction) def ask(self, message: str) -> GenerationResponse: """ @@ -170,19 +147,18 @@ class AzureOpenAiChatSession(GenerativeModelChatSession): _history = [] - def __init__(self, model: AzureOpenAiGenerativeModel, args: Optional[dict] = None): + def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. - + Args: model (AzureOpenAiGenerativeModel): The model instance for the session. - args (Optional[dict]): Additional arguments for customization. + system_instruction (Optional[str]): Optional system instruction. """ self._model = model - self._args = args - self._history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None + self._chat_history = ( + [{"role": "system", "content": system_instruction}] + if system_instruction is not None else [] ) @@ -197,21 +173,27 @@ def send_message(self, message: str, output_method: OutputMethod = OutputMethod. Returns: GenerationResponse: The generated response. """ - generation_config = self._get_generation_config(output_method) - prompt = [] - prompt.extend(self._history) - prompt.append({"role": "user", "content": message[:14385]}) + generation_config = self._adjust_generation_config(output_method) + self._chat_history.append({"role": "user", "content": message[:14385]}) response = self._model.client.chat.completions.create( model=self._model.model_name, - messages=prompt, + messages=self._chat_history, **generation_config ) - content = self._model._parse_generate_content_response(response) - self._history.append({"role": "user", "content": message}) - self._history.append({"role": "assistant", "content": content.text}) + content = self._model.parse_generate_content_response(response) + self._chat_history.append({"role": "assistant", "content": content.text}) return content - def _get_generation_config(self, output_method: OutputMethod): + def get_chat_history(self) -> list[dict]: + """ + Retrieve the conversation history for the current chat session. + + Returns: + list[dict]: The chat session's conversation history. + """ + return self._chat_history.copy() + + def _adjust_generation_config(self, output_method: OutputMethod): """ Adjust the generation configuration based on the output method. diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index fddbe77f..31e4c11c 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -1,6 +1,11 @@ import os -from typing import Union - +from typing import Optional +from google.generativeai import ( + GenerativeModel as GoogleGenerativeModel, + GenerationConfig as GoogleGenerationConfig, + configure, + protos, + types,) from .model import ( OutputMethod, GenerativeModel, @@ -10,33 +15,43 @@ GenerativeModelChatSession, ) -from google.generativeai import ( - GenerativeModel as GoogleGenerativeModel, - GenerationConfig as GoogleGenerationConfig, - configure, - protos, - types,) - class GeminiGenerativeModel(GenerativeModel): - + """ + A generative model that interfaces with GoogleAI API for chat completions. + """ + _model: GoogleGenerativeModel = None def __init__( self, model_name: str, - generation_config: Union[GoogleGenerationConfig, None] = None, - system_instruction: Union[str, None] = None, + generation_config: Optional[GoogleGenerationConfig] = None, + system_instruction: Optional[str] = None, ): + """ + Initialize the GoogleGenerativeModel with required parameters. + Args: + model_name (str): Name of the GoogleAI model. + generation_config (Optional[GoogleGenerationConfig]): Configuration settings for generation. + system_instruction (Optional[str]): System-level instruction for the model. + """ self._model_name = model_name self._generation_config = generation_config self._system_instruction = system_instruction configure(api_key=os.environ["GOOGLE_API_KEY"]) - - def _get_model(self) -> GoogleGenerativeModel: - if self._model is None: - self._model = GoogleGenerativeModel( + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: + """ + Start a new chat session. + + Args: + system_instruction (Optional[str]): Optional system instruction to guide the chat session. + + Returns: + GeminiChatSession: A new instance of the chat session. + """ + self._model = GoogleGenerativeModel( self._model_name, generation_config=( GoogleGenerationConfig( @@ -49,24 +64,21 @@ def _get_model(self) -> GoogleGenerativeModel: if self._generation_config is not None else None ), - system_instruction=self._system_instruction, + system_instruction=system_instruction, ) - - return self._model - - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - self._system_instruction = system_instruction - self._model = None - self._get_model() - - return self - - def start_chat(self, args: Union[dict, None] = None) -> GenerativeModelChatSession: - return GeminiChatSession(self, args) - + + return GeminiChatSession(self) + def parse_generate_content_response( self, response: types.generation_types.GenerateContentResponse ) -> GenerationResponse: + """ + Parse the model's response and extract content for the user. + Args: + response (any): The raw response from the model. + Returns: + GenerationResponse: Parsed response containing the generated text and finish reason. + """ return GenerationResponse( text=response.text, finish_reason=( @@ -82,6 +94,12 @@ def parse_generate_content_response( ) def to_json(self) -> dict: + """ + Serialize the model's configuration and state to JSON format. + + Returns: + dict: The serialized JSON data. + """ return { "model_name": self._model_name, "generation_config": self._generation_config.to_json(), @@ -90,6 +108,13 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "GenerativeModel": + """ + Deserialize a JSON object to create an instance of GeminiGenerativeModel. + Args: + json (dict): The serialized JSON data. + Returns: + GenerativeModel: A new instance of the model. + """ return GeminiGenerativeModel( model_name=json["model_name"], generation_config=GenerativeModelConfig.from_json( @@ -100,19 +125,46 @@ def from_json(json: dict) -> "GenerativeModel": class GeminiChatSession(GenerativeModelChatSession): - - def __init__(self, model: GeminiGenerativeModel, args: Union[dict, None] = None): + """ + A chat session for interacting with the GoogleAI model, maintaining conversation history. + """ + + def __init__(self, model: GeminiGenerativeModel): + """ + Initialize the chat session and set up the conversation history. + + Args: + model (GeminiGenerativeModel): The model instance for the session. + """ + self._model = model - self._chat_session = self._model._model.start_chat( - history=args.get("history", []) if args is not None else [], - ) + self._chat_session = self._model._model.start_chat() def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: - generation_config = self._get_generation_config(output_method) + """ + Send a message in the chat session and receive the model's response. + + Args: + message (str): The message to send. + output_method (OutputMethod): Format for the model's output. + + Returns: + GenerationResponse: The generated response. + """ + generation_config = self._adjust_generation_config(output_method) response = self._chat_session.send_message(message, generation_config=generation_config) return self._model.parse_generate_content_response(response) - def _get_generation_config(self, output_method: OutputMethod): + def _adjust_generation_config(self, output_method: OutputMethod) -> dict: + """ + Adjust the generation configuration based on the output method. + + Args: + output_method (OutputMethod): The desired output method (e.g., default or JSON). + + Returns: + dict: The configuration settings for generation. + """ if output_method == OutputMethod.JSON: return { "response_mime_type": "application/json", diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 288e6a1d..723f78fb 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -41,7 +41,6 @@ def __init__( system_instruction (Optional[str]): Instruction to guide the model. """ - env_val = validate_environment(model_name) if not env_val['keys_in_environment']: raise ValueError(f"Missing {env_val['missing_keys']} in the environment.") @@ -104,30 +103,17 @@ def check_and_pull_model(self) -> None: logger.error(f"Failed to pull the model '{self.model_name}': {e}") raise ValueError(f"Failed to pull the model '{self.model_name}': {e}") - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - """ - Set or update the system instruction for new model instance. - - Args: - system_instruction (str): Instruction for guiding the model's behavior. - - Returns: - GenerativeModel: The updated model instance. - """ - self.system_instruction = system_instruction - return self - - def start_chat(self, args: Optional[dict] = None) -> GenerativeModelChatSession: + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ Start a new chat session. - + Args: - args (Optional[dict]): Additional arguments for the chat session. - + system_instruction (Optional[str]): Optional system instruction to guide the chat session. + Returns: GenerativeModelChatSession: A new instance of the chat session. """ - return LiteModelChatSession(self, args) + return LiteModelChatSession(self, system_instruction) def parse_generate_content_response(self, response: any) -> GenerationResponse: """ @@ -190,30 +176,20 @@ class LiteModelChatSession(GenerativeModelChatSession): A chat session for interacting with the LiteLLM model, maintaining conversation history. """ - def __init__(self, model: LiteModel, args: Optional[dict] = None): + def __init__(self, model: LiteModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. Args: - model (LiteLLMGenerativeModel): The model instance for the session. - args (Optional[dict]): Additional arguments for customization. + model (OllamaGenerativeModel): The model instance for the session. + system_instruction (Optional[str]): Optional system instruction """ self._model = model - self._args = args self._chat_history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None + [{"role": "system", "content": system_instruction}] + if system_instruction is not None else [] ) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._chat_history.copy() def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: """ @@ -256,7 +232,16 @@ def _adjust_generation_config(self, output_method: OutputMethod): config['response_format'] = { "type": "json_object" } return config - + + def get_chat_history(self) -> list[dict]: + """ + Retrieve the conversation history for the current chat session. + + Returns: + list[dict]: The chat session's conversation history. + """ + return self._chat_history.copy() + def delete_last_message(self): """ Deletes the last message exchange (user message and assistant response) from the chat history. diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index a41d4189..bef59438 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -1,5 +1,5 @@ from enum import Enum -from typing import Union +from typing import Optional from abc import ABC, abstractmethod @@ -15,15 +15,13 @@ class OutputMethod(Enum): class GenerativeModelConfig: """ Configuration for a generative model - Args: - temperature (float): The temperature to use for sampling. - top_p (float): The top-p value to use for sampling. - top_k (int): The top-k value to use for sampling. - max_output_tokens (int): The maximum number of tokens to generate. - stop_sequences (list[str]): The stop sequences to use for sampling. - response_format (dict): The format of the response. - + temperature (Optional[float]): The temperature to use for sampling. + top_p (Optional[float]): The top-p value to use for sampling. + top_k (Optional[int]): The top-k value to use for sampling. + max_output_tokens (Optional[int]): The maximum number of tokens to generate. + stop_sequences (Optional[list[str]]): The stop sequences to use for sampling. + response_format (Optional[dict]): The format of the response. Examples: >>> config = GenerativeModelConfig(temperature=0.5, top_p=0.9, top_k=50, max_output_tokens=100, stop_sequences=[".", "?", "!"]) @@ -31,12 +29,12 @@ class GenerativeModelConfig: def __init__( self, - temperature: Union[float, None] = None, - top_p: Union[float, None] = None, - top_k: Union[int, None] = None, - max_output_tokens: Union[int, None] = None, - stop_sequences: Union[list[str], None] = None, - response_format: Union[dict, None] = None, + temperature: Optional[float] = None, + top_p: Optional[float] = None, + top_k: Optional[int] = None, + max_output_tokens: Optional[int] = None, + stop_sequences: Optional[list[str]] = None, + response_format: Optional[dict] = None, ): self.temperature = temperature self.top_p = top_p @@ -100,13 +98,9 @@ class GenerativeModel(ABC): """ @abstractmethod - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - pass - - @abstractmethod - def start_chat(self, args: Union[dict, None]) -> GenerativeModelChatSession: + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: pass - + @staticmethod @abstractmethod def from_json(json: dict) -> "GenerativeModel": diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index b053067b..2d72ba0d 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -40,29 +40,13 @@ def __init__( self.generation_config = generation_config or GenerativeModelConfig() self.system_instruction = system_instruction self._host = host - - def _connect_to_client(self) -> None: - """ - Initializing the connection to the Ollama client. - """ - self.client = Client(host=self._host) - - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - """ - Set or update the system instruction and connect to the Ollama model. - - Args: - system_instruction (str): Instruction for guiding the model's behavior. - - Returns: - GenerativeModel: The updated model instance. - """ - self.system_instruction = system_instruction - self._connect_to_client() + try: + self.client = Client(host) + except Exception as e: + logger.error(f"Failed to initialize the Ollama client: {e}") + raise e self.check_and_pull_model() - return self - def check_and_pull_model(self) -> None: """ Checks if the specified model is available locally, and pulls it if not. @@ -89,19 +73,19 @@ def check_and_pull_model(self) -> None: except Exception as e: logger.error(f"Failed to pull the model '{self.model_name}': {e}") - def start_chat(self, args: Optional[dict] = None) -> GenerativeModelChatSession: + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ Start a new chat session. Args: - args (Optional[dict]): Additional arguments for the chat session. + system_instruction (Optional[str]): Optional system instruction to guide the chat session. Returns: GenerativeModelChatSession: A new instance of the chat session. """ - return OllamaChatSession(self, args) + return OllamaChatSession(self, system_instruction) - def _parse_generate_content_response(self, response: any) -> GenerationResponse: + def parse_generate_content_response(self, response: any) -> GenerationResponse: """ Parse the model's response and extract content for the user. @@ -153,19 +137,18 @@ class OllamaChatSession(GenerativeModelChatSession): A chat session for interacting with the Ollama model, maintaining conversation history. """ - def __init__(self, model: OllamaGenerativeModel, args: Optional[dict] = None): + def __init__(self, model: OllamaGenerativeModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. Args: model (OllamaGenerativeModel): The model instance for the session. - args (Optional[dict]): Additional arguments for customization. + system_instruction (Optional[str]): Optional system instruction """ self._model = model - self._args = args self._chat_history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None + [{"role": "system", "content": system_instruction}] + if system_instruction is not None else [] ) @@ -196,7 +179,7 @@ def send_message(self, message: str, output_method: OutputMethod = OutputMethod. messages=self._chat_history, options=Options(**generation_config) ) - content = self._model._parse_generate_content_response(response) + content = self._model.parse_generate_content_response(response) self._chat_history.append({"role": "assistant", "content": content.text}) return content diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index e630e3dc..d87ac600 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -1,3 +1,6 @@ +import os +from openai import OpenAI +from typing import Optional from .model import ( OutputMethod, GenerativeModel, @@ -6,39 +9,46 @@ FinishReason, GenerativeModelChatSession, ) -from typing import Union -from openai import OpenAI class OpenAiGenerativeModel(GenerativeModel): + """ + A generative model that interfaces with OpenAI's API for chat completions. + """ client: OpenAI = None def __init__( self, model_name: str, - generation_config: Union[GenerativeModelConfig, None] = None, - system_instruction: Union[str, None] = None, + generation_config: Optional[GenerativeModelConfig] = None, + system_instruction: Optional[str] = None, ): + """ + Initialize the OpenAiGenerativeModel with required parameters. + + Args: + model_name (str): Name of the OpenAI model. + generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. + system_instruction (Optional[str]): System-level instruction for the model. + """ self.model_name = model_name self.generation_config = generation_config or GenerativeModelConfig() self.system_instruction = system_instruction + if not os.getenv("OPENAI_API_KEY"): + raise ValueError("Missing OpenAI API key in the environment: OPENAI_API_KEY") + self.client = OpenAI() - def _get_model(self) -> OpenAI: - if self.client is None: - self.client = OpenAI() - - return self.client - - def with_system_instruction(self, system_instruction: str) -> "GenerativeModel": - self.system_instruction = system_instruction - self.client = None - self._get_model() - - return self - - def start_chat(self, args: Union[dict, None] = None) -> GenerativeModelChatSession: - return OpenAiChatSession(self, args) + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: + """ + Start a new chat session. + + Args: + system_instruction (Optional[str]): Optional system instruction to guide the chat session. + Returns: + GenerativeModelChatSession: A new instance of the chat session. + """ + return OpenAiChatSession(self, system_instruction) def parse_generate_content_response(self, response: any) -> GenerationResponse: return GenerationResponse( @@ -55,6 +65,13 @@ def parse_generate_content_response(self, response: any) -> GenerationResponse: ) def to_json(self) -> dict: + """ + Serialize the model's configuration and state to JSON format. + + Returns: + dict: The serialized JSON data. + """ + return { "model_name": self.model_name, "generation_config": self.generation_config.to_json(), @@ -63,6 +80,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "GenerativeModel": + """ + Deserialize a JSON object to create an instance of OpenAiGenerativeModel. + + Args: + json (dict): The serialized JSON data. + + Returns: + GenerativeModel: A new instance of the model. + """ return OpenAiGenerativeModel( json["model_name"], generation_config=GenerativeModelConfig.from_json( @@ -73,34 +99,63 @@ def from_json(json: dict) -> "GenerativeModel": class OpenAiChatSession(GenerativeModelChatSession): - - _history = [] - - def __init__(self, model: OpenAiGenerativeModel, args: Union[dict, None] = None): + """ + A chat session for interacting with the OpenAI model, maintaining conversation history. + """ + + def __init__(self, model: OpenAiGenerativeModel, system_instruction: Optional[str] = None) -> None: + """ + Initialize the chat session and set up the conversation history. + Args: + model (OpenAiGenerativeModel): The model instance for the session. + system_instruction (Optional[str]): Optional system instruction. + """ self._model = model - self._args = args - self._history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None + self._chat_history = ( + [{"role": "system", "content": system_instruction}] + if system_instruction is not None else [] ) def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: - generation_config = self._get_generation_config(output_method) - prompt = [] - prompt.extend(self._history) - prompt.append({"role": "user", "content": message[:14385]}) + """ + Send a message in the chat session and receive the model's response. + Args: + message (str): The message to send. + output_method (OutputMethod): Format for the model's output. + Returns: + GenerationResponse: The generated response. + """ + generation_config = self._adjust_generation_config(output_method) + self._chat_history.append({"role": "user", "content": message[:14385]}) response = self._model.client.chat.completions.create( model=self._model.model_name, - messages=prompt, + messages=self._chat_history, **generation_config ) content = self._model.parse_generate_content_response(response) - self._history.append({"role": "user", "content": message}) - self._history.append({"role": "assistant", "content": content.text}) + self._chat_history.append({"role": "assistant", "content": content.text}) return content - def _get_generation_config(self, output_method: OutputMethod): + def get_chat_history(self) -> list[dict]: + """ + Retrieve the conversation history for the current chat session. + + Returns: + list[dict]: The chat session's conversation history. + """ + return self._chat_history.copy() + + def _adjust_generation_config(self, output_method: OutputMethod): + """ + Adjust the generation configuration based on the output method. + + Args: + output_method (OutputMethod): The desired output method (e.g., default or JSON). + + Returns: + dict: The configuration settings for generation. + """ config = self._model.generation_config.to_json() if output_method == OutputMethod.JSON: config['temperature'] = 0 diff --git a/graphrag_sdk/ontology.py b/graphrag_sdk/ontology.py index f3b8fbbc..a771fe01 100644 --- a/graphrag_sdk/ontology.py +++ b/graphrag_sdk/ontology.py @@ -1,10 +1,10 @@ import json import logging import graphrag_sdk -from .entity import Entity from falkordb import Graph -from typing import Optional, Union +from .entity import Entity from .relation import Relation +from typing import Optional, Union from graphrag_sdk.source import AbstractSource from graphrag_sdk.models import GenerativeModel from .attribute import Attribute, AttributeType @@ -41,13 +41,13 @@ class Ontology(object): relations (list[Relation]): The list of relations in the ontology. """ - def __init__(self, entities: list[Entity] = None, relations: list[Relation] = None): + def __init__(self, entities: Optional[list[Entity]] = None, relations: Optional[list[Relation]] = None): """ Initialize the Ontology class. Args: - entities (list[Entity], optional): List of Entity objects. Defaults to None. - relations (list[Relation], optional): List of Relation objects. Defaults to None. + entities (Optional[list[Entity]]): List of Entity objects. Defaults to None. + relations (Optional[list[Relation]]): List of Relation objects. Defaults to None. """ self.entities = entities or [] self.relations = relations or [] @@ -81,7 +81,7 @@ def from_sources( return step.run(boundaries=boundaries) @staticmethod - def from_json(txt: Union[dict, str]): + def from_json(txt: Union[dict, str]) -> "Ontology": """ Creates an Ontology object from a JSON representation. @@ -101,7 +101,7 @@ def from_json(txt: Union[dict, str]): ) @staticmethod - def from_schema_graph(graph: Graph): + def from_schema_graph(graph: Graph) -> "Ontology": """ Creates an Ontology object from a given schema graph. @@ -125,7 +125,7 @@ def from_schema_graph(graph: Graph): return ontology @staticmethod - def from_kg_graph(graph: Graph, sample_size: int = 100,): + def from_kg_graph(graph: Graph, sample_size: Optional[int] = 100) -> "Ontology": """ Constructs an Ontology object from a given Knowledge Graph. @@ -135,7 +135,7 @@ def from_kg_graph(graph: Graph, sample_size: int = 100,): Args: graph (Graph): The graph object representing the knowledge graph. - sample_size (int): The sample size for the attribute extraction. + sample_size (Optional[int]): The maximum number of attributes to sample for each entity and relationship. Defaults to 100. Returns: Ontology: The Ontology object constructed from the Knowledge Graph. @@ -173,7 +173,7 @@ def from_kg_graph(graph: Graph, sample_size: int = 100,): return ontology - def add_entity(self, entity: Entity): + def add_entity(self, entity: Entity) -> None: """ Adds an entity to the ontology. @@ -182,7 +182,7 @@ def add_entity(self, entity: Entity): """ self.entities.append(entity) - def add_relation(self, relation: Relation): + def add_relation(self, relation: Relation) -> None: """ Adds a relation to the ontology. @@ -298,7 +298,7 @@ def discard_relations_without_entities(self): return self - def validate_entities(self): + def validate_entities(self) -> bool: """ Validates the entities in the ontology. @@ -324,7 +324,7 @@ def validate_entities(self): return False return True - def get_entity_with_label(self, label: str): + def get_entity_with_label(self, label: str) -> Optional[Entity]: """ Retrieves the entity with the specified label. @@ -336,7 +336,7 @@ def get_entity_with_label(self, label: str): """ return next((n for n in self.entities if n.label == label), None) - def get_relations_with_label(self, label: str): + def get_relations_with_label(self, label: str) -> list[Relation]: """ Returns a list of relations with the specified label. @@ -348,7 +348,7 @@ def get_relations_with_label(self, label: str): """ return [e for e in self.relations if e.label == label] - def has_entity_with_label(self, label: str): + def has_entity_with_label(self, label: str) -> bool: """ Checks if the ontology has an entity with the given label. @@ -360,7 +360,7 @@ def has_entity_with_label(self, label: str): """ return any(n.label == label for n in self.entities) - def has_relation_with_label(self, label: str): + def has_relation_with_label(self, label: str) -> bool: """ Checks if the ontology has a relation with the given label. @@ -386,7 +386,7 @@ def __str__(self) -> str: relations="\n- ".join([str(relation) for relation in self.relations]), ) - def save_to_graph(self, graph: Graph): + def save_to_graph(self, graph: Graph) -> None: """ Saves the entities and relations to the specified graph. diff --git a/graphrag_sdk/orchestrator/execution_plan.py b/graphrag_sdk/orchestrator/execution_plan.py index b624f079..69114122 100644 --- a/graphrag_sdk/orchestrator/execution_plan.py +++ b/graphrag_sdk/orchestrator/execution_plan.py @@ -1,22 +1,44 @@ from json import loads from typing import Union -from graphrag_sdk.orchestrator.step import PlanStep, StepBlockType +from graphrag_sdk.orchestrator.step import PlanStep class ExecutionPlan: - + """ + Represents an execution plan consisting of a sequence of steps. + """ + steps: list[PlanStep] = [] def __init__(self, steps: list[PlanStep]): + """ + Args: + steps (List[PlanStep]): The list of steps in the execution plan. + """ self.steps = steps @staticmethod def from_json(json: Union[str, dict]) -> "ExecutionPlan": + """ + Create an ExecutionPlan instance from a JSON dictionary or string. + + Args: + json (Union[str, dict]): The input JSON string or dictionary. + + Returns: + ExecutionPlan: An instance of ExecutionPlan. + """ if isinstance(json, str): json = loads(json) return ExecutionPlan([PlanStep.from_json(step) for step in json]) def to_json(self) -> dict: + """ + Convert the execution plan to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the execution plan. + """ return {"steps": [step.to_json() for step in self.steps]} def __str__(self) -> str: diff --git a/graphrag_sdk/orchestrator/orchestrator.py b/graphrag_sdk/orchestrator/orchestrator.py index 1db76cae..73bb4cd3 100644 --- a/graphrag_sdk/orchestrator/orchestrator.py +++ b/graphrag_sdk/orchestrator/orchestrator.py @@ -1,53 +1,97 @@ +import logging from graphrag_sdk.agents import Agent -from graphrag_sdk.models import GenerativeModel +from graphrag_sdk.helpers import extract_json +from graphrag_sdk.models import GenerativeModel, GenerativeModelChatSession +from .orchestrator_runner import OrchestratorRunner, OrchestratorResult from graphrag_sdk.models.model import OutputMethod -from .orchestrator_runner import OrchestratorRunner +from .execution_plan import ( + ExecutionPlan, +) from graphrag_sdk.fixtures.prompts import ( ORCHESTRATOR_SYSTEM, ORCHESTRATOR_EXECUTION_PLAN_PROMPT, ) -from graphrag_sdk.helpers import extract_json -from .execution_plan import ( - ExecutionPlan, -) -import logging -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) class Orchestrator: + """ + The Orchestrator class is responsible for managing agents and generating an execution plan + based on the user's input question. It interacts with a generative model to produce the plan + and assigns agents to execute tasks. + """ def __init__(self, model: GenerativeModel, backstory: str = ""): + """ + Initialize the Orchestrator with a generative model and an optional backstory. + Args: + model (GenerativeModel): The model that powers the orchestration process. + backstory (str): Optional backstory or context to be included in the orchestration system. + """ self._model = model self._backstory = backstory self._agents = [] self._chat = None - def _get_chat(self): + def _get_chat(self) -> GenerativeModelChatSession: + """ + Internal method to get or initialize a chat session with the model. + + Returns: + GenerativeModelChatSession: The chat session used for communication with the model. + """ if self._chat is None: - self._chat = self._model.with_system_instruction( + self._chat = self._model.start_chat( ORCHESTRATOR_SYSTEM.replace("#BACKSTORY", self._backstory).replace( "#AGENTS", - ",".join([str(agent) for agent in self._agents]), - ) - ).start_chat({"response_validation": False}) + ",".join([str(agent) for agent in self._agents])) + ) return self._chat def register_agent(self, agent: Agent): self._agents.append(agent) - def ask(self, question: str): + def ask(self, question: str) -> OrchestratorResult: + """ + Ask the orchestrator a question and run the corresponding execution plan. + Args: + question (str): The user's question. + Returns: + OrchestratorRunner: The result of executing the plan. + """ return self.runner(question).run() def runner(self, question: str) -> OrchestratorRunner: + """ + Create an OrchestratorRunner to execute the plan based on the user's question. + + Args: + question (str): The user's input question. + + Returns: + OrchestratorRunner: A runner that will handle the execution of the plan. + """ plan = self._create_execution_plan(question) return OrchestratorRunner( self._get_chat(), self._agents, plan, user_question=question ) - def _create_execution_plan(self, question: str): + def _create_execution_plan(self, question: str) -> ExecutionPlan: + """ + Generate an execution plan based on the user's question by interacting with the model. + + Args: + question (str): The question or prompt for which the execution plan is generated. + + Returns: + ExecutionPlan: The generated execution plan. + + Raises: + Exception: If the plan generation fails. + """ try: response = self._get_chat().send_message( ORCHESTRATOR_EXECUTION_PLAN_PROMPT.replace("#QUESTION", question) diff --git a/graphrag_sdk/orchestrator/orchestrator_decision.py b/graphrag_sdk/orchestrator/orchestrator_decision.py index 65b6adb2..552adc47 100644 --- a/graphrag_sdk/orchestrator/orchestrator_decision.py +++ b/graphrag_sdk/orchestrator/orchestrator_decision.py @@ -1,15 +1,28 @@ from json import loads -from typing import Union +from typing import Union, Optional from graphrag_sdk.orchestrator.step import PlanStep class OrchestratorDecisionCode: + CONTINUE = "continue" END = "end" UPDATE_STEP = "update_step" @staticmethod def from_str(code: str) -> str: + """ + Convert a string representation of a decision code to the corresponding constant. + + Args: + code (str): The string representation of a decision code. + + Returns: + str: The corresponding decision code. + + Raises: + ValueError: If the code is unknown. + """ if code == OrchestratorDecisionCode.CONTINUE: return OrchestratorDecisionCode.CONTINUE elif code == OrchestratorDecisionCode.END: @@ -21,13 +34,30 @@ def from_str(code: str) -> str: class OrchestratorDecision: + """ + Represents a decision made by the orchestrator. + """ + def __init__( - self, code: OrchestratorDecisionCode, new_step: Union[PlanStep, None] = None + self, code: OrchestratorDecisionCode, new_step: Optional[PlanStep] = None ): + """ + Initialize a new OrchestratorDecision object. + + Args: + code (OrchestratorDecisionCode): The decision code. + new_step (Optional[PlanStep]): The new step to execute, if applicable. + """ self.code = code self.new_step = new_step def to_json(self) -> dict: + """ + Convert the orchestrator decision to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the orchestrator decision. + """ return { "code": self.code, "new_step": self.new_step.to_json() if self.new_step else None, @@ -35,6 +65,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: Union[dict, str]) -> "OrchestratorDecision": + """ + Create an OrchestratorDecision instance from a JSON dictionary or string. + + Args: + json (Union[dict, str]): The input dictionary or string containing decision data. + + Returns: + OrchestratorDecision: An instance of OrchestratorDecision. + """ json = json if isinstance(json, dict) else loads(json) return OrchestratorDecision( OrchestratorDecisionCode.from_str(json["code"]), diff --git a/graphrag_sdk/orchestrator/orchestrator_runner.py b/graphrag_sdk/orchestrator/orchestrator_runner.py index 2b97b8c9..a424603d 100644 --- a/graphrag_sdk/orchestrator/orchestrator_runner.py +++ b/graphrag_sdk/orchestrator/orchestrator_runner.py @@ -1,22 +1,37 @@ -from typing import Union +import logging +from typing import Optional from graphrag_sdk.agents import Agent -from graphrag_sdk.models import GenerativeModelChatSession from .execution_plan import ExecutionPlan +from graphrag_sdk.helpers import extract_json from .step import StepResult, PlanStep, StepBlockType -from .orchestrator_decision import OrchestratorDecision, OrchestratorDecisionCode +from graphrag_sdk.models import GenerativeModelChatSession from graphrag_sdk.fixtures.prompts import ORCHESTRATOR_DECISION_PROMPT -from graphrag_sdk.helpers import extract_json -import logging +from .orchestrator_decision import OrchestratorDecision, OrchestratorDecisionCode -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) class OrchestratorResult(StepResult): + """ + Represents the result of an orchestrator execution step. + """ def __init__(self, output: str): + """ + Initialize a new OrchestratorResult object. + + Args: + _output (str): The output generated by the orchestrator. + """ self._output = output def to_json(self) -> dict: + """ + Convert the orchestrator result to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the orchestrator result. + """ return { "output": self._output, } @@ -35,10 +50,20 @@ def __repr__(self) -> str: @property def output(self) -> str: + """ + Get the output of the orchestrator result. + + Returns: + str: The output generated by the orchestrator. + """ return self._output class OrchestratorRunner: + """ + Manages the execution of an orchestrator plan, coordinating the involved agents. + """ + _runner_log: list[tuple[PlanStep, StepResult]] = [] _agent_sessions: dict[str, GenerativeModelChatSession] = {} @@ -47,9 +72,19 @@ def __init__( chat: GenerativeModelChatSession, agents: list[Agent], plan: ExecutionPlan, - user_question: str = "", - config: dict = None, + user_question: Optional[str] = None, + config: Optional[dict] = None, ): + """ + Initialize a new OrchestratorRunner object. + + Args: + chat (GenerativeModelChatSession): The chat session used for communication with the model. + agents (list[Agent]): List of registered agents for executing tasks. + plan (ExecutionPlan): The execution plan that dictates the steps to be executed. + user_question (str): The user's original question. + config (dict): Configuration settings for the orchestrator. + """ self._chat = chat self._agents = agents self._plan = plan @@ -60,38 +95,107 @@ def __init__( @property def plan(self) -> ExecutionPlan: + """ + Get the execution plan. + + Returns: + ExecutionPlan: The current execution plan. + """ return self._plan @property def chat(self) -> GenerativeModelChatSession: + """ + Get the chat session. + + Returns: + GenerativeModelChatSession: The current chat session. + """ return self._chat @property def runner_log(self) -> list[tuple[PlanStep, StepResult]]: + """ + Get the log of executed steps and their results. + + Returns: + list[tuple[PlanStep, StepResult]]: The log of steps executed. + """ return self._runner_log @property def user_question(self) -> str: + """ + Get the user's original question. + + Returns: + str: The user's question. + """ return self._user_question def get_agent(self, agent_id: str) -> Agent: + """ + Retrieve an agent by its ID. + + Args: + agent_id (str): The ID of the agent to retrieve. + + Returns: + Agent: The agent corresponding to the provided ID. + """ return next(agent for agent in self._agents if agent.agent_id == agent_id) - def get_session(self, session_id: str) -> Union[GenerativeModelChatSession, None]: + def get_session(self, session_id: str) -> Optional[GenerativeModelChatSession]: + """ + Retrieve the chat session for a specific agent. + + Args: + session_id (str): The ID of the session to retrieve. + + Returns: + Optional[GenerativeModelChatSession]: The corresponding session or None if not found. + """ return self._agent_sessions.get(session_id, None) def set_session(self, session_id: str, session: GenerativeModelChatSession): + """ + Set the chat session for a specific agent. + + Args: + session_id (str): The ID of the session to set. + session (GenerativeModelChatSession): The session to associate with the agent. + """ + self._agent_sessions[session_id] = session def get_user_input(self, question: str) -> str: + """ + Get user input based on a prompt. + + Args: + question (str): The prompt to display to the user. + + Returns: + str: The user's input. + """ + return input(question) def run(self) -> OrchestratorResult: + """ + Execute the orchestrator plan and return the result. + + Returns: + OrchestratorResult: The result of the orchestrator execution. + + Raises: + ValueError: If the execution plan is empty. + """ - first_step = self._plan.steps[0] if len(self._plan.steps) > 0 else None + if not self._plan.steps: + raise ValueError("Execution plan contains no steps to execute.") - if first_step is None: - return OrchestratorResult("No steps to run") + first_step = self._plan.steps[0] first_step_result = first_step.run(self) @@ -105,23 +209,39 @@ def run(self) -> OrchestratorResult: return loop_response def _run_loop(self, steps: list[PlanStep]) -> StepResult: + """ + Run a loop through the steps of the execution plan and handle decisions. + + Args: + steps (list[PlanStep]): The remaining steps to execute. + + Returns: + StepResult: The result of the execution. + """ decision = self._get_orchestrator_decision( steps[0] if len(steps) > 0 else None, ) if decision.code == OrchestratorDecisionCode.END: return self._handle_end_decision() - - if decision.code == OrchestratorDecisionCode.CONTINUE: + elif decision.code == OrchestratorDecisionCode.CONTINUE: return self._handle_continue_decision(steps) - - if decision.code == OrchestratorDecisionCode.UPDATE_STEP: + elif decision.code == OrchestratorDecisionCode.UPDATE_STEP: return self._handle_update_step_decision(decision.new_step) + else: + raise ValueError(f"Unhandled OrchestratorDecisionCode: {decision.code}") def _handle_end_decision(self) -> StepResult: + """ + Handle the decision to end the orchestration. + + Returns: + StepResult: The result of the orchestration upon ending. + """ last_step = self._runner_log[-1][0] if len(self._runner_log) > 0 else None if last_step is None: - return OrchestratorResult("No steps to run") + return OrchestratorResult("Execution plan contains no steps to execute.") + if last_step.block != StepBlockType.SUMMARY: return self._call_summary_step() last_result = self._runner_log[-1][1] if len(self._runner_log) > 0 else None @@ -133,6 +253,15 @@ def _handle_end_decision(self) -> StepResult: ) def _handle_continue_decision(self, steps: list[PlanStep]) -> StepResult: + """ + Handle the decision to continue with the next step in the execution. + + Args: + steps (list[PlanStep]): The remaining steps to execute. + + Returns: + StepResult: The result of the next step execution. + """ if len(steps) == 0: return self._handle_end_decision() @@ -142,11 +271,26 @@ def _handle_continue_decision(self, steps: list[PlanStep]) -> StepResult: return self._run_loop(steps[1:]) def _handle_update_step_decision(self, new_step: PlanStep) -> StepResult: + """ + Handle the decision to update the current step. + + Args: + new_step (PlanStep): The new step to execute. + + Returns: + StepResult: The result of the new step execution. + """ next_step_result = new_step.run(self) self._runner_log.append((new_step, next_step_result)) return self._run_loop([]) def _call_summary_step(self): + """ + Call the summary step at the end of the orchestration. + + Returns: + StepResult: The result of the summary step execution. + """ return self._run_loop( [ PlanStep.from_json( @@ -161,8 +305,17 @@ def _call_summary_step(self): def _get_orchestrator_decision( self, - next_step: Union[PlanStep, None] = None, + next_step: Optional[PlanStep] = None, ) -> OrchestratorDecision: + """ + Get the orchestrator's decision based on the current step and context. + + Args: + next_step (Optional[PlanStep]): The next step to evaluate for decision making. + + Returns: + OrchestratorDecision: The decision made by the orchestrator. + """ response = self.chat.send_message( ORCHESTRATOR_DECISION_PROMPT.replace( diff --git a/graphrag_sdk/orchestrator/step.py b/graphrag_sdk/orchestrator/step.py index 5396049a..6c1ce11a 100644 --- a/graphrag_sdk/orchestrator/step.py +++ b/graphrag_sdk/orchestrator/step.py @@ -3,7 +3,11 @@ from .step_result import StepResult from abc import ABC, abstractmethod + class StepBlockType: + """ + Enum representing different types of step blocks in a plan. + """ PARALLEL = "parallel" AGENT = "agent" SUMMARY = "summary" @@ -11,6 +15,18 @@ class StepBlockType: @staticmethod def from_str(text: str) -> "StepBlockType": + """ + Convert a string to a corresponding StepBlockType enum value. + + Args: + text (str): The string representation of the step block type. + + Returns: + StepBlockType: The corresponding block type. + + Raises: + ValueError: If the input string does not match any known step block type. + """ if text == StepBlockType.PARALLEL: return StepBlockType.PARALLEL elif text == StepBlockType.AGENT: @@ -24,6 +40,10 @@ def from_str(text: str) -> "StepBlockType": class PlanStep(ABC): + """ + Abstract base class for a PlanStep, which defines a step in the execution plan. + Each subclass must implement the following properties and methods. + """ @property @abstractmethod @@ -42,6 +62,18 @@ def properties(self) -> any: @staticmethod def from_json(json: Union[dict, str]) -> "PlanStep": + """ + Factory method to create a PlanStep instance from a JSON object or string. + + Args: + json (Union[dict, str]): The JSON representation of the step. + + Returns: + PlanStep: The corresponding step instance. + + Raises: + ValueError: If the block type is unknown or if step_type is None. + """ json = json if isinstance(json, dict) else loads(json) from graphrag_sdk.orchestrator.steps import PLAN_STEP_TYPE_MAP block = StepBlockType.from_str(json["block"]) diff --git a/graphrag_sdk/orchestrator/steps/agent.py b/graphrag_sdk/orchestrator/steps/agent.py index 65172a05..b320fb46 100644 --- a/graphrag_sdk/orchestrator/steps/agent.py +++ b/graphrag_sdk/orchestrator/steps/agent.py @@ -1,19 +1,36 @@ +import logging +from typing import Optional from graphrag_sdk.agents.agent import AgentResponseCode from graphrag_sdk.orchestrator.step_result import StepResult from graphrag_sdk.orchestrator.step import PlanStep, StepBlockType from graphrag_sdk.orchestrator.orchestrator_runner import OrchestratorRunner -import logging -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) class AgentStepResult(StepResult): - + """ + Represents the result of executing an agent step. + """ + def __init__(self, response_code: AgentResponseCode, payload: dict): + """ + Initializes a new AgentStepResult object. + + Args: + response_code (AgentResponseCode): The response code from the agent. + payload (dict): The payload containing the result data. + """ self.response_code = response_code self.payload = payload def to_json(self) -> dict: + """ + Convert the agent step result to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the agent step result. + """ return { "response_code": self.response_code, "payload": self.payload, @@ -21,6 +38,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "AgentStepResult": + """ + Create an AgentStepResult instance from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + AgentStepResult: An instance of AgentStepResult. + """ return AgentStepResult( AgentResponseCode.from_str(json["response_code"]), json["payload"], @@ -38,14 +64,34 @@ def output(self) -> str: class AgentProperties: - - def __init__(self, agent_id: str, session_id: str = None, payload: dict = None): + """ + Represents the properties for an agent step. + """ + + def __init__(self, agent_id: str, session_id: Optional[str] = None, payload: Optional[dict] = None): + """ + Represents the properties for an agent step. + + Args: + agent_id (str): The identifier for the agent. + session_id (Optional[str]): The session identifier. + payload (Optional[dict]): Additional payload data for the agent. + """ self.agent_id = agent_id self.session_id = session_id self.payload = payload @staticmethod def from_json(json: dict) -> "AgentProperties": + """ + Create AgentProperties from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + AgentProperties: An instance of AgentProperties. + """ return AgentProperties( json["agent_id"], json.get("session_id", None), @@ -53,6 +99,12 @@ def from_json(json: dict) -> "AgentProperties": ) def to_json(self) -> dict: + """ + Convert the agent properties to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the agent properties. + """ return { "agent_id": self.agent_id, "session_id": self.session_id, @@ -67,8 +119,18 @@ def __repr__(self) -> str: class AgentStep(PlanStep): + """ + Represents a step that interacts with an agent. + """ def __init__(self, id: str, properties: AgentProperties): + """ + Initializes a new AgentStep object. + + Args: + id (str): The identifier for the step. + properties (AgentProperties): The properties of the agent step. + """ self._id = id self._properties = properties @@ -85,6 +147,12 @@ def properties(self) -> AgentProperties: return self._properties def to_json(self) -> dict: + """ + Convert the agent step to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the agent step. + """ return { "id": self.id, "block": self.block, @@ -93,6 +161,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "AgentStep": + """ + Create an AgentStep from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + AgentStep: An instance of AgentStep. + """ return AgentStep(json["id"], AgentProperties.from_json(json["properties"])) def __str__(self) -> str: @@ -105,6 +182,15 @@ def run( self, runner: "OrchestratorRunner", ) -> AgentStepResult: + """ + Run the agent step, executing the agent with the provided properties. + + Args: + runner (OrchestratorRunner): The orchestrator runner instance. + + Returns: + AgentStepResult: The result of the agent step execution. + """ logger.info(f"Running agent {self.properties.agent_id}, step: {self.id}, payload: {self.properties.payload}") agent = runner.get_agent(self.properties.agent_id) diff --git a/graphrag_sdk/orchestrator/steps/parallel.py b/graphrag_sdk/orchestrator/steps/parallel.py index 90a33620..24e6cac6 100644 --- a/graphrag_sdk/orchestrator/steps/parallel.py +++ b/graphrag_sdk/orchestrator/steps/parallel.py @@ -1,20 +1,47 @@ +from typing import Optional import graphrag_sdk.orchestrator.step +from graphrag_sdk.orchestrator.step import PlanStep from concurrent.futures import ThreadPoolExecutor, wait from graphrag_sdk.orchestrator.step_result import StepResult from graphrag_sdk.orchestrator.orchestrator_runner import OrchestratorRunner class ParallelStepResult(StepResult): + """ + Represents the result of executing parallel steps. + """ + results: list[StepResult] def __init__(self, results: list[StepResult]): + """ + Initializes a new ParallelStepResult object. + + Args: + results (list[StepResult]): The results of the parallel steps. + """ self.results = results def to_json(self) -> dict: + """ + Convert the parallel step result to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the parallel step result. + """ return {"results": [result.to_json() for result in self.results]} @staticmethod def from_json(json: dict) -> "ParallelStepResult": + """ + Create a ParallelStepResult instance from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + ParallelStepResult: An instance of ParallelStepResult. + """ return ParallelStepResult( [ StepResult.from_json(result) @@ -34,13 +61,32 @@ def output(self) -> str: class ParallelProperties: + """ + Represents properties for parallel execution of steps. + """ + steps: list["PlanStep"] def __init__(self, steps: list["PlanStep"]): + """ + Initializes a new ParallelProperties object. + + Args: + steps (list[PlanStep]): The list of steps to execute in parallel. + """ self.steps = steps @staticmethod def from_json(json: dict) -> "ParallelProperties": + """ + Create ParallelProperties from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + ParallelProperties: An instance of ParallelProperties. + """ return ParallelProperties( [ graphrag_sdk.orchestrator.step.PlanStep.from_json(step) @@ -49,6 +95,12 @@ def from_json(json: dict) -> "ParallelProperties": ) def to_json(self) -> dict: + """ + Convert the parallel properties to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the parallel properties. + """ return {"steps": [step.to_json() for step in self.steps]} def __str__(self) -> str: @@ -59,8 +111,18 @@ def __repr__(self) -> str: class ParallelStep(graphrag_sdk.orchestrator.step.PlanStep): + """ + Represents a step that executes multiple sub-steps in parallel. + """ def __init__(self, id: str, properties: ParallelProperties): + """ + Initializes a new ParallelStep object. + + Args: + id (str): The identifier for the step. + properties (ParallelProperties): The properties of the parallel step. + """ self._id = id self._properties = properties @@ -77,6 +139,12 @@ def properties(self) -> ParallelProperties: return self._properties def to_json(self) -> dict: + """ + Convert the parallel step to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the parallel step. + """ return { "id": self.id, "block": self.block, @@ -85,6 +153,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "ParallelStep": + """ + Create a ParallelStep from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + ParallelStep: An instance of ParallelStep. + """ return ParallelStep( json["id"], ParallelProperties.from_json(json["properties"]) ) @@ -96,8 +173,18 @@ def __repr__(self) -> str: return str(self) def run( - self, runner: OrchestratorRunner, config: dict = None + self, runner: OrchestratorRunner, config: Optional[dict] = None ) -> ParallelStepResult: + """ + Run the parallel step, executing sub-steps concurrently. + + Args: + runner (OrchestratorRunner): The orchestrator runner instance. + config (Optional[dict]): Configuration options. Defaults to None. + + Returns: + ParallelStepResult: The result of the parallel step execution. + """ config = config or {"parallel_max_workers": 16} tasks = [] with ThreadPoolExecutor( diff --git a/graphrag_sdk/orchestrator/steps/summary.py b/graphrag_sdk/orchestrator/steps/summary.py index edeb5475..c72b1a8c 100644 --- a/graphrag_sdk/orchestrator/steps/summary.py +++ b/graphrag_sdk/orchestrator/steps/summary.py @@ -1,26 +1,49 @@ +import logging import graphrag_sdk.orchestrator.step from graphrag_sdk.orchestrator.step_result import StepResult -from concurrent.futures import ThreadPoolExecutor, wait from graphrag_sdk.orchestrator.orchestrator_runner import OrchestratorRunner from graphrag_sdk.fixtures.prompts import ORCHESTRATOR_SUMMARY_PROMPT -import logging - logger = logging.getLogger(__name__) class SummaryResult(StepResult): + """ + Represents the result of a summary step. + """ def __init__(self, output: str): + """ + Initializes a new SummaryResult object. + + Args: + output (str): The summary output. + """ self._output = output def to_json(self) -> dict: + """ + Convert the summary result to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the summary result. + """ return { "output": self._output, } @staticmethod def from_json(json: dict) -> "SummaryResult": + """ + Create a SummaryResult instance from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + SummaryResult: An instance of SummaryResult. + """ + return SummaryResult( json["output"], ) @@ -37,8 +60,18 @@ def output(self) -> str: class SummaryStep(graphrag_sdk.orchestrator.step.PlanStep): + """ + Represents a step that generates a summary. + """ def __init__(self, id: str, properties: any): + """ + Initializes a new SummaryStep object. + + Args: + id (str): The identifier for the step. + properties (any): The properties of the summary step. + """ self._id = id self._properties = {} @@ -55,6 +88,12 @@ def properties(self) -> any: return self._properties def to_json(self) -> dict: + """ + Convert the summary step to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the summary step. + """ return { "id": self.id, "block": self.block, @@ -63,6 +102,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "SummaryStep": + """ + Create a SummaryStep from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + SummaryStep: An instance of SummaryStep. + """ return SummaryStep(json["id"], {}) def __str__(self) -> str: @@ -75,6 +123,15 @@ def run( self, runner: OrchestratorRunner, ) -> SummaryResult: + """ + Run the summary step, generating a summary based on execution logs. + + Args: + runner (OrchestratorRunner): The orchestrator runner instance. + + Returns: + SummaryResult: The result of the summary step. + """ response = runner.chat.send_message( ORCHESTRATOR_SUMMARY_PROMPT.replace( "#USER_QUESTION", str(runner.user_question) diff --git a/graphrag_sdk/orchestrator/steps/user_input.py b/graphrag_sdk/orchestrator/steps/user_input.py index b3c5c7da..5106b454 100644 --- a/graphrag_sdk/orchestrator/steps/user_input.py +++ b/graphrag_sdk/orchestrator/steps/user_input.py @@ -1,23 +1,47 @@ +import logging from graphrag_sdk.orchestrator.step import PlanStep, StepBlockType from graphrag_sdk.orchestrator.step_result import StepResult from graphrag_sdk.orchestrator.orchestrator_runner import OrchestratorRunner -import logging -logger = logging.getLogger(__name__) +logger = logging.getLogger(__name__) class UserInputResult(StepResult): + """ + Represents the result of a user input step. + """ def __init__(self, output: str): + """ + Initializes a new UserInputResult object. + + Args: + output (str): The user's input. + """ self._output = output def to_json(self) -> dict: + """ + Convert the user input result to a JSON-serializable dictionary. + + Returns: + Dict: A dictionary representation of the user input result. + """ return { "output": self._output, } @staticmethod def from_json(json: dict) -> "UserInputResult": + """ + Create a UserInputResult instance from a JSON dictionary. + + Args: + json (Dict): The input JSON dictionary. + + Returns: + UserInputResult: An instance of UserInputResult. + """ return UserInputResult( json["output"], ) @@ -34,17 +58,41 @@ def output(self) -> str: class UserInputProperties: + """ + Represents the properties required for a user input step. + """ def __init__(self, question: str): + """ + Initialize a new UserInputProperties object. + + Args: + question (str): The question to prompt the user. + """ self.question = question @staticmethod def from_json(json: dict) -> "UserInputProperties": + """ + Create UserInputProperties from a JSON dictionary. + + Args: + json (Dict): The input JSON dictionary. + + Returns: + UserInputProperties: An instance of UserInputProperties. + """ return UserInputProperties( json["question"], ) def to_json(self) -> dict: + """ + Convert the user input properties to a JSON-serializable dictionary. + + Returns: + Dict: A dictionary representation of the user input properties. + """ return { "question": self.question, } @@ -57,8 +105,18 @@ def __repr__(self) -> str: class UserInputStep(PlanStep): + """ + Represents a step that requires user input. + """ def __init__(self, id: str, properties: UserInputProperties): + """ + Initializes a new UserInputStep object. + + Args: + id (str): The identifier for the step. + properties (UserInputProperties): The properties of the user input step. + """ self._id = id self._properties = properties @@ -75,6 +133,12 @@ def properties(self) -> UserInputProperties: return self._properties def to_json(self) -> dict: + """ + Convert the user input step to a JSON-serializable dictionary. + + Returns: + dict: A dictionary representation of the user input step. + """ return { "id": self.id, "block": self.block, @@ -83,6 +147,15 @@ def to_json(self) -> dict: @staticmethod def from_json(json: dict) -> "UserInputStep": + """ + Create a UserInputStep from a JSON dictionary. + + Args: + json (dict): The input JSON dictionary. + + Returns: + UserInputStep: An instance of UserInputStep. + """ return UserInputStep( json["id"], UserInputProperties.from_json(json["properties"]) ) @@ -97,5 +170,14 @@ def run( self, runner: OrchestratorRunner, ) -> UserInputResult: + """ + Run the user input step, prompting the user for input. + + Args: + runner (OrchestratorRunner): The orchestrator runner instance. + + Returns: + UserInputResult: The result of the user input step. + """ logger.info(f"Running user input step: {self.id}") return UserInputResult(runner.get_user_input(self.properties.question)) diff --git a/graphrag_sdk/relation.py b/graphrag_sdk/relation.py index e39c3cc8..f8bd0ff8 100644 --- a/graphrag_sdk/relation.py +++ b/graphrag_sdk/relation.py @@ -1,8 +1,8 @@ -import json import re +import json import logging -from typing import Union from .attribute import Attribute +from typing import Union, Optional from falkordb import Node as GraphNode, Edge as GraphEdge from graphrag_sdk.fixtures.regex import ( EDGE_LABEL_REGEX, @@ -13,7 +13,6 @@ logger = logging.getLogger(__name__) - class _RelationEntity: """ Represents a relation entity. @@ -35,7 +34,7 @@ def __init__(self, label: str): self.label = re.sub(r"([^a-zA-Z0-9_])", "", label) @staticmethod - def from_json(txt: str): + def from_json(txt: str) -> "_RelationEntity": """ Creates a _RelationEntity object from a JSON string. @@ -48,7 +47,7 @@ def from_json(txt: str): txt = txt if isinstance(txt, dict) else json.loads(txt) return _RelationEntity(txt.get("label", txt)) - def to_json(self): + def to_json(self) -> dict: """ Converts the _RelationEntity object to a JSON string. @@ -77,7 +76,7 @@ class Relation: label (str): The label of the relation. source (Union[_RelationEntity, str]): The source entity of the relation. target (Union[_RelationEntity, str]): The target entity of the relation. - attributes (list[Attribute]): The attributes associated with the relation. + attributes (Optional[list[Attribute]]): The attributes associated with the relation. Methods: from_graph(relation: GraphEdge, entities: list[GraphNode]) -> Relation: @@ -101,7 +100,7 @@ def __init__( label: str, source: Union[_RelationEntity, str], target: Union[_RelationEntity, str], - attributes: list[Attribute] = None, + attributes: Optional[list[Attribute]] = None, ): """ Initializes a Relation object. @@ -110,7 +109,7 @@ def __init__( label (str): The label of the relation. source (Union[_RelationEntity, str]): The source entity of the relation. target (Union[_RelationEntity, str]): The target entity of the relation. - attributes (list[Attribute], optional): The attributes associated with the relation. Defaults to None. + attributes (Optional[list[Attribute]]): The attributes associated with the relation. Defaults to None. """ attributes = attributes or [] if isinstance(source, str): @@ -129,7 +128,7 @@ def __init__( self.attributes = attributes @staticmethod - def from_graph(relation: GraphEdge, entities: list[GraphNode]): + def from_graph(relation: GraphEdge, entities: list[GraphNode]) -> "Relation": """ Creates a Relation object from a graph edge and a list of graph nodes. @@ -156,7 +155,7 @@ def from_graph(relation: GraphEdge, entities: list[GraphNode]): ) @staticmethod - def from_json(txt: Union[dict, str]): + def from_json(txt: Union[dict, str]) -> "Relation": """ Creates a Relation object from a JSON string or dictionary. @@ -179,7 +178,7 @@ def from_json(txt: Union[dict, str]): ) @staticmethod - def from_string(txt: str): + def from_string(txt: str) -> "Relation": """ Creates a Relation object from a string representation. @@ -220,7 +219,7 @@ def to_json(self) -> dict: "attributes": [attr.to_json() for attr in self.attributes], } - def combine(self, relation2: "Relation"): + def combine(self, relation2: "Relation") -> "Relation": """ Overwrites attributes of self with attributes of relation2. @@ -240,7 +239,7 @@ def combine(self, relation2: "Relation"): return self - def to_graph_query(self): + def to_graph_query(self) -> str: """ Generates a Cypher query string for creating the relation in a graph database. diff --git a/graphrag_sdk/source.py b/graphrag_sdk/source.py index 148a222f..dbe3b1dc 100644 --- a/graphrag_sdk/source.py +++ b/graphrag_sdk/source.py @@ -1,5 +1,5 @@ from abc import ABC -from typing import Optional, Iterator +from typing import Iterator, Optional from graphrag_sdk.document import Document from graphrag_sdk.document_loaders import ( PDFLoader, @@ -18,12 +18,11 @@ def Source(path: str, instruction: Optional[str] = None) -> "AbstractSource": Args: path (str): path to source - instruction (str): source specific instruction for the LLM - + instruction (Optional[str]): source specific instruction for the LLM + Returns: AbstractSource: A source object corresponding to the input path format. """ - if not isinstance(path, str) or path == "": raise Exception("Invalid argument, path should be a none empty string.") diff --git a/graphrag_sdk/steps/Step.py b/graphrag_sdk/steps/Step.py index 5ceec5d6..7f0471af 100644 --- a/graphrag_sdk/steps/Step.py +++ b/graphrag_sdk/steps/Step.py @@ -1,4 +1,4 @@ class Step: - def run(self): + def run(self) -> None: pass diff --git a/graphrag_sdk/steps/create_ontology_step.py b/graphrag_sdk/steps/create_ontology_step.py index 5df9ea8d..3b31f1e8 100644 --- a/graphrag_sdk/steps/create_ontology_step.py +++ b/graphrag_sdk/steps/create_ontology_step.py @@ -24,13 +24,12 @@ FIX_JSON_PROMPT, BOUNDARIES_PREFIX, ) -RENDER_STEP_SIZE = 0.5 +RENDER_STEP_SIZE = 0.5 logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) - class CreateOntologyStep(Step): """ Create Ontology Step @@ -41,25 +40,56 @@ def __init__( sources: list[AbstractSource], ontology: Ontology, model: GenerativeModel, - config: dict = { - "max_workers": 16, - "max_input_tokens": 500000, - "max_output_tokens": 8192, - }, - hide_progress: bool = False, + config: Optional[dict] = None, + hide_progress: Optional[bool] = False, ) -> None: + """ + Initialize the CreateOntologyStep. + + Args: + sources (List[AbstractSource]): List of sources from which ontology is created. + ontology (Ontology): The initial ontology to be merged with new extracted data. + model (GenerativeModel): The generative model used for processing and creating the ontology. + config (Optional[dict]): Configuration for the step, including thread workers and token limits. Defaults to standard config. + hide_progress (bool): Flag to hide the progress bar. Defaults to False. + """ self.sources = sources self.ontology = ontology - self.model = model.with_system_instruction(CREATE_ONTOLOGY_SYSTEM) - self.config = config + self.model = model + if config is None: + self.config = { + "max_workers": 16, + "max_input_tokens": 500000, + "max_output_tokens": 8192, + } + else: + self.config = config self.hide_progress = hide_progress self.process_files = 0 self.counter_lock = Lock() - def _create_chat(self): - return self.model.start_chat({"response_validation": False}) + def _create_chat(self) -> GenerativeModelChatSession: + """ + Create a new chat session with the generative model. + + Returns: + GenerativeModelChatSession: A session for interacting with the generative model. + """ + return self.model.start_chat(CREATE_ONTOLOGY_SYSTEM) def run(self, boundaries: Optional[str] = None): + """ + Execute the ontology creation process by extracting data from all sources. + + Args: + boundaries (Optional[str]): Additional boundaries or constraints for the ontology creation. + + Returns: + Ontology: The final ontology after merging with extracted data. + + Raises: + Exception: If ontology creation fails and no entities are found. + """ tasks: list[Future[Ontology]] = [] with tqdm(total=len(self.sources) + 1, desc="Process Documents", disable=self.hide_progress) as pbar: @@ -104,8 +134,21 @@ def _process_source( source: AbstractSource, o: Ontology, boundaries: Optional[str] = None, - retries: int = 1, + retries: Optional[int] = 1, ): + """ + Process a single document and extract ontology data. + + Args: + chat_session (GenerativeModelChatSession): The chat session for interacting with the generative model. + document (Document): The document to extract data from. + o (Ontology): The current ontology to be merged with extracted data. + boundaries (Optional[str]): Constraints for data extraction. + retries (Optional[int]) Number of retries for processing the document. + + Returns: + Ontology: The updated ontology after processing the document. + """ try: document = next(source.load()) @@ -170,6 +213,16 @@ def _process_source( return o def _fix_ontology(self, chat_session: GenerativeModelChatSession, o: Ontology): + """ + Fix and validate the ontology using the generative model. + + Args: + chat_session (GenerativeModelChatSession): The chat session for interacting with the model. + o (Ontology): The ontology to fix and validate. + + Returns: + Ontology: The fixed and validated ontology. + """ logger.debug(f"Fixing ontology...") user_message = FIX_ONTOLOGY_PROMPT.format(ontology=o) @@ -230,8 +283,22 @@ def _call_model( self, chat_session: GenerativeModelChatSession, prompt: str, - retry=6, + retry: Optional[int] = 6, ): + """ + Call the generative model with retries and rate limiting. + + Args: + chat_session (GenerativeModelChatSession): The chat session for interacting with the model. + prompt (str): The prompt to send to the model. + retry (Optional[int]): Number of retries if quota is exceeded or errors occur. + + Returns: + GenerationResponse: The model's response. + + Raises: + Exception: If the model fails after exhausting retries. + """ try: return chat_session.send_message(prompt) except Exception as e: diff --git a/graphrag_sdk/steps/extract_data_step.py b/graphrag_sdk/steps/extract_data_step.py index 65258968..6e8a1224 100644 --- a/graphrag_sdk/steps/extract_data_step.py +++ b/graphrag_sdk/steps/extract_data_step.py @@ -6,6 +6,7 @@ from uuid import uuid4 from falkordb import Graph from threading import Lock +from typing import Optional from graphrag_sdk.steps.Step import Step from graphrag_sdk.document import Document from ratelimit import limits, sleep_and_retry @@ -44,19 +45,32 @@ def __init__( ontology: Ontology, model: GenerativeModel, graph: Graph, - config: dict = { - "max_workers": 16, - "max_input_tokens": 500000, - "max_output_tokens": 8192, - }, - hide_progress: bool = False, + config: Optional[dict] = None, + hide_progress: Optional[bool] = False, ) -> None: + """ + Initialize the ExtractDataStep. + + Args: + sources (list[AbstractSource]): List of data sources to process. + ontology (Ontology): The ontology associated with the knowledge graph. + model (GenerativeModel): The generative model used for data extraction. + graph (Graph): The FalkorDB graph instance. + config (Optional[dict]): Configuration options for the step. + hide_progress (Optional[bool]): Flag to hide progress bar. Defaults to False. + """ self.sources = sources self.ontology = ontology self.config = config - self.model = model.with_system_instruction( - EXTRACT_DATA_SYSTEM.replace("#ONTOLOGY", str(self.ontology.to_json())) - ) + if config is None: + self.config = { + "max_workers": 16, + "max_input_tokens": 500000, + "max_output_tokens": 8192, + } + else: + self.config = config + self.model = model self.graph = graph self.hide_progress = hide_progress self.process_files = 0 @@ -64,11 +78,16 @@ def __init__( if not os.path.exists("logs"): os.makedirs("logs") - def _create_chat(self): - return self.model.start_chat({"response_validation": False}) - - def run(self, instructions: str = None) -> list[AbstractSource]: + def _create_chat(self) -> GenerativeModelChatSession: + return self.model.start_chat(EXTRACT_DATA_SYSTEM.replace("#ONTOLOGY", str(self.ontology.to_json()))) + def run(self, instructions: Optional[str] = None): + """ + Run the data extraction process. + + Args: + instructions (Optional[str]): Optional additional instructions for data extraction. + """ # Each task is represented by a tuple containing: # 1. A Future object (the asynchronous processing task) # 2. A string (the ID of the document being processed) @@ -117,11 +136,24 @@ def _process_document( document: Document, ontology: Ontology, graph: Graph, - source_instructions: str = "", - instructions: str = "", - retries: int = 1, + source_instructions: Optional[str] = "", + instructions: Optional[str] = "", + retries: Optional[int] = 1, ): try: + """ + Process a single source document and extract entities and relations. + + Args: + task_id (str): The unique ID for the task. + chat_session (GenerativeModelChatSession): The chat session for the extraction. + document (Document): The document to process. + ontology (Ontology): The ontology associated with the graph. + graph (Graph): The FalkorDB graph instance. + source_instructions (Optional[str]): Instructions specific to the source. + instructions (Optional[str]): Additional instructions. + retries (Optional[int]): Number of times to retry if the model stops unexpectedly. + """ _task_logger = logging.getLogger(task_id) _task_logger.setLevel(logging.DEBUG) @@ -220,7 +252,15 @@ def _process_document( with self.counter_lock: self.process_files += 1 - def _create_entity(self, graph: Graph, args: dict, ontology: Ontology): + def _create_entity(self, graph: Graph, args: dict, ontology: Ontology) -> None: + """ + Create an entity in the graph based on the extracted data. + + Args: + graph (Graph): The graph instance to create the entity in. + args (dict): The entity data extracted from the source. + ontology (Ontology): The ontology to validate the entity type. + """ # Get unique attributes from entity entity = ontology.get_entity_with_label(args["label"]) if entity is None: @@ -252,7 +292,15 @@ def _create_entity(self, graph: Graph, args: dict, ontology: Ontology): result = graph.query(query) return result - def _create_relation(self, graph: Graph, args: dict, ontology: Ontology): + def _create_relation(self, graph: Graph, args: dict, ontology: Ontology) -> None: + """ + Create a relation in the graph based on the extracted data. + + Args: + graph (Graph): The graph instance to create the relation in. + args (dict): The relation data extracted from the source. + ontology (Ontology): The ontology to validate the relation type. + """ relations = ontology.get_relations_with_label(args["label"]) if len(relations) == 0: print(f"Relations with label {args['label']} not found in ontology") @@ -304,7 +352,22 @@ def _call_model( prompt: str, retry: int = 6, output_method: OutputMethod = OutputMethod.DEFAULT - ): + ) -> GenerationResponse: + """ + Call the generative model with rate limiting and retries. + + Args: + chat_session (GenerativeModelChatSession): The chat session for interacting with the model. + prompt (str): The prompt to send to the model. + retry (Optional[int]): Number of retries in case of quota exceeded or errors. + output_method (Optional[OutputMethod]): The output method for the response. + + Returns: + GenerationResponse: The model's response. + + Raises: + Exception: If an error occurs after exhausting retries. + """ try: return chat_session.send_message(prompt, output_method=output_method) except Exception as e: diff --git a/graphrag_sdk/steps/graph_query_step.py b/graphrag_sdk/steps/graph_query_step.py index a9ac8bb2..0edffb22 100644 --- a/graphrag_sdk/steps/graph_query_step.py +++ b/graphrag_sdk/steps/graph_query_step.py @@ -1,5 +1,6 @@ import logging from falkordb import Graph +from typing import Optional from graphrag_sdk.steps.Step import Step from graphrag_sdk.ontology import Ontology from graphrag_sdk.models import ( @@ -25,11 +26,23 @@ def __init__( graph: Graph, ontology: Ontology, chat_session: GenerativeModelChatSession, - config: dict = None, - last_answer: str = None, - cypher_prompt: str = None, - cypher_prompt_with_history: str = None, + config: Optional[dict] = None, + last_answer: Optional[str] = None, + cypher_prompt: Optional[str] = None, + cypher_prompt_with_history: Optional[str] = None, ) -> None: + """ + Initializes the GraphQueryGenerationStep object. + + Args: + graph (Graph): The graph object to query. + ontology (Ontology): The ontology object. + chat_session (GenerativeModelChatSession): The chat session object. + config (Optional[dict]): The configuration object. + last_answer (Optional[str]): The last answer. + cypher_prompt (Optional[str]): The Cypher prompt. + cypher_prompt_with_history (Optional[str]): The Cypher prompt with history. + """ self.ontology = ontology self.config = config or {} self.graph = graph @@ -38,7 +51,17 @@ def __init__( self.cypher_prompt = cypher_prompt self.cypher_prompt_with_history = cypher_prompt_with_history - def run(self, question: str, retries: int = 10): + def run(self, question: str, retries: Optional[int] = 10): + """ + Run the step to generate and validate a Cypher query. + + Args: + question (str): The question being asked to generate the query. + retries (Optional[int]): Number of retries allowed in case of errors. + + Returns: + tuple[Optional[str], Optional[str]]: The context and the generated Cypher query. + """ cypher = "" for i in range(retries): try: diff --git a/graphrag_sdk/steps/qa_step.py b/graphrag_sdk/steps/qa_step.py index 286cfd8b..67d452b7 100644 --- a/graphrag_sdk/steps/qa_step.py +++ b/graphrag_sdk/steps/qa_step.py @@ -1,11 +1,12 @@ import logging +from typing import Optional from graphrag_sdk.steps.Step import Step from graphrag_sdk.models import GenerativeModelChatSession + logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) - class QAStep(Step): """ QA Step @@ -14,14 +15,33 @@ class QAStep(Step): def __init__( self, chat_session: GenerativeModelChatSession, - config: dict = None, - qa_prompt: str = None, + config: Optional[dict] = None, + qa_prompt: Optional[str] = None, ) -> None: + """ + Initialize the QA Step. + + Args: + chat_session (GenerativeModelChatSession): The chat session for handling the QA. + config (Optional[dict]): Optional configuration for the step. + qa_prompt (Optional[str]): The prompt for the + """ self.config = config or {} self.chat_session = chat_session self.qa_prompt = qa_prompt - def run(self, question: str, cypher: str, context: str): + def run(self, question: str, cypher: str, context: str) -> str: + """ + Run the QA step. + + Args: + question (str): The question being asked. + cypher (str): The Cypher query to run. + context (str): Context for the QA. + + Returns: + str: The response from the QA session. + """ qa_prompt = self.qa_prompt.format( context=context, cypher=cypher, question=question ) diff --git a/tests/test_kg_gemini.py b/tests/test_kg_gemini.py index cbfdf2b1..adf63e22 100644 --- a/tests/test_kg_gemini.py +++ b/tests/test_kg_gemini.py @@ -1,8 +1,6 @@ import re -import os import logging import unittest -import vertexai from falkordb import FalkorDB from dotenv import load_dotenv from graphrag_sdk.entity import Entity @@ -13,13 +11,11 @@ from graphrag_sdk.models.gemini import GeminiGenerativeModel from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig -load_dotenv() +load_dotenv() logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) -vertexai.init(project=os.getenv("PROJECT_ID"), location=os.getenv("REGION")) - class TestKGGemini(unittest.TestCase): """ From 9bb851936126accdf36b814a21630b61ab7ac4a4 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 26 Feb 2025 10:17:23 +0200 Subject: [PATCH 019/136] fix-typo --- graphrag_sdk/chat_session.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index c04dfbce..e013cdee 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -64,7 +64,7 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, ) self.last_answer = None - def send_message(self, message: str) -> str: + def send_message(self, message: str) -> dict: """ Sends a message to the chat session. From 6ba1aeff27ed66df94604564d263dad029226268 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 26 Feb 2025 11:18:03 +0200 Subject: [PATCH 020/136] add-missing-opt --- graphrag_sdk/helpers.py | 6 ++++-- graphrag_sdk/orchestrator/orchestrator.py | 5 +++-- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/graphrag_sdk/helpers.py b/graphrag_sdk/helpers.py index 9e1d982b..8c7693fe 100644 --- a/graphrag_sdk/helpers.py +++ b/graphrag_sdk/helpers.py @@ -7,13 +7,13 @@ logger = logging.getLogger(__name__) -def extract_json(text: Union[str, dict], skip_repair=False) -> str: +def extract_json(text: Union[str, dict], skip_repair: Optional[bool] = False) -> str: """ Extracts JSON from a string or dictionary, optionally skipping JSON repair. Args: text (Union[str, dict]): The input text or dictionary. - skip_repair (bool): Flag to skip JSON repair. Defaults to False. + skip_repair (Optional[bool]): Flag to skip JSON repair. Defaults to False. Returns: str: The extracted JSON as a string. @@ -120,9 +120,11 @@ def validate_cypher( ) -> Optional[list[str]]: """ Validates a Cypher query against the ontology. + Args: cypher (str): The Cypher query. ontology (Ontology): The ontology to validate against. + Returns: Optional[list[str]]: A list of validation errors, or None if valid. """ diff --git a/graphrag_sdk/orchestrator/orchestrator.py b/graphrag_sdk/orchestrator/orchestrator.py index 73bb4cd3..388b7ea9 100644 --- a/graphrag_sdk/orchestrator/orchestrator.py +++ b/graphrag_sdk/orchestrator/orchestrator.py @@ -1,4 +1,5 @@ import logging +from typing import Optional from graphrag_sdk.agents import Agent from graphrag_sdk.helpers import extract_json from graphrag_sdk.models import GenerativeModel, GenerativeModelChatSession @@ -22,12 +23,12 @@ class Orchestrator: and assigns agents to execute tasks. """ - def __init__(self, model: GenerativeModel, backstory: str = ""): + def __init__(self, model: GenerativeModel, backstory: Optional[str] = ""): """ Initialize the Orchestrator with a generative model and an optional backstory. Args: model (GenerativeModel): The model that powers the orchestration process. - backstory (str): Optional backstory or context to be included in the orchestration system. + backstory (Optional[str]): Optional backstory or context to be included in the orchestration system. """ self._model = model self._backstory = backstory From 67d9d4a6eedf2e00bfae2ec8b105cf51c0feccc8 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 26 Feb 2025 11:55:46 +0200 Subject: [PATCH 021/136] fix-er-orc --- graphrag_sdk/orchestrator/orchestrator.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/orchestrator/orchestrator.py b/graphrag_sdk/orchestrator/orchestrator.py index 388b7ea9..251e9e8e 100644 --- a/graphrag_sdk/orchestrator/orchestrator.py +++ b/graphrag_sdk/orchestrator/orchestrator.py @@ -26,6 +26,7 @@ class Orchestrator: def __init__(self, model: GenerativeModel, backstory: Optional[str] = ""): """ Initialize the Orchestrator with a generative model and an optional backstory. + Args: model (GenerativeModel): The model that powers the orchestration process. backstory (Optional[str]): Optional backstory or context to be included in the orchestration system. @@ -57,10 +58,12 @@ def register_agent(self, agent: Agent): def ask(self, question: str) -> OrchestratorResult: """ Ask the orchestrator a question and run the corresponding execution plan. + Args: question (str): The user's question. + Returns: - OrchestratorRunner: The result of executing the plan. + OrchestratorResult: The result of executing the plan. """ return self.runner(question).run() From 3478b1f88c29966c87847658662d24ce9e0055f0 Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Wed, 26 Feb 2025 23:47:33 +0200 Subject: [PATCH 022/136] Define AttributeType as Enum --- graphrag_sdk/attribute.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index 402a10f5..05b5f85c 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -2,12 +2,13 @@ import json import logging from typing import Union +from enum import Enum from graphrag_sdk.fixtures.regex import * logger = logging.getLogger(__name__) -class AttributeType: +class AttributeType(Enum): """ Represents the types of attributes in the system. """ From 78de53cd9ec038b9a41e3892f39466253e19fb02 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Thu, 27 Feb 2025 14:12:48 +0200 Subject: [PATCH 023/136] update-gemini-mov --- examples/movies/demo-movies.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/movies/demo-movies.ipynb b/examples/movies/demo-movies.ipynb index 276d84c5..6b0d55c0 100644 --- a/examples/movies/demo-movies.ipynb +++ b/examples/movies/demo-movies.ipynb @@ -96,11 +96,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "model = LiteModel(model_name=\"gemini/gemini-2.0-flash-exp\")\n", + "model = LiteModel(model_name=\"gemini/gemini-2.0-flash\")\n", "\n", "boundaries = \"\"\"\n", " Extract only the most relevant information about all the movies, actors, and directors over the text.\n", From 6b7e52fefc407d8cf8dcb60addac5578d414d6e3 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Thu, 27 Feb 2025 16:05:43 +0200 Subject: [PATCH 024/136] fix-json-conv --- graphrag_sdk/attribute.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index 05b5f85c..bf2649cc 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -153,7 +153,7 @@ def to_json(self): """ json_data = { "name": self.name, - "type": self.type, + "type": self.type.value, "unique": self.unique, "required": self.required, } From 0ae14146e7efaa04ece52d66b9e3f5fd33382dae Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Sun, 2 Mar 2025 14:28:46 +0200 Subject: [PATCH 025/136] fix-synonym-er --- graphrag_sdk/attribute.py | 31 +++++++++++++++---------------- 1 file changed, 15 insertions(+), 16 deletions(-) diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index 9514623f..b1818a17 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -21,20 +21,6 @@ class AttributeType(Enum): MAP = "map" VECTOR = "vectorf32" - - # Synonyms for attribute types - _SYNONYMS = { - "string": STRING, - "integer": NUMBER, - "float": NUMBER, - "number": NUMBER, - "boolean": BOOLEAN, - "list": LIST, - "point": POINT, - "map": MAP, - "vectorf32": VECTOR, - } - @staticmethod def from_string(txt: str) -> "AttributeType": """ @@ -53,10 +39,23 @@ def from_string(txt: str) -> "AttributeType": normalized_txt = txt.lower() # Find the matching attribute type - if normalized_txt in AttributeType._SYNONYMS: - return AttributeType._SYNONYMS[normalized_txt] + if normalized_txt in _SYNONYMS: + return _SYNONYMS[normalized_txt] raise ValueError(f"Invalid attribute type: {txt}") + +# Mapping of string representations to AttributeType enum members. +_SYNONYMS = { + "string": AttributeType.STRING, + "integer": AttributeType.NUMBER, + "float": AttributeType.NUMBER, + "number": AttributeType.NUMBER, + "boolean": AttributeType.BOOLEAN, + "list": AttributeType.LIST, + "point": AttributeType.POINT, + "map": AttributeType.MAP, + "vectorf32": AttributeType.VECTOR, +} class Attribute: """ Represents an attribute of an entity or relation in the ontology. From d309cf69586154cd992fb465d4e32e8a700a27f6 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Sun, 2 Mar 2025 17:58:49 +0200 Subject: [PATCH 026/136] additional-args --- graphrag_sdk/models/azure_openai.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index 253a3336..a1615e60 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -1,4 +1,5 @@ import os +from typing import Any from typing import Optional from openai import AzureOpenAI from .model import ( @@ -16,13 +17,12 @@ class AzureOpenAiGenerativeModel(GenerativeModel): A generative model that interfaces with Azure's OpenAI API for chat completions. """ - client: AzureOpenAI = None - def __init__( self, model_name: str, generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, + **kwargs: Any, ): """ Initialize the AzureOpenAiGenerativeModel with required parameters. @@ -31,10 +31,12 @@ def __init__( model_name (str): Name of the Azure OpenAI model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. + kwargs (Any): Additional arguments required by Azure OpenAI API. """ self.model_name = model_name self.generation_config = generation_config or GenerativeModelConfig() self.system_instruction = system_instruction + self.additional_params = kwargs # Credentials self.api_key = os.getenv("AZURE_OPENAI_API_KEY") @@ -45,6 +47,13 @@ def __init__( raise ValueError( "Missing credentials in the environment: AZURE_OPENAI_API_KEY, AZURE_ENDPOINT, or AZURE_API_VERSION." ) + + self.client = AzureOpenAI( + azure_endpoint=self.azure_endpoint, + api_version=self.api_version, + api_key=self.api_key, + **self.additional_params, # Azure additional parameters + ) def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: From bc53eddd21069686b43aed160a7cd238b494b753 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Sun, 2 Mar 2025 18:00:39 +0200 Subject: [PATCH 027/136] fix-doc --- graphrag_sdk/models/azure_openai.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index a1615e60..d5b723dc 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -31,7 +31,7 @@ def __init__( model_name (str): Name of the Azure OpenAI model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. - kwargs (Any): Additional arguments required by Azure OpenAI API. + kwargs (Any): Additional arguments optional by Azure OpenAI API. """ self.model_name = model_name self.generation_config = generation_config or GenerativeModelConfig() From 31165987753351fa03feb324dadac8d5ad2bed89 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 5 Mar 2025 12:30:34 +0200 Subject: [PATCH 028/136] fix-config --- graphrag_sdk/models/azure_openai.py | 4 +-- graphrag_sdk/models/gemini.py | 13 +++++--- graphrag_sdk/models/model.py | 47 +++++++++++++++++------------ tests/test_kg_gemini.py | 4 +-- tests/test_kg_litellm_openai.py | 4 +-- tests/test_kg_openai.py | 4 +-- 6 files changed, 45 insertions(+), 31 deletions(-) diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index 253a3336..573de3c8 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -75,11 +75,11 @@ def ask(self, message: str) -> GenerationResponse: {"role": "system", "content": self.system_instruction}, {"role": "user", "content": message[:14385]}, ], - max_tokens=self.generation_config.max_output_tokens, + max_tokens=self.generation_config.max_tokens, temperature=self.generation_config.temperature, top_p=self.generation_config.top_p, top_k=self.generation_config.top_k, - stop=self.generation_config.stop_sequences, + stop=self.generation_config.stop, ) return self._parse_generate_content_response(response) diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 31e4c11c..429d8fc1 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -37,7 +37,7 @@ def __init__( system_instruction (Optional[str]): System-level instruction for the model. """ self._model_name = model_name - self._generation_config = generation_config + self._generation_config = generation_config or GenerativeModelConfig() self._system_instruction = system_instruction configure(api_key=os.environ["GOOGLE_API_KEY"]) @@ -58,8 +58,8 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode temperature=self._generation_config.temperature, top_p=self._generation_config.top_p, top_k=self._generation_config.top_k, - max_output_tokens=self._generation_config.max_output_tokens, - stop_sequences=self._generation_config.stop_sequences, + max_output_tokens=self._generation_config.max_tokens, + stop_sequences=self._generation_config.stop, ) if self._generation_config is not None else None @@ -170,7 +170,12 @@ def _adjust_generation_config(self, output_method: OutputMethod) -> dict: "response_mime_type": "application/json", "temperature": 0 } - return self._model._generation_config + + config = self._model._generation_config.to_json() + config["max_output_tokens"] = config.pop("max_tokens") + config["response_mime_type"] = config.pop("response_format") + config["stop_sequences"] = config.pop("stop") + return config def delete_last_message(self): """ diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index bef59438..72047437 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -14,17 +14,26 @@ class OutputMethod(Enum): class GenerativeModelConfig: """ - Configuration for a generative model + Configuration for a generative model. + + This configuration follows OpenAI-style parameter naming but is designed to be compatible with other generative models. + Args: - temperature (Optional[float]): The temperature to use for sampling. - top_p (Optional[float]): The top-p value to use for sampling. - top_k (Optional[int]): The top-k value to use for sampling. - max_output_tokens (Optional[int]): The maximum number of tokens to generate. - stop_sequences (Optional[list[str]]): The stop sequences to use for sampling. - response_format (Optional[dict]): The format of the response. - Examples: - - >>> config = GenerativeModelConfig(temperature=0.5, top_p=0.9, top_k=50, max_output_tokens=100, stop_sequences=[".", "?", "!"]) + temperature (Optional[float]): Controls the randomness of the output. Higher values (e.g., 1.0) make responses more random, + while lower values (e.g., 0.1) make them more deterministic. + top_p (Optional[float]): Nucleus sampling parameter. A value of 0.9 considers only the top 90% of probability mass. + top_k (Optional[int]): Limits sampling to the top-k most probable tokens. + max_tokens (Optional[int]): The maximum number of tokens the model is allowed to generate in a response. + stop (Optional[list[str]]): A list of stop sequences that signal the model to stop generating further tokens. + response_format (Optional[dict]): Specifies the desired format of the response, if supported by the model. + Example: + >>> config = GenerativeModelConfig( + ... temperature=0.5, + ... top_p=0.9, + ... top_k=50, + ... max_tokens=100, + ... stop=[".", "?", "!"] + ... ) """ def __init__( @@ -32,26 +41,26 @@ def __init__( temperature: Optional[float] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, - max_output_tokens: Optional[int] = None, - stop_sequences: Optional[list[str]] = None, + max_tokens: Optional[int] = None, + stop: Optional[list[str]] = None, response_format: Optional[dict] = None, ): self.temperature = temperature self.top_p = top_p self.top_k = top_k - self.max_output_tokens = max_output_tokens - self.stop_sequences = stop_sequences + self.max_tokens = max_tokens + self.stop = stop self.response_format = response_format def __str__(self) -> str: - return f"GenerativeModelConfig(temperature={self.temperature}, top_p={self.top_p}, top_k={self.top_k}, max_output_tokens={self.max_output_tokens}, stop_sequences={self.stop_sequences})" + return f"GenerativeModelConfig(temperature={self.temperature}, top_p={self.top_p}, top_k={self.top_k}, max_output_tokens={self.max_tokens}, stop_sequences={self.stop})" def to_json(self) -> dict: return { "temperature": self.temperature, "top_p": self.top_p, - "max_tokens": self.max_output_tokens, - "stop": self.stop_sequences, + "max_tokens": self.max_tokens, + "stop": self.stop, "response_format": self.response_format, } @@ -61,8 +70,8 @@ def from_json(json: dict) -> "GenerativeModelConfig": temperature=json.get("temperature"), top_p=json.get("top_p"), top_k=json.get("top_k"), - max_output_tokens=json.get("max_tokens"), - stop_sequences=json.get("stop"), + max_tokens=json.get("max_tokens"), + stop=json.get("stop"), ) diff --git a/tests/test_kg_gemini.py b/tests/test_kg_gemini.py index adf63e22..f0ed7957 100644 --- a/tests/test_kg_gemini.py +++ b/tests/test_kg_gemini.py @@ -9,7 +9,7 @@ from graphrag_sdk.relation import Relation from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk.models.gemini import GeminiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig load_dotenv() @@ -71,7 +71,7 @@ def setUpClass(cls): cls.graph_name = "IMDB_gemini" - model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001") + model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001", generation_config=GenerativeModelConfig(temperature=0)) cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, diff --git a/tests/test_kg_litellm_openai.py b/tests/test_kg_litellm_openai.py index 253d7bfa..77b2ef5f 100644 --- a/tests/test_kg_litellm_openai.py +++ b/tests/test_kg_litellm_openai.py @@ -9,7 +9,7 @@ from graphrag_sdk.ontology import Ontology from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk.models.litellm import LiteModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig load_dotenv() @@ -68,7 +68,7 @@ def setUpClass(cls): ) ) cls.graph_name = "IMDB_openai" - model = LiteModel(model_name="gpt-4o") + model = LiteModel(model_name="gpt-4o", generation_config=GenerativeModelConfig(temperature=0)) cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, diff --git a/tests/test_kg_openai.py b/tests/test_kg_openai.py index 785a28df..23ed1871 100644 --- a/tests/test_kg_openai.py +++ b/tests/test_kg_openai.py @@ -9,7 +9,7 @@ from graphrag_sdk.ontology import Ontology from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk.models.openai import OpenAiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig load_dotenv() @@ -68,7 +68,7 @@ def setUpClass(cls): ) ) cls.graph_name = "IMDB_openai" - model = OpenAiGenerativeModel(model_name="gpt-3.5-turbo-0125") + model = OpenAiGenerativeModel(model_name="gpt-3.5-turbo-0125", generation_config=GenerativeModelConfig(temperature=0)) cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, From ff62dbd33c200152ab6e1de8bfd776968f60a736 Mon Sep 17 00:00:00 2001 From: Gal Shubeli <124919062+galshubeli@users.noreply.github.com> Date: Wed, 5 Mar 2025 12:33:37 +0200 Subject: [PATCH 029/136] Update graphrag_sdk/models/model.py Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- graphrag_sdk/models/model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index 72047437..a7b87c29 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -53,7 +53,7 @@ def __init__( self.response_format = response_format def __str__(self) -> str: - return f"GenerativeModelConfig(temperature={self.temperature}, top_p={self.top_p}, top_k={self.top_k}, max_output_tokens={self.max_tokens}, stop_sequences={self.stop})" + return f"GenerativeModelConfig(temperature={self.temperature}, top_p={self.top_p}, top_k={self.top_k}, max_tokens={self.max_tokens}, stop={self.stop})" def to_json(self) -> dict: return { From 5189050c68bd7dbc6cd591b274fac93e58027e17 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 5 Mar 2025 13:33:17 +0200 Subject: [PATCH 030/136] add-comment --- graphrag_sdk/models/gemini.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 429d8fc1..85e9f464 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -172,6 +172,8 @@ def _adjust_generation_config(self, output_method: OutputMethod) -> dict: } config = self._model._generation_config.to_json() + + # Convert OpenAI-style config keys to GoogleAI-style keys config["max_output_tokens"] = config.pop("max_tokens") config["response_mime_type"] = config.pop("response_format") config["stop_sequences"] = config.pop("stop") From 5be9461641c97bc088bcffb16153a0c6f06b4e58 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 5 Mar 2025 14:15:41 +0200 Subject: [PATCH 031/136] update-config-usage --- graphrag_sdk/models/gemini.py | 49 +++++++++++++++++++---------------- tests/test_kg_gemini.py | 5 ++-- 2 files changed, 30 insertions(+), 24 deletions(-) diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 85e9f464..117d55d6 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -30,15 +30,28 @@ def __init__( system_instruction: Optional[str] = None, ): """ - Initialize the GoogleGenerativeModel with required parameters. + Initializes the GoogleGenerativeModel with the specified parameters. + Args: - model_name (str): Name of the GoogleAI model. + model_name (str): The name of the GoogleAI model to use. generation_config (Optional[GoogleGenerationConfig]): Configuration settings for generation. - system_instruction (Optional[str]): System-level instruction for the model. + If not provided, a default instance of `GoogleGenerationConfig` is used. + system_instruction (Optional[str]): An optional system-level instruction to guide the model’s behavior. + + Raises: + TypeError: If `generation_config` is provided but is not an instance of `GoogleGenerationConfig`. """ + if generation_config is not None and not isinstance(generation_config, GoogleGenerationConfig): + raise TypeError( + "generation_config must be an instance of GoogleGenerationConfig " + "(from google.generativeai import GenerationConfig as GoogleGenerationConfig)." + ) + self._model_name = model_name - self._generation_config = generation_config or GenerativeModelConfig() + self._generation_config = generation_config or GoogleGenerationConfig() self._system_instruction = system_instruction + + # Configure the API key for Google Generative AI configure(api_key=os.environ["GOOGLE_API_KEY"]) def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: @@ -54,13 +67,7 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode self._model = GoogleGenerativeModel( self._model_name, generation_config=( - GoogleGenerationConfig( - temperature=self._generation_config.temperature, - top_p=self._generation_config.top_p, - top_k=self._generation_config.top_k, - max_output_tokens=self._generation_config.max_tokens, - stop_sequences=self._generation_config.stop, - ) + self._generation_config if self._generation_config is not None else None ), @@ -102,7 +109,13 @@ def to_json(self) -> dict: """ return { "model_name": self._model_name, - "generation_config": self._generation_config.to_json(), + "generation_config": { + "temperature": self._generation_config.temperature, + "top_p": self._generation_config.top_p, + "max_output_tokens": self._generation_config.max_output_tokens, + "stop_sequences": self._generation_config.stop_sequences, + "response_mime_type": self._generation_config.response_mime_type, + }, "system_instruction": self._system_instruction, } @@ -117,9 +130,7 @@ def from_json(json: dict) -> "GenerativeModel": """ return GeminiGenerativeModel( model_name=json["model_name"], - generation_config=GenerativeModelConfig.from_json( - json["generation_config"] - ), + generation_config=GoogleGenerationConfig(**json["generation_config"]), system_instruction=json["system_instruction"], ) @@ -171,13 +182,7 @@ def _adjust_generation_config(self, output_method: OutputMethod) -> dict: "temperature": 0 } - config = self._model._generation_config.to_json() - - # Convert OpenAI-style config keys to GoogleAI-style keys - config["max_output_tokens"] = config.pop("max_tokens") - config["response_mime_type"] = config.pop("response_format") - config["stop_sequences"] = config.pop("stop") - return config + return self._model._generation_config def delete_last_message(self): """ diff --git a/tests/test_kg_gemini.py b/tests/test_kg_gemini.py index f0ed7957..03c59cc3 100644 --- a/tests/test_kg_gemini.py +++ b/tests/test_kg_gemini.py @@ -9,7 +9,8 @@ from graphrag_sdk.relation import Relation from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk.models.gemini import GeminiGenerativeModel -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from google.generativeai import GenerationConfig as GoogleGenerationConfig load_dotenv() @@ -71,7 +72,7 @@ def setUpClass(cls): cls.graph_name = "IMDB_gemini" - model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001", generation_config=GenerativeModelConfig(temperature=0)) + model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001", generation_config=GoogleGenerationConfig(temperature=0)) cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, From b2a12636e2b7011bd1b986a2a207475f07881dd6 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 5 Mar 2025 14:36:08 +0200 Subject: [PATCH 032/136] v0.6.2 --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 325c77bb..e8fbcb8d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "graphrag_sdk" -version = "0.6.1" +version = "0.6.2" license = "MIT" description = "Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] From 19b8d7e158e3628fd8a2929d714160787b2245c1 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 10 Mar 2025 14:13:07 +0200 Subject: [PATCH 033/136] standart-tests --- .github/workflows/test.yml | 2 +- .gitignore | 3 +- .../{test_metrics.py => graph_metrics.py} | 148 ++-------- tests/test_rag.py | 275 +++++++++++------- 4 files changed, 205 insertions(+), 223 deletions(-) rename graphrag_sdk/{test_metrics.py => graph_metrics.py} (78%) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 39625ef6..e343b067 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -27,7 +27,7 @@ jobs: strategy: matrix: - model: [gemini/gemini-2.0-flash-exp, openai/gpt-4o] # List of models + model: [gemini/gemini-2.0-flash, openai/gpt-4o] # List of models steps: - uses: actions/checkout@v4 diff --git a/.gitignore b/.gitignore index ab174994..c3418c0c 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,5 @@ output logs falkordb-data -weaviate-data \ No newline at end of file +weaviate-data +.deepeval_telemtry.txt diff --git a/graphrag_sdk/test_metrics.py b/graphrag_sdk/graph_metrics.py similarity index 78% rename from graphrag_sdk/test_metrics.py rename to graphrag_sdk/graph_metrics.py index be264969..d023cba4 100644 --- a/graphrag_sdk/test_metrics.py +++ b/graphrag_sdk/graph_metrics.py @@ -1,133 +1,41 @@ +""" +Metrics for evaluating Knowledge Graph performance. + +This module provides two metrics: +1. GraphContextualRelevancy - Measures how relevant the retrieved context is to the input query +2. GraphContextualRecall - Measures how well the expected output is supported by the retrieved context +""" + from typing import Optional -from deepeval.metrics import BaseMetric, AnswerRelevancyMetric, FaithfulnessMetric, ContextualRelevancyMetric -from deepeval.test_case import LLMTestCase +from deepeval.metrics import BaseMetric from typing import Optional, List, Union - -from deepeval.utils import get_or_create_event_loop, prettify_list +from deepeval.utils import prettify_list +from deepeval.test_case import LLMTestCase +from deepeval.models import DeepEvalBaseLLM +from deepeval.metrics.indicator import metric_progress_indicator +from deepeval.metrics.contextual_relevancy.schema import ContextualRelevancyVerdicts +from deepeval.metrics.contextual_recall.schema import ( + Reason, + Verdicts, + ContextualRecallVerdict,) +from deepeval.test_case import ( + LLMTestCase, + LLMTestCaseParams, + ConversationalTestCase,) from deepeval.metrics.utils import ( construct_verbose_logs, trimAndLoadJson, check_llm_test_case_params, - initialize_model, -) -from deepeval.test_case import ( - LLMTestCase, - LLMTestCaseParams, - ConversationalTestCase, -) - -from deepeval.metrics.contextual_relevancy.schema import * -from deepeval.metrics import BaseMetric -from deepeval.models import DeepEvalBaseLLM -from deepeval.metrics.contextual_recall.template import ContextualRecallTemplate -from deepeval.metrics.indicator import metric_progress_indicator -from deepeval.metrics.contextual_recall.schema import * - -required_params: List[LLMTestCaseParams] = [ + initialize_model,) +REQUIRED_PARAMS: List[LLMTestCaseParams] = [ LLMTestCaseParams.INPUT, LLMTestCaseParams.ACTUAL_OUTPUT, LLMTestCaseParams.RETRIEVAL_CONTEXT, LLMTestCaseParams.EXPECTED_OUTPUT, ] -class CombineMetrics(BaseMetric): - def __init__( - self, - threshold: float = 0.5, - evaluation_model: Optional[str] = "gpt-4o", - include_reason: bool = True, - async_mode: bool = True, - strict_mode: bool = False, - ): - self.threshold = 1 if strict_mode else threshold - self.evaluation_model = evaluation_model - self.include_reason = include_reason - self.async_mode = async_mode - self.strict_mode = strict_mode - - def measure(self, test_case: LLMTestCase): - try: - graph_context_recall_metric, graph_context_relevancy_metric = self.initialize_metrics() - # Remember, deepeval's default metrics follow the same pattern as your custom metric! - # relevancy_metric.measure(test_case) - graph_context_relevancy_metric.measure(test_case) - graph_context_recall_metric.measure(test_case) - - # Custom logic to set score, reason, and success - self.set_score_reason_success(graph_context_recall_metric, graph_context_relevancy_metric) - return self.score - except Exception as e: - # Set and re-raise error - self.error = str(e) - raise - - - def is_successful(self) -> bool: - if self.error is not None: - self.success = False - else: - return self.success - - @property - def __name__(self): - return "Composite Graph Context Metric" - - - ###################### - ### Helper methods ### - ###################### - def initialize_metrics(self): - graph_context_relevancy_metric = GraphContextualRelevancy( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - strict_mode=self.strict_mode - ) - - graph_context_recall_metric = GraphContextualRecall( - threshold=self.threshold, - model=self.evaluation_model, - include_reason=self.include_reason, - strict_mode=self.strict_mode - ) - - # relevancy_metric = AnswerRelevancyMetric( - # threshold=self.threshold, - # model=self.evaluation_model, - # include_reason=self.include_reason, - # async_mode=self.async_mode, - # strict_mode=self.strict_mode - # ) - # faithfulness_metric = FaithfulnessMetric( - # threshold=self.threshold, - # model=self.evaluation_model, - # include_reason=self.include_reason, - # async_mode=self.async_mode, - # strict_mode=self.strict_mode - # ) - return graph_context_recall_metric, graph_context_relevancy_metric - - def set_score_reason_success( - self, - graph_context_recall_metric: BaseMetric, - graph_context_relevancy_metric: BaseMetric, - ): - graph_context_recall_metric_score = graph_context_recall_metric.score - graph_context_recall_metric_reason = graph_context_recall_metric.reason - graph_context_relevancy_metric_score = graph_context_relevancy_metric.score - graph_context_relevancy_metric_reason = graph_context_relevancy_metric.reason - - # Custom logic to set score - composite_score = min(graph_context_recall_metric_score, graph_context_relevancy_metric_score) - self.score = 0 if self.strict_mode and composite_score < self.threshold else composite_score - # Custom logic to set reason - if self.include_reason: - self.reason = graph_context_recall_metric_reason + "\n" + graph_context_relevancy_metric_reason - # Custom logic to set success - self.success = self.score >= self.threshold - class GraphContextualRecall(BaseMetric): def __init__( self, @@ -135,21 +43,19 @@ def __init__( model: Optional[Union[str, DeepEvalBaseLLM]] = None, include_reason: bool = True, strict_mode: bool = False, - verbose_mode: bool = False, ): self.threshold = 1 if strict_mode else threshold self.model, self.using_native_model = initialize_model(model) self.evaluation_model = self.model.get_model_name() self.include_reason = include_reason self.strict_mode = strict_mode - self.verbose_mode = verbose_mode def measure( self, test_case: LLMTestCase, _show_indicator: bool = True, ) -> float: - check_llm_test_case_params(test_case, required_params, self) + check_llm_test_case_params(test_case, REQUIRED_PARAMS, self) self.evaluation_cost = 0 if self.using_native_model else None with metric_progress_indicator(self, _show_indicator=_show_indicator): @@ -338,14 +244,12 @@ def __init__( model: Optional[Union[str, DeepEvalBaseLLM]] = None, include_reason: bool = True, strict_mode: bool = False, - verbose_mode: bool = False, ): self.threshold = 1 if strict_mode else threshold self.model, self.using_native_model = initialize_model(model) self.evaluation_model = self.model.get_model_name() self.include_reason = include_reason self.strict_mode = strict_mode - self.verbose_mode = verbose_mode def measure( self, @@ -354,7 +258,7 @@ def measure( ) -> float: if isinstance(test_case, ConversationalTestCase): test_case = test_case.turns[0] - check_llm_test_case_params(test_case, required_params, self) + check_llm_test_case_params(test_case, REQUIRED_PARAMS, self) self.evaluation_cost = 0 if self.using_native_model else None with metric_progress_indicator(self, _show_indicator=_show_indicator): diff --git a/tests/test_rag.py b/tests/test_rag.py index de936587..866f4644 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -1,130 +1,207 @@ import os +import pytest import logging -import unittest import numpy as np from dotenv import load_dotenv from graphrag_sdk.entity import Entity -from graphrag_sdk.source import Source from deepeval.test_case import LLMTestCase from graphrag_sdk.relation import Relation from graphrag_sdk.ontology import Ontology from graphrag_sdk.models.litellm import LiteModel +from graphrag_sdk.source import Source_FromRawText from graphrag_sdk.attribute import Attribute, AttributeType +# Custom metrics of DeepEval +from graphrag_sdk.graph_metrics import GraphContextualRelevancy, GraphContextualRecall from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig -from graphrag_sdk.test_metrics import CombineMetrics -os.environ["DEEPEVAL_ENABLE_TELEMETRY"] = "NO" + load_dotenv() +TEST_FILE = "tests/data/madoff.txt" + +# Test queries and expected results +BENCHMARK = [ + { + "query": "How many actors acted in a movie?", + "expected": "Over than 10 actors acted in a movie." + }, + { + "query": "Which actors acted in a movie?", + "expected": "Joseph Scotto, Melony Feliciano, and Donna Pastorello acted in a movie." + }, + { + "query": "What is the role of Joseph Scotto in a movie?", + "expected": "Joseph Scotto played the role of Bernie Madoff in a movie." + }, + { + "query": "Did Donna Pastorello act in a movie?", + "expected": "Yes, Donna Pastorello acted in a movie as Eleanor Squillari." + }, + { + "query": "Who played the role of Mark Madoff in a movie?", + "expected": "Alex Olson played the role of Mark Madoff in a movie." + }, + { + "query": "Did Melony Feliciano have a named role in a movie?", + "expected": "No, Melony Feliciano acted as a background extra in a movie." + },] logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) -class TestKGLiteLLM(unittest.TestCase): + +@pytest.fixture +def movie_actor_ontology(): """ - Test Knowledge Graph + Create and return an ontology for movies and actors with the ACTED_IN relationship. """ - - @classmethod - def setUpClass(cls): - # Get the model name from the environment variable - model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash-exp") - - cls.ontology = Ontology() - - cls.ontology.add_entity( - Entity( - label="Actor", - attributes=[ - Attribute( - name="name", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) + ontology = Ontology() + + # Add Actor entity with name attribute + ontology.add_entity( + Entity( + label="Actor", + attributes=[ + Attribute( + name="name", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], ) - cls.ontology.add_entity( - Entity( - label="Movie", - attributes=[ - Attribute( - name="title", - attr_type=AttributeType.STRING, - unique=True, - required=True, - ), - ], - ) + ) + + # Add Movie entity with title attribute + ontology.add_entity( + Entity( + label="Movie", + attributes=[ + Attribute( + name="title", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], ) - cls.ontology.add_relation( - Relation( - label="ACTED_IN", - source="Actor", - target="Movie", - attributes=[ - Attribute( - name="role", - attr_type=AttributeType.STRING, - unique=False, - required=True, - ), - ], - ) + ) + + # Add ACTED_IN relation between Actor and Movie with role attribute + ontology.add_relation( + Relation( + label="ACTED_IN", + source="Actor", + target="Movie", + attributes=[ + Attribute( + name="role", + attr_type=AttributeType.STRING, + unique=False, + required=True, + ), + ], ) - cls.graph_name = model_name.split("/")[0] + ) + + return ontology - # Use the model name from the environment variable - model = LiteModel(model_name=model_name, generation_config=GenerativeModelConfig(temperature=0)) +@pytest.fixture +def knowledge_graph_setup(movie_actor_ontology): + """ + Sets up the knowledge graph using the provided ontology. + """ + # Get the model name from the environment variable, with a default + model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash") + graph_name = model_name.split("/")[0] + + # Configure the model with zero temperature for deterministic outputs + model = LiteModel( + model_name=model_name, + generation_config=GenerativeModelConfig(temperature=0) + ) + + # Initialize the knowledge graph with the model and ontology + kg = KnowledgeGraph( + name=graph_name, + ontology=movie_actor_ontology, + model_config=KnowledgeGraphModelConfig.with_model(model), + ) + + # URL for a movie on IMDB + with open(TEST_FILE) as f: + string = f.read() + + sources = [Source_FromRawText(string)] + + # Process the source to populate the knowledge graph + kg.process_sources(sources) + + return kg + + +@pytest.fixture +def delete_kg(): + """ + Returns a function that deletes a given knowledge graph. + """ + def cleanup(kg): + logger.info("Cleaning up test graph...") + kg.delete() + + return cleanup - cls.kg = KnowledgeGraph( - name=cls.graph_name, - ontology=cls.ontology, - model_config=KnowledgeGraphModelConfig.with_model(model), - ) - def test_llm(self): - url = "https://www.imdb.com/title/tt23732458/" - - sources = [Source(url)] - - self.kg.process_sources(sources) - inputs = [ - "How many actors acted in a movie?", - "Which actors acted in a movie?", - "What is the role of Joseph Scotto in a movie?", - "Did Donna Pastorello act in a movie?", - "Who played the role of Mark Madoff in a movie?", - "Did Melony Feliciano have a named role in a movie?", - ] - - expected_outputs = [ - "Over than 10 actors acted in a movie.", - "Joseph Scotto, Melony Feliciano, and Donna Pastorello acted in a movie", - "Joseph Scotto played the role of Bernie Madoff in a movie.", - "Yes, Donna Pastorello acted in a movie as Eleanor Squillari.", - "Alex Olson played the role of Mark Madoff in a movie.", - "No, Melony Feliciano acted as a background extra in a movie.", - ] - answer_combined_metric = CombineMetrics(threshold=0.5) +class TestGraphRAGPipeline: + """ + Test Knowledge Graph using LiteLLM for query processing and evaluation. + Tests the ability of the graph to answer questions based on processed sources. + """ + + def test_movie_actor_queries(self, knowledge_graph_setup, delete_kg): + """ + Test the knowledge graph's ability to answer questions about actors and movies. + """ + kg = knowledge_graph_setup + + # Configure evaluation metrics + relevancy_metric = GraphContextualRelevancy(threshold=0.5) + recall_metric = GraphContextualRecall(threshold=0.5) scores = [] - for input_text, expected_output in zip(inputs, expected_outputs): - chat = self.kg.chat_session() - answer = chat.send_message(input_text) + # Run each test case and evaluate metrics + for case in BENCHMARK: + chat = kg.chat_session() + answer = chat.send_message(case["query"]) + # Create a test case for evaluation test_case = LLMTestCase( - input=input_text, - actual_output=answer["response"], - retrieval_context=[answer["context"]], - context=[answer["context"]], - name="kg_rag_test", - expected_output=expected_output, - additional_metadata=answer["cypher"], + input=case["query"], + actual_output=answer["response"], + retrieval_context=[answer["context"]], + context=[answer["context"]], + name="knowledge_graph_test", + expected_output=case["expected"], + additional_metadata=answer["cypher"], ) - score = answer_combined_metric.measure(test_case) - scores.append(score) - - self.kg.delete() - assert np.mean(scores) >= 0.5 + + # Measure metrics + relevancy_score = relevancy_metric.measure(test_case) + recall_score = recall_metric.measure(test_case) + + # Calculate and store average score + combined_score = (relevancy_score + recall_score) / 2 + scores.append(combined_score) + + # Log results for debugging + logger.info(f"Query: {case['query']}") + logger.info(f"Response: {answer['response']}") + logger.info(f"Combined Score: {combined_score}") + + # Clean up by deleting the graph + delete_kg(kg) + + # Verify that the average score meets the threshold + average_score = np.mean(scores) + logger.info(f"Average Score: {average_score}") + assert average_score >= 0.5, f"Average score {average_score} is below threshold of 0.5" \ No newline at end of file From 6b1730678eda5b26a3f4c83e4abcc3c3dd598a73 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 10 Mar 2025 14:15:47 +0200 Subject: [PATCH 034/136] restore-req-file --- requirements.txt | 54 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 54 insertions(+) create mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 00000000..550d2e56 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,54 @@ +appnope==0.1.4 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and platform_system == "Darwin" +asttokens==2.4.1 ; python_version >= "3.9" and python_full_version < "4.0.0" +async-timeout==5.0.1 ; python_full_version >= "3.9.0" and python_full_version < "3.11.3" +backoff==2.2.1 ; python_full_version >= "3.9.0" and python_version < "4.0" +beautifulsoup4==4.12.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +bs4==0.0.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +certifi==2024.8.30 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +cffi==1.17.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" +charset-normalizer==3.4.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +colorama==0.4.6 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform == "win32" +comm==0.2.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +debugpy==1.8.8 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +decorator==5.1.1 ; python_version >= "3.9" and python_full_version < "4.0.0" +exceptiongroup==1.2.2 ; python_version >= "3.9" and python_version < "3.11" +executing==2.1.0 ; python_version >= "3.9" and python_full_version < "4.0.0" +falkordb==1.0.9 ; python_full_version >= "3.9.0" and python_version < "4.0" +fix-busted-json==0.0.18 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +idna==3.10 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +importlib-metadata==8.5.0 ; python_full_version >= "3.9.0" and python_version < "3.10" +ipykernel==6.29.5 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +ipython==8.18.1 ; python_version >= "3.9" and python_full_version < "4.0.0" +jedi==0.19.2 ; python_version >= "3.9" and python_full_version < "4.0.0" +jupyter-client==8.6.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +jupyter-core==5.7.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +matplotlib-inline==0.1.7 ; python_version >= "3.9" and python_full_version < "4.0.0" +nest-asyncio==1.6.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +packaging==24.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +parso==0.8.4 ; python_version >= "3.9" and python_full_version < "4.0.0" +pexpect==4.9.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" +platformdirs==4.3.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +prompt-toolkit==3.0.48 ; python_version >= "3.9" and python_full_version < "4.0.0" +psutil==6.1.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +ptyprocess==0.7.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" +pure-eval==0.2.3 ; python_version >= "3.9" and python_full_version < "4.0.0" +pycparser==2.22 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" +pygments==2.18.0 ; python_version >= "3.9" and python_full_version < "4.0.0" +pypdf==4.3.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +python-abc==0.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +python-dateutil==2.9.0.post0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +python-dotenv==1.0.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +pywin32==308 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_full_version >= "3.9.0" and python_full_version < "4.0.0" +pyzmq==26.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +ratelimit==2.2.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +redis==5.2.0 ; python_full_version >= "3.9.0" and python_version < "4.0" +requests==2.32.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +six==1.16.0 ; python_version >= "3.9" and python_full_version < "4.0.0" +soupsieve==2.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +stack-data==0.6.3 ; python_version >= "3.9" and python_full_version < "4.0.0" +tornado==6.4.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +traitlets==5.14.3 ; python_version >= "3.9" and python_full_version < "4.0.0" +typing-extensions==4.12.2 ; python_version >= "3.9" and python_full_version < "4.0.0" +urllib3==2.2.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" +wcwidth==0.2.13 ; python_version >= "3.9" and python_full_version < "4.0.0" +zipp==3.21.0 ; python_version >= "3.9" and python_version < "3.10" \ No newline at end of file From e1a19d9ed597c3c6f78aef098252105e66bfec0d Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 10 Mar 2025 14:37:54 +0200 Subject: [PATCH 035/136] update-docs --- graphrag_sdk/graph_metrics.py | 196 +++++++++++++++++++++++++++++++++- 1 file changed, 195 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/graph_metrics.py b/graphrag_sdk/graph_metrics.py index d023cba4..0d15e338 100644 --- a/graphrag_sdk/graph_metrics.py +++ b/graphrag_sdk/graph_metrics.py @@ -1,5 +1,5 @@ """ -Metrics for evaluating Knowledge Graph performance. +This module is based on DeepEval framwork and provides metrics for evaluating Knowledge Graph performance. This module provides two metrics: 1. GraphContextualRelevancy - Measures how relevant the retrieved context is to the input query @@ -37,6 +37,13 @@ class GraphContextualRecall(BaseMetric): + """ + Evaluates how well the expected output is supported by the retrieval context. + + A high score indicates that most sentences in the expected output + can be attributed to information in the context. + """ + def __init__( self, threshold: float = 0.5, @@ -44,6 +51,16 @@ def __init__( include_reason: bool = True, strict_mode: bool = False, ): + """ + Initialize the GraphContextualRecall metric. + + Args: + threshold: Minimum score to consider the test successful (0.0-1.0) + model: LLM to use for evaluation (string name or DeepEvalBaseLLM instance) + include_reason: Whether to generate a reason for the score + strict_mode: If True, requires perfect score to pass + verbose_mode: If True, includes detailed logs in the output + """ self.threshold = 1 if strict_mode else threshold self.model, self.using_native_model = initialize_model(model) self.evaluation_model = self.model.get_model_name() @@ -55,18 +72,33 @@ def measure( test_case: LLMTestCase, _show_indicator: bool = True, ) -> float: + """ + Measure the contextual recall score. + + Args: + test_case: The test case to evaluate + _show_indicator: Whether to show a progress indicator + + Returns: + The recall score (0.0-1.0) + """ + # Validate test case has required parameters check_llm_test_case_params(test_case, REQUIRED_PARAMS, self) self.evaluation_cost = 0 if self.using_native_model else None with metric_progress_indicator(self, _show_indicator=_show_indicator): + # Generate verdicts self.verdicts: List[ContextualRecallVerdict] = ( self._generate_verdicts( test_case.expected_output, test_case.retrieval_context, test_case.additional_metadata ) ) + + # Calculate the score and generate the reason self.score = self._calculate_score() self.reason = self._generate_reason(test_case.expected_output) self.success = self.score >= self.threshold + # Generate verbose logs self.verbose_logs = construct_verbose_logs( self, steps=[ @@ -78,9 +110,19 @@ def measure( return self.score def _generate_reason(self, expected_output: str): + """ + Generate a human-readable reason for the metric score. + + Args: + expected_output: The expected output to evaluate + + Returns: + A string explaining the score + """ if self.include_reason is False: return None + # Collect supportive and unsupportive reasons supportive_reasons = [] unsupportive_reasons = [] for verdict in self.verdicts: @@ -89,6 +131,7 @@ def _generate_reason(self, expected_output: str): else: unsupportive_reasons.append(verdict.reason) + # Generate the prompt for the reason prompt = GraphContextualRecallTemplate.generate_reason( expected_output=expected_output, supportive_reasons=supportive_reasons, @@ -96,6 +139,7 @@ def _generate_reason(self, expected_output: str): score=format(self.score, ".2f"), ) + # Generate the reason using the appropriate model if self.using_native_model: res, cost = self.model.generate(prompt) self.evaluation_cost += cost @@ -111,6 +155,12 @@ def _generate_reason(self, expected_output: str): return data["reason"] def _calculate_score(self): + """ + Calculate the recall score based on the verdicts. + + Returns: + A score between 0.0 and 1.0 + """ number_of_verdicts = len(self.verdicts) if number_of_verdicts == 0: return 0 @@ -121,11 +171,24 @@ def _calculate_score(self): justified_sentences += 1 score = justified_sentences / number_of_verdicts + + # In strict mode, return 0 if below threshold return 0 if self.strict_mode and score < self.threshold else score def _generate_verdicts( self, expected_output: str, retrieval_context: List[str], cypher_query: Optional[str] = None ) -> List[ContextualRecallVerdict]: + """ + Generate verdicts for each sentence in the expected output. + + Args: + expected_output: The expected output to evaluate + retrieval_context: List of retrieval contexts to check against + cypher_query: Optional Cypher query used to generate the context + + Returns: + List of ContextualRecallVerdict for each sentence + """ prompt = GraphContextualRecallTemplate.generate_verdicts( expected_output=expected_output, retrieval_context=retrieval_context, cypher_query=cypher_query ) @@ -151,6 +214,12 @@ def _generate_verdicts( return verdicts def is_successful(self) -> bool: + """ + Check if the metric meets the success threshold. + + Returns: + True if the score meets or exceeds the threshold, False otherwise + """ if self.error is not None: self.success = False else: @@ -165,10 +234,26 @@ def __name__(self): return "Graph Contextual Recall" class GraphContextualRecallTemplate: + """ + Template for generating prompts for the GraphContextualRecall metric. + """ + @staticmethod def generate_reason( expected_output, supportive_reasons, unsupportive_reasons, score ): + """ + Generate a prompt for generating a reason for the recall score. + + Args: + expected_output: The original expected output + supportive_reasons: List of supportive reasons for the score + unsupportive_reasons: List of unsupportive reasons for the score + score: The calculated recall score + + Returns: + A formatted prompt for generating the reason + """ return f""" Given the original expected output, a list of supportive reasons, and a list of unsupportive reasons (which is deduced directly from the 'expected output'), and a contextual recall score (closer to 1 the better), summarize a CONCISE reason for the score. A supportive reason is the reason why a certain sentence in the original expected output can be attributed to the node in the retrieval context. @@ -203,6 +288,17 @@ def generate_reason( @staticmethod def generate_verdicts(expected_output, retrieval_context, cypher_query): + """ + Generate a prompt for generating verdicts for the expected output. + + Args: + expected_output: The original expected output + retrieval_context: List of retrieval contexts to check against + cypher_query: Optional Cypher query used to generate the context + + Returns: + A formatted prompt for generating the verdicts + """ return f""" For EACH sentence in the given expected output below, determine whether the sentence can be attributed to the nodes of retrieval contexts (cypher query and its output). Please generate a list of JSON with two keys: `verdict` and `reason`. The `verdict` key should STRICTLY be either a 'yes' or 'no'. Answer 'yes' if the sentence can be attributed to any parts of the retrieval context (cypher query and its output), else answer 'no'. @@ -238,6 +334,13 @@ def generate_verdicts(expected_output, retrieval_context, cypher_query): """ class GraphContextualRelevancy(BaseMetric): + """ + Evaluates how relevant the retrieval context is to the input query. + + A high score indicates that most of the statements in the context + are relevant to answering the query. + """ + def __init__( self, threshold: float = 0.5, @@ -245,6 +348,16 @@ def __init__( include_reason: bool = True, strict_mode: bool = False, ): + """ + Initialize the GraphContextualRelevancy metric. + + Args: + threshold: Minimum score to consider the test successful (0.0-1.0) + model: LLM to use for evaluation (string name or DeepEvalBaseLLM instance) + include_reason: Whether to generate a reason for the score + strict_mode: If True, requires perfect score to pass + verbose_mode: If True, includes detailed logs in the output + """ self.threshold = 1 if strict_mode else threshold self.model, self.using_native_model = initialize_model(model) self.evaluation_model = self.model.get_model_name() @@ -256,19 +369,36 @@ def measure( test_case: Union[LLMTestCase, ConversationalTestCase], _show_indicator: bool = True, ) -> float: + """ + Measure the contextual relevancy score. + + Args: + test_case: The test case to evaluate + _show_indicator: Whether to show a progress indicator + + Returns: + The relevancy score (0.0-1.0) + """ + # Convert conversational test case to standard test case if needed if isinstance(test_case, ConversationalTestCase): test_case = test_case.turns[0] + + # Validate test case has required parameters check_llm_test_case_params(test_case, REQUIRED_PARAMS, self) + # Initialize cost tracking for native models self.evaluation_cost = 0 if self.using_native_model else None with metric_progress_indicator(self, _show_indicator=_show_indicator): + # Generate verdicts for each context self.verdicts_list: List[ContextualRelevancyVerdicts] = [ (self._generate_verdicts(test_case.input, context, test_case.additional_metadata)) for context in test_case.retrieval_context ] + # Calculate the score and generate the reason self.score = self._calculate_score() self.reason = self._generate_reason(test_case.input) self.success = self.score >= self.threshold + # Generate verbose logs self.verbose_logs = construct_verbose_logs( self, steps=[ @@ -280,9 +410,19 @@ def measure( return self.score def _generate_reason(self, input: str): + """ + Generate a human-readable reason for the metric score. + + Args: + input_query: The original input query + + Returns: + A string explaining the score + """ if self.include_reason is False: return None + # Collect irrelevant and relevant statements irrelevancies = [] relevant_statements = [] for verdicts in self.verdicts_list: @@ -292,12 +432,15 @@ def _generate_reason(self, input: str): else: relevant_statements.append(verdict.statement) + # Generate the prompt for the reason prompt: dict = GraphContextualRelevancyTemplate.generate_reason( input=input, irrelevancies=irrelevancies, relevant_statements=relevant_statements, score=format(self.score, ".2f"), ) + + # Generate the reason using the appropriate model if self.using_native_model: res, cost = self.model.generate(prompt) self.evaluation_cost += cost @@ -313,6 +456,12 @@ def _generate_reason(self, input: str): return data["reason"] def _calculate_score(self): + """ + Calculate the relevancy score based on the verdicts. + + Returns: + A score between 0.0 and 1.0 + """ total_verdicts = 0 relevant_statements = 0 for verdicts in self.verdicts_list: @@ -325,11 +474,24 @@ def _calculate_score(self): return 0 score = relevant_statements / total_verdicts + + # In strict mode, return 0 if below threshold return 0 if self.strict_mode and score < self.threshold else score def _generate_verdicts( self, input: str, context: str, cypher_query: Optional[str] = None ) -> ContextualRelevancyVerdicts: + """ + Generate verdicts for a single context. + + Args: + input_query: The original input query + context: The retrieval context to evaluate + cypher_query: Optional Cypher query used to generate the context + + Returns: + ContextualRelevancyVerdicts containing verdicts for each statement + """ prompt = GraphContextualRelevancyTemplate.generate_verdicts( input=input, context=context, cypher_query=cypher_query ) @@ -350,6 +512,12 @@ def _generate_verdicts( return ContextualRelevancyVerdicts(**data) def is_successful(self) -> bool: + """ + Check if the metric meets the success threshold. + + Returns: + True if the score meets or exceeds the threshold, False otherwise + """ if self.error is not None: self.success = False else: @@ -364,6 +532,9 @@ def __name__(self): return "Graph Contextual Relevancy" class GraphContextualRelevancyTemplate: + """ + Template for generating prompts for the GraphContextualRelevancy metric. + """ @staticmethod def generate_reason( input: str, @@ -371,6 +542,18 @@ def generate_reason( relevant_statements: List[str], score: float, ): + """ + Generate a prompt for generating a reason for the relevancy score. + + Args: + input: The original input query + irrelevancies: List of irrelevant statements in the context + relevant_statements: List of relevant statements in the context + score: The calculated relevancy score + + Returns: + A formatted prompt for generating the reason + """ return f"""Based on the given input, reasons for why the retrieval context is irrelevant to the input, the statements in the retrieval context that is actually relevant to the retrieval context, and the contextual relevancy score (the closer to 1 the better), please generate a CONCISE reason for the score. In your reason, you should quote data provided in the reasons for irrelevancy and relevant statements to support your point. @@ -402,6 +585,17 @@ def generate_reason( @staticmethod def generate_verdicts(input: str, context: str, cypher_query: Optional[str] = None): + """ + Generate a prompt for generating verdicts for the context. + + Args: + input: The original input query + context: The retrieval context to evaluate + cypher_query: Optional Cypher query used to generate the context + + Returns: + A formatted prompt for generating the verdicts + """ return f"""Based on the input and context (cypher and query output), please generate a JSON object to indicate whether each statement found in the context is relevant to the provided input. The JSON will be a list of 'verdicts', with 2 mandatory fields: 'verdict' and 'statement', and 1 optional field: 'reason'. You should first extract statements found in the context, which are high level information found in the context, before deciding on a verdict and optionally a reason for each statement. The 'verdict' key should STRICTLY be either 'yes' or 'no', and states whether the statement is relevant to the input. From 8a1f2c2730deada68083e3725c675c6e2ae5c8d8 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 24 Mar 2025 15:43:59 +0200 Subject: [PATCH 036/136] add-streaming --- graphrag_sdk/chat_session.py | 71 ++++++++++++++++++++++++++++ graphrag_sdk/models/litellm.py | 38 ++++++++++++++- graphrag_sdk/steps/qa_step.py | 2 +- graphrag_sdk/steps/stream_qa_step.py | 50 ++++++++++++++++++++ 4 files changed, 159 insertions(+), 2 deletions(-) create mode 100644 graphrag_sdk/steps/stream_qa_step.py diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index e013cdee..3f8c86b2 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -1,7 +1,9 @@ import json from falkordb import Graph +from typing import Iterator from graphrag_sdk.ontology import Ontology from graphrag_sdk.steps.qa_step import QAStep +from graphrag_sdk.steps.stream_qa_step import StreamingQAStep from graphrag_sdk.model_config import KnowledgeGraphModelConfig from graphrag_sdk.steps.graph_query_step import GraphQueryGenerationStep @@ -63,6 +65,12 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, qa_system_instruction ) self.last_answer = None + self.last_complete_response = { + "question": None, + "response": None, + "context": None, + "cypher": None + } def send_message(self, message: str) -> dict: """ @@ -111,7 +119,70 @@ def send_message(self, message: str) -> dict: "context": context, "cypher": cypher } + + def send_message_stream(self, message: str) -> Iterator[str]: + + """ + Sends a message to the chat session and streams the response. + + Args: + message (str): The message to send. + + Yields: + str: Chunks of the response as they're generated. + + Returns: + Generator that produces the response in chunks and implicitly builds a dictionary + with the complete response data in the following format: + {"question": message, + "response": answer, + "context": context, + "cypher": cypher} + """ + cypher_step = GraphQueryGenerationStep( + graph=self.graph, + chat_session=self.cypher_chat_session, + ontology=self.ontology, + last_answer=self.last_answer, + cypher_prompt=self.cypher_prompt, + cypher_prompt_with_history=self.cypher_prompt_with_history + ) + + (context, cypher) = cypher_step.run(message) + + if not cypher or len(cypher) == 0: + # Stream the error message for consistency with successful responses + error_message = "I am sorry, I could not find the answer to your question" + yield error_message + + self.last_complete_response = { + "question": message, + "response": error_message, + "context": None, + "cypher": None + } + return + + qa_step = StreamingQAStep( + chat_session=self.qa_chat_session, + qa_prompt=self.qa_prompt, + ) + + # Only accumulate chunks if needed for post-processing + # Otherwise, simply yield them directly + for chunk in qa_step.run(message, cypher, context): + yield chunk + + # Set the last answer using chat history to ensure we have the complete response + self.last_answer = qa_step.chat_session.get_chat_history()[-1]['content'] + self.last_complete_response = { + "question": message, + "response": self.last_answer, + "context": context, + "cypher": cypher + } + def clean_ontology_for_prompt(self, ontology: dict) -> str: """ Cleans the ontology by removing 'unique' and 'required' keys and prepares it for use in a prompt. diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 324bbf06..4f5bcc21 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -1,6 +1,6 @@ import logging from ollama import Client -from typing import Optional +from typing import Optional, Iterator from litellm import completion, validate_environment, utils as litellm_utils from .model import ( OutputMethod, @@ -216,6 +216,42 @@ def send_message(self, message: str, output_method: OutputMethod = OutputMethod. self._chat_history.append({"role": "assistant", "content": content.text}) return content + def send_message_stream(self, message: str) -> Iterator[str]: + """ + Send a message and receive the response in a streaming fashion. + + Args: + message (str): The message to send. + + Yields: + str: Streamed chunks of the model's response. + """ + generation_config = self._adjust_generation_config(OutputMethod.DEFAULT) + self._chat_history.append({"role": "user", "content": message}) + + try: + response_stream = completion( + model=self._model.model, + messages=self._chat_history, + stream=True, # Enable streaming mode + **generation_config + ) + + chunks = [] + for chunk in response_stream: + if "choices" in chunk and chunk["choices"]: + content = chunk["choices"][0].get("delta", {}).get("content", "") + if content: + chunks.append(content) + yield content # Yield streamed response chunks + + # Save the final response to chat history + full_response = "".join(chunks) # Collect full response + self._chat_history.append({"role": "assistant", "content": full_response}) + + except Exception as e: + raise ValueError(f"Error during streaming request, check credentials - {e}") + def _adjust_generation_config(self, output_method: OutputMethod): """ Adjust the generation configuration based on the specified output method. diff --git a/graphrag_sdk/steps/qa_step.py b/graphrag_sdk/steps/qa_step.py index 67d452b7..bf25e5c8 100644 --- a/graphrag_sdk/steps/qa_step.py +++ b/graphrag_sdk/steps/qa_step.py @@ -24,7 +24,7 @@ def __init__( Args: chat_session (GenerativeModelChatSession): The chat session for handling the QA. config (Optional[dict]): Optional configuration for the step. - qa_prompt (Optional[str]): The prompt for the + qa_prompt (Optional[str]): The prompt template for question answering. """ self.config = config or {} self.chat_session = chat_session diff --git a/graphrag_sdk/steps/stream_qa_step.py b/graphrag_sdk/steps/stream_qa_step.py new file mode 100644 index 00000000..8ed3d2cc --- /dev/null +++ b/graphrag_sdk/steps/stream_qa_step.py @@ -0,0 +1,50 @@ +import logging +from typing import Optional, Iterator +from graphrag_sdk.steps.Step import Step +from graphrag_sdk.models import GenerativeModelChatSession + + +logger = logging.getLogger(__name__) +logger.setLevel(logging.DEBUG) + +class StreamingQAStep(Step): + """ + QA Step that supports streaming responses + """ + + def __init__( + self, + chat_session: GenerativeModelChatSession, + config: Optional[dict] = None, + qa_prompt: Optional[str] = None, + ) -> None: + """ + Initialize the QA Step. + + Args: + chat_session (GenerativeModelChatSession): The chat session for handling the QA. + config (Optional[dict]): Optional configuration for the step. + qa_prompt (Optional[str]): The prompt template for question answering. + """ + self.config = config or {} + self.chat_session = chat_session + self.qa_prompt = qa_prompt + + def run(self, question: str, cypher: str, context: str) -> Iterator[str]: + """ + Run the QA step and stream the response chunks. + + Args: + question (str): The question being asked. + cypher (str): The Cypher query to run. + context (str): Context for the QA. + + Returns: + Iterator[str]: A generator that yields response chunks. + """ + qa_prompt = self.qa_prompt.format( + context=context, cypher=cypher, question=question + ) + logger.debug(f"QA Prompt: {qa_prompt}") + for chunk in self.chat_session.send_message_stream(qa_prompt): + yield chunk \ No newline at end of file From 1e77997ffde0d4f9bc03897ef144603ed3ec6873 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 24 Mar 2025 16:03:22 +0200 Subject: [PATCH 037/136] generic-to-models --- graphrag_sdk/chat_session.py | 6 +++--- graphrag_sdk/models/model.py | 5 ++++- graphrag_sdk/steps/stream_qa_step.py | 1 + 3 files changed, 8 insertions(+), 4 deletions(-) diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index 3f8c86b2..8b3ce6e0 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -155,9 +155,10 @@ def send_message_stream(self, message: str) -> Iterator[str]: error_message = "I am sorry, I could not find the answer to your question" yield error_message + self.last_answer = error_message self.last_complete_response = { "question": message, - "response": error_message, + "response": self.last_answer, "context": None, "cypher": None } @@ -168,8 +169,7 @@ def send_message_stream(self, message: str) -> Iterator[str]: qa_prompt=self.qa_prompt, ) - # Only accumulate chunks if needed for post-processing - # Otherwise, simply yield them directly + # Yield chunks of the response as they're generated for chunk in qa_step.run(message, cypher, context): yield chunk diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index a7b87c29..fb5989ca 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -1,6 +1,6 @@ from enum import Enum -from typing import Optional from abc import ABC, abstractmethod +from typing import Optional, Iterator class FinishReason: @@ -100,6 +100,9 @@ def __init__(self, model: "GenerativeModel"): def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: pass + def send_message_stream(self, message: str) -> Iterator[str]: + raise NotImplementedError("Streaming not supported by this API implementation.") + class GenerativeModel(ABC): """ diff --git a/graphrag_sdk/steps/stream_qa_step.py b/graphrag_sdk/steps/stream_qa_step.py index 8ed3d2cc..ab2d2bae 100644 --- a/graphrag_sdk/steps/stream_qa_step.py +++ b/graphrag_sdk/steps/stream_qa_step.py @@ -46,5 +46,6 @@ def run(self, question: str, cypher: str, context: str) -> Iterator[str]: context=context, cypher=cypher, question=question ) logger.debug(f"QA Prompt: {qa_prompt}") + # Send the message and stream the response for chunk in self.chat_session.send_message_stream(qa_prompt): yield chunk \ No newline at end of file From 1b7657776253398e79deaa13baa008a2f6eaa9b4 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 24 Mar 2025 16:35:19 +0200 Subject: [PATCH 038/136] test-streaming --- tests/test_streaming.py | 182 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 182 insertions(+) create mode 100644 tests/test_streaming.py diff --git a/tests/test_streaming.py b/tests/test_streaming.py new file mode 100644 index 00000000..752d2151 --- /dev/null +++ b/tests/test_streaming.py @@ -0,0 +1,182 @@ +import os +import pytest +import logging +import numpy as np +from dotenv import load_dotenv +from graphrag_sdk.entity import Entity +from deepeval.test_case import LLMTestCase +from graphrag_sdk.relation import Relation +from graphrag_sdk.ontology import Ontology +from graphrag_sdk.models.litellm import LiteModel +from graphrag_sdk.source import Source_FromRawText +from graphrag_sdk.attribute import Attribute, AttributeType +# Custom metrics of DeepEval +from graphrag_sdk.graph_metrics import GraphContextualRelevancy, GraphContextualRecall +from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig, GenerativeModelConfig + + +load_dotenv() +TEST_FILE = "tests/data/madoff.txt" + +# Test case +USECASE = { + "query": "How many actors acted in a movie?\nPlease give me full details of the actors with a long output.", + "expected": "Over than 10 actors acted in a movie." + } + +logging.basicConfig(level=logging.DEBUG) +logger = logging.getLogger(__name__) + + +@pytest.fixture +def movie_actor_ontology(): + """ + Create and return an ontology for movies and actors with the ACTED_IN relationship. + """ + ontology = Ontology() + + # Add Actor entity with name attribute + ontology.add_entity( + Entity( + label="Actor", + attributes=[ + Attribute( + name="name", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], + ) + ) + + # Add Movie entity with title attribute + ontology.add_entity( + Entity( + label="Movie", + attributes=[ + Attribute( + name="title", + attr_type=AttributeType.STRING, + unique=True, + required=True, + ), + ], + ) + ) + + # Add ACTED_IN relation between Actor and Movie with role attribute + ontology.add_relation( + Relation( + label="ACTED_IN", + source="Actor", + target="Movie", + attributes=[ + Attribute( + name="role", + attr_type=AttributeType.STRING, + unique=False, + required=True, + ), + ], + ) + ) + + return ontology + + +@pytest.fixture +def knowledge_graph_setup(movie_actor_ontology): + """ + Sets up the knowledge graph using the provided ontology. + """ + # Get the model name from the environment variable, with a default + model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash") + graph_name = model_name.split("/")[0] + + # Configure the model with zero temperature for deterministic outputs + model = LiteModel( + model_name=model_name, + generation_config=GenerativeModelConfig(temperature=0) + ) + + # Initialize the knowledge graph with the model and ontology + kg = KnowledgeGraph( + name=graph_name, + ontology=movie_actor_ontology, + model_config=KnowledgeGraphModelConfig.with_model(model), + ) + + # URL for a movie on IMDB + with open(TEST_FILE) as f: + string = f.read() + + sources = [Source_FromRawText(string)] + + # Process the source to populate the knowledge graph + kg.process_sources(sources) + + return kg + + +@pytest.fixture +def delete_kg(): + """ + Returns a function that deletes a given knowledge graph. + """ + def cleanup(kg): + logger.info("Cleaning up test graph...") + kg.delete() + + return cleanup + + +class TestStreamingResponse: + """ + Test the knowledge graph's ability to answer questions about actors and movies. + Test the streaming response of the knowledge graph. + """ + + def test_streaming(self, knowledge_graph_setup, delete_kg): + """ + Test the knowledge graph's ability to answer questions about actors and movies with streaming response. + """ + kg = knowledge_graph_setup + + # Configure evaluation metrics + relevancy_metric = GraphContextualRelevancy(threshold=0.5) + recall_metric = GraphContextualRecall(threshold=0.5) + + chat = kg.chat_session() + answer = chat.send_message(USECASE["query"]) + # Stream the response evaluation + for chunk in chat.send_message_stream(USECASE["query"]): + logger.info(chunk) + answer = chat.last_complete_response + # Create a test case for evaluation + test_case = LLMTestCase( + input=USECASE["query"], + actual_output=answer["response"], + retrieval_context=[answer["context"]], + context=[answer["context"]], + name="knowledge_graph_test", + expected_output=USECASE["expected"], + additional_metadata=answer["cypher"], + ) + + # Measure metrics + relevancy_score = relevancy_metric.measure(test_case) + recall_score = recall_metric.measure(test_case) + + # Calculate and store average score + combined_score = (relevancy_score + recall_score) / 2 + + # Log results for debugging + logger.info(f"Query: {USECASE['query']}") + logger.info(f"Response: {answer['response']}") + logger.info(f"Combined Score: {combined_score}") + + # Clean up by deleting the graph + delete_kg(kg) + + assert combined_score >= 0.5, f"Average score {combined_score} is below threshold of 0.5" \ No newline at end of file From 42fd040a19b7bb6d13d61073bb4cffbce8b3a58b Mon Sep 17 00:00:00 2001 From: Matan Broit Date: Mon, 31 Mar 2025 13:22:05 +0300 Subject: [PATCH 039/136] added chat metadata field and return query execition time on send_message --- graphrag_sdk/chat_session.py | 6 ++++-- graphrag_sdk/steps/graph_query_step.py | 6 ++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index e013cdee..df5f0bb6 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -63,6 +63,8 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, qa_system_instruction ) self.last_answer = None + #Statistics + self.metadata = {"last_query_execution_time": None} def send_message(self, message: str) -> dict: """ @@ -87,8 +89,8 @@ def send_message(self, message: str) -> dict: cypher_prompt_with_history=self.cypher_prompt_with_history ) - (context, cypher) = cypher_step.run(message) - + (context, cypher, query_execution_time) = cypher_step.run(message) + self.metadata["last_query_execution_time"] = query_execution_time if not cypher or len(cypher) == 0: return { "question": message, diff --git a/graphrag_sdk/steps/graph_query_step.py b/graphrag_sdk/steps/graph_query_step.py index 0edffb22..213297ae 100644 --- a/graphrag_sdk/steps/graph_query_step.py +++ b/graphrag_sdk/steps/graph_query_step.py @@ -86,13 +86,15 @@ def run(self, question: str, retries: Optional[int] = 10): raise Exception("\n".join(validation_errors)) if cypher is not None: - result_set = self.graph.query(cypher).result_set + query_result = self.graph.query(cypher) + result_set = query_result.result_set + execution_time = query_result.run_time_ms context = stringify_falkordb_response(result_set) logger.debug(f"Context: {context}") logger.debug(f"Context size: {len(result_set)}") logger.debug(f"Context characters: {len(str(context))}") - return (context, cypher) + return (context, cypher, execution_time) except Exception as e: logger.debug(f"Error: {e}") error = e From f0870b394d6d3f37c3d680f60167e4c54c6c14c0 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 14:19:39 +0300 Subject: [PATCH 040/136] reduce-code-duplication --- graphrag_sdk/chat_session.py | 83 +++++++++---------- ...treaming.py => test_streaming_response.py} | 1 - 2 files changed, 38 insertions(+), 46 deletions(-) rename tests/{test_streaming.py => test_streaming_response.py} (99%) diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index 8b3ce6e0..4340e99d 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -64,14 +64,35 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, self.qa_chat_session = model_config.qa.start_chat( qa_system_instruction ) - self.last_answer = None self.last_complete_response = { "question": None, "response": None, "context": None, "cypher": None } + self.cypher_error_message = "I am sorry, I could not find the answer to your question" + + def _generate_cypher_query(self, message: str) -> tuple: + """ + Generate a Cypher query for the given message. + + Args: + message (str): The message to generate a query for. + + Returns: + tuple: A tuple containing (context, cypher) + """ + cypher_step = GraphQueryGenerationStep( + graph=self.graph, + chat_session=self.cypher_chat_session, + ontology=self.ontology, + last_answer=self.last_complete_response["response"], + cypher_prompt=self.cypher_prompt, + cypher_prompt_with_history=self.cypher_prompt_with_history + ) + return cypher_step.run(message) + def send_message(self, message: str) -> dict: """ Sends a message to the chat session. @@ -86,39 +107,32 @@ def send_message(self, message: str) -> dict: "context": context, "cypher": cypher} """ - cypher_step = GraphQueryGenerationStep( - graph=self.graph, - chat_session=self.cypher_chat_session, - ontology=self.ontology, - last_answer=self.last_answer, - cypher_prompt=self.cypher_prompt, - cypher_prompt_with_history=self.cypher_prompt_with_history - ) - - (context, cypher) = cypher_step.run(message) + (context, cypher) = self._generate_cypher_query(message) if not cypher or len(cypher) == 0: - return { + self.last_complete_response = { "question": message, - "response": "I am sorry, I could not find the answer to your question", + "response": self.cypher_error_message, "context": None, "cypher": None - } - + } + return self.last_complete_response + qa_step = QAStep( chat_session=self.qa_chat_session, qa_prompt=self.qa_prompt, ) answer = qa_step.run(message, cypher, context) - self.last_answer = answer - - return { + + self.last_complete_response = { "question": message, "response": answer, "context": context, "cypher": cypher - } + } + + return self.last_complete_response def send_message_stream(self, message: str) -> Iterator[str]: @@ -130,35 +144,16 @@ def send_message_stream(self, message: str) -> Iterator[str]: Yields: str: Chunks of the response as they're generated. - - Returns: - Generator that produces the response in chunks and implicitly builds a dictionary - with the complete response data in the following format: - {"question": message, - "response": answer, - "context": context, - "cypher": cypher} """ - cypher_step = GraphQueryGenerationStep( - graph=self.graph, - chat_session=self.cypher_chat_session, - ontology=self.ontology, - last_answer=self.last_answer, - cypher_prompt=self.cypher_prompt, - cypher_prompt_with_history=self.cypher_prompt_with_history - ) - - (context, cypher) = cypher_step.run(message) + (context, cypher) = self._generate_cypher_query(message) if not cypher or len(cypher) == 0: # Stream the error message for consistency with successful responses - error_message = "I am sorry, I could not find the answer to your question" - yield error_message + yield self.cypher_error_message - self.last_answer = error_message self.last_complete_response = { "question": message, - "response": self.last_answer, + "response": self.cypher_error_message, "context": None, "cypher": None } @@ -174,15 +169,13 @@ def send_message_stream(self, message: str) -> Iterator[str]: yield chunk # Set the last answer using chat history to ensure we have the complete response - self.last_answer = qa_step.chat_session.get_chat_history()[-1]['content'] - self.last_complete_response = { "question": message, - "response": self.last_answer, + "response": qa_step.chat_session.get_chat_history()[-1]['content'], "context": context, "cypher": cypher } - + def clean_ontology_for_prompt(self, ontology: dict) -> str: """ Cleans the ontology by removing 'unique' and 'required' keys and prepares it for use in a prompt. diff --git a/tests/test_streaming.py b/tests/test_streaming_response.py similarity index 99% rename from tests/test_streaming.py rename to tests/test_streaming_response.py index 752d2151..f8150e75 100644 --- a/tests/test_streaming.py +++ b/tests/test_streaming_response.py @@ -1,7 +1,6 @@ import os import pytest import logging -import numpy as np from dotenv import load_dotenv from graphrag_sdk.entity import Entity from deepeval.test_case import LLMTestCase From c4ae0df029938aa2cd988cfbdf0031c2cd544b08 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 14:25:49 +0300 Subject: [PATCH 041/136] glob-var --- graphrag_sdk/chat_session.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/graphrag_sdk/chat_session.py b/graphrag_sdk/chat_session.py index 4340e99d..c0da97fa 100644 --- a/graphrag_sdk/chat_session.py +++ b/graphrag_sdk/chat_session.py @@ -7,6 +7,7 @@ from graphrag_sdk.model_config import KnowledgeGraphModelConfig from graphrag_sdk.steps.graph_query_step import GraphQueryGenerationStep +CYPHER_ERROR_RES = "Sorry, I could not find the answer to your question" class ChatSession: """ @@ -70,7 +71,6 @@ def __init__(self, model_config: KnowledgeGraphModelConfig, ontology: Ontology, "context": None, "cypher": None } - self.cypher_error_message = "I am sorry, I could not find the answer to your question" def _generate_cypher_query(self, message: str) -> tuple: """ @@ -112,7 +112,7 @@ def send_message(self, message: str) -> dict: if not cypher or len(cypher) == 0: self.last_complete_response = { "question": message, - "response": self.cypher_error_message, + "response": CYPHER_ERROR_RES, "context": None, "cypher": None } @@ -149,11 +149,11 @@ def send_message_stream(self, message: str) -> Iterator[str]: if not cypher or len(cypher) == 0: # Stream the error message for consistency with successful responses - yield self.cypher_error_message + yield CYPHER_ERROR_RES self.last_complete_response = { "question": message, - "response": self.cypher_error_message, + "response": CYPHER_ERROR_RES, "context": None, "cypher": None } From ea7178275073107e452b1b5416486174fb597f70 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 14:41:01 +0300 Subject: [PATCH 042/136] fix-comments --- graphrag_sdk/models/litellm.py | 16 +++++++++------- tests/test_streaming_response.py | 28 +++++++++++++++++++--------- 2 files changed, 28 insertions(+), 16 deletions(-) diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 4f5bcc21..a762c989 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -239,18 +239,20 @@ def send_message_stream(self, message: str) -> Iterator[str]: chunks = [] for chunk in response_stream: - if "choices" in chunk and chunk["choices"]: - content = chunk["choices"][0].get("delta", {}).get("content", "") - if content: - chunks.append(content) - yield content # Yield streamed response chunks - + if not chunk or "choices" not in chunk or not chunk["choices"]: + continue # Skip empty or malformed chunks + + content = chunk["choices"][0].get("delta", {}).get("content", "") + if content: + chunks.append(content) + yield content # Yield streamed response chunks + # Save the final response to chat history full_response = "".join(chunks) # Collect full response self._chat_history.append({"role": "assistant", "content": full_response}) except Exception as e: - raise ValueError(f"Error during streaming request, check credentials - {e}") + raise ValueError(f"Error during streaming request, check credentials - {e}") from e def _adjust_generation_config(self, output_method: OutputMethod): """ diff --git a/tests/test_streaming_response.py b/tests/test_streaming_response.py index f8150e75..f86ef354 100644 --- a/tests/test_streaming_response.py +++ b/tests/test_streaming_response.py @@ -20,7 +20,7 @@ # Test case USECASE = { "query": "How many actors acted in a movie?\nPlease give me full details of the actors with a long output.", - "expected": "Over than 10 actors acted in a movie." + "expected": "More than 10 actors acted in a movie." } logging.basicConfig(level=logging.DEBUG) @@ -147,20 +147,30 @@ def test_streaming(self, knowledge_graph_setup, delete_kg): recall_metric = GraphContextualRecall(threshold=0.5) chat = kg.chat_session() - answer = chat.send_message(USECASE["query"]) - # Stream the response evaluation + # Track that we received multiple chunks to verify streaming + received_chunks = [] for chunk in chat.send_message_stream(USECASE["query"]): logger.info(chunk) - answer = chat.last_complete_response + received_chunks.append(chunk) + + # Verify that streaming actually occurred (received multiple chunks) + assert len(received_chunks) > 1, "Expected multiple chunks in streaming response" + + # Get the last complete response for the cypher and context + response_dict = chat.last_complete_response + answer = ' '.join(received_chunks) + + assert answer.strip() == response_dict["response"].strip(), "Combined chunks (using join) should match last complete response" + # Create a test case for evaluation test_case = LLMTestCase( input=USECASE["query"], - actual_output=answer["response"], - retrieval_context=[answer["context"]], - context=[answer["context"]], - name="knowledge_graph_test", + actual_output=answer, + retrieval_context=[response_dict["context"]], + context=[response_dict["context"]], + name="streaming_test", expected_output=USECASE["expected"], - additional_metadata=answer["cypher"], + additional_metadata=response_dict["cypher"], ) # Measure metrics From 5722fa79e2cce64abfc21eb112eeafc94b46d91a Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 14:51:36 +0300 Subject: [PATCH 043/136] fix-test --- tests/test_streaming_response.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_streaming_response.py b/tests/test_streaming_response.py index f86ef354..0aac9657 100644 --- a/tests/test_streaming_response.py +++ b/tests/test_streaming_response.py @@ -158,7 +158,7 @@ def test_streaming(self, knowledge_graph_setup, delete_kg): # Get the last complete response for the cypher and context response_dict = chat.last_complete_response - answer = ' '.join(received_chunks) + answer = ''.join(received_chunks) assert answer.strip() == response_dict["response"].strip(), "Combined chunks (using join) should match last complete response" @@ -182,7 +182,7 @@ def test_streaming(self, knowledge_graph_setup, delete_kg): # Log results for debugging logger.info(f"Query: {USECASE['query']}") - logger.info(f"Response: {answer['response']}") + logger.info(f"Response: {answer}") logger.info(f"Combined Score: {combined_score}") # Clean up by deleting the graph From 4f010243fd1474e002510f596889c629614d9cd8 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 15:59:31 +0300 Subject: [PATCH 044/136] cypher-gen-fixes --- graphrag_sdk/steps/graph_query_step.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/graphrag_sdk/steps/graph_query_step.py b/graphrag_sdk/steps/graph_query_step.py index 213297ae..e77da058 100644 --- a/graphrag_sdk/steps/graph_query_step.py +++ b/graphrag_sdk/steps/graph_query_step.py @@ -51,7 +51,7 @@ def __init__( self.cypher_prompt = cypher_prompt self.cypher_prompt_with_history = cypher_prompt_with_history - def run(self, question: str, retries: Optional[int] = 10): + def run(self, question: str, retries: Optional[int] = 10) -> tuple[Optional[str], Optional[str], Optional[int]]: """ Run the step to generate and validate a Cypher query. @@ -60,7 +60,7 @@ def run(self, question: str, retries: Optional[int] = 10): retries (Optional[int]): Number of retries allowed in case of errors. Returns: - tuple[Optional[str], Optional[str]]: The context and the generated Cypher query. + tuple[Optional[str], Optional[str], Optional[int]]: The context, the generated Cypher query and the query execution time. """ cypher = "" for i in range(retries): @@ -79,7 +79,7 @@ def run(self, question: str, retries: Optional[int] = 10): logger.debug(f"Cypher: {cypher}") if not cypher or len(cypher) == 0: - return (None, None) + return (None, None, None) validation_errors = validate_cypher(cypher, self.ontology) if validation_errors is not None: @@ -94,7 +94,7 @@ def run(self, question: str, retries: Optional[int] = 10): logger.debug(f"Context size: {len(result_set)}") logger.debug(f"Context characters: {len(str(context))}") - return (context, cypher, execution_time) + return (context, cypher, execution_time) except Exception as e: logger.debug(f"Error: {e}") error = e From 4dda290e72f22569e23629a6598d04f5baa43373 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 31 Mar 2025 16:14:50 +0300 Subject: [PATCH 045/136] v0.7.0 --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 05c44989..e0905b06 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "graphrag_sdk" -version = "0.6.2" +version = "0.7.0" license = "MIT" description = "Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] From eb64efeb7a1598adc95d336b530abb3c081e05f6 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 11:44:42 +0300 Subject: [PATCH 046/136] move-eval-dev --- pyproject.toml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index e0905b06..7d58be21 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,7 +23,6 @@ python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" rich = "^13.9.4" ipykernel = "^6.29.5" -deepeval = "^2.2.6" vertexai = { version = "^1.49.0", optional = true } ollama = { version = "^0.2.1", optional = true } openai = { version = "^1.35.9", optional = true } @@ -46,6 +45,8 @@ sphinx = "^7.3.7" sphinx-rtd-theme = "^2.0.0" pandas = "^2.2.2" jupyter = "^1.0.0" +deepeval = "^2.2.6" + [build-system] requires = ["poetry-core"] From 0cfb3c07d9f2446e76360b10dcd2d5fd64e076d8 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 11:46:12 +0300 Subject: [PATCH 047/136] bump-ver --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 7d58be21..e735c733 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "graphrag_sdk" -version = "0.7.0" +version = "0.7.1" license = "MIT" description = "Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] From bfa76a21858a7313c3b8f28fae5b832060063776 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 11:51:25 +0300 Subject: [PATCH 048/136] fix-lock --- .github/workflows/test.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index bb158471..7cead062 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -60,6 +60,9 @@ jobs: if: steps.cache.outputs.cache-hit != true run: | curl -sSL https://install.python-poetry.org | python3 - + + - name: Update poetry.lock + run: poetry lock --no-update - name: Install dependencies run: poetry install --extras "all" From 00d710be8410e8894d652f48578ad9e6acd9dcb9 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 11:53:53 +0300 Subject: [PATCH 049/136] lock --- .github/workflows/test.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 7cead062..0e489d48 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -60,9 +60,9 @@ jobs: if: steps.cache.outputs.cache-hit != true run: | curl -sSL https://install.python-poetry.org | python3 - - + - name: Update poetry.lock - run: poetry lock --no-update + run: poetry lock - name: Install dependencies run: poetry install --extras "all" From 71015871ca8c0228867a812796e0f6b3c074cefc Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 12:11:47 +0300 Subject: [PATCH 050/136] update-lock --- .github/workflows/test.yml | 3 --- poetry.lock | 4 ++-- 2 files changed, 2 insertions(+), 5 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 0e489d48..bb158471 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -61,9 +61,6 @@ jobs: run: | curl -sSL https://install.python-poetry.org | python3 - - - name: Update poetry.lock - run: poetry lock - - name: Install dependencies run: poetry install --extras "all" diff --git a/poetry.lock b/poetry.lock index d3eeed57..69155c4d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -5667,4 +5667,4 @@ vertexai = ["vertexai"] [metadata] lock-version = "2.0" python-versions = ">=3.10.0,<3.14" -content-hash = "2d7951ca5051488cc9fa02c12251d8ccd6e4ea4a88e8abba021130c079b2c2b7" +content-hash = "dc786bd1f0590e2e59d0b119fe356a5b6a291918a4ff922d76a27b81b9d90680" From cf06b16043d14a1c7d70b2073b03e0cc7ac7d976 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 1 Apr 2025 12:18:43 +0300 Subject: [PATCH 051/136] deep-test-dep --- .github/workflows/test.yml | 2 +- poetry.lock | 2 +- pyproject.toml | 3 +-- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index bb158471..183ef5b5 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -62,7 +62,7 @@ jobs: curl -sSL https://install.python-poetry.org | python3 - - name: Install dependencies - run: poetry install --extras "all" + run: poetry install --with test --extras "all" - name: Wait for Ollama to be ready run: | diff --git a/poetry.lock b/poetry.lock index 69155c4d..b86128f4 100644 --- a/poetry.lock +++ b/poetry.lock @@ -5667,4 +5667,4 @@ vertexai = ["vertexai"] [metadata] lock-version = "2.0" python-versions = ">=3.10.0,<3.14" -content-hash = "dc786bd1f0590e2e59d0b119fe356a5b6a291918a4ff922d76a27b81b9d90680" +content-hash = "cec28acdc863c103f978f9cc03b45b5bb777e2cb9ee50e9a22c416bc3f7c109f" diff --git a/pyproject.toml b/pyproject.toml index e735c733..01694915 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,14 +39,13 @@ litellm = ["litellm", "ollama"] [tool.poetry.group.test.dependencies] pytest = "^8.2.1" +deepeval = "^2.2.6" [tool.poetry.group.dev.dependencies] sphinx = "^7.3.7" sphinx-rtd-theme = "^2.0.0" pandas = "^2.2.2" jupyter = "^1.0.0" -deepeval = "^2.2.6" - [build-system] requires = ["poetry-core"] From eedc49114d025be3007b6a66af06d7dc2927b38f Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 23 Jun 2025 16:19:10 +0300 Subject: [PATCH 052/136] update-config-providers --- graphrag_sdk/model_config.py | 30 +++- graphrag_sdk/models/azure_openai.py | 186 ++++++-------------- graphrag_sdk/models/gemini.py | 191 ++++++++------------- graphrag_sdk/models/litellm.py | 33 +--- graphrag_sdk/models/model.py | 85 ++++++---- graphrag_sdk/models/ollama.py | 198 ++++++++-------------- graphrag_sdk/models/openai.py | 143 ++++++---------- graphrag_sdk/orchestrator/orchestrator.py | 1 - graphrag_sdk/steps/extract_data_step.py | 10 +- tests/test_auto_create_ontology.py | 2 +- tests/test_kg.py | 2 +- tests/test_multi_agent.py | 4 +- tests/test_ontology_from_kg.py | 2 +- 13 files changed, 348 insertions(+), 539 deletions(-) diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index 2e2e5842..e4826c60 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -1,4 +1,5 @@ -from graphrag_sdk.models import GenerativeModel +from graphrag_sdk.models import (GenerativeModel, + GenerativeModelConfig) class KnowledgeGraphModelConfig: @@ -34,6 +35,9 @@ def __init__( def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ Creates a new KnowledgeGraphModelConfig instance with the given generative model. + + The extract_data model will be configured with temperature=0 and JSON response format + for structured data extraction. Args: model (GenerativeModel): The generative model to use. @@ -41,9 +45,29 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": Returns: KnowledgeGraphModelConfig: The new KnowledgeGraphModelConfig instance. - """ + """ + # Take user's existing config and modify for extract_data + config_dict = model.generation_config.to_json() + # Override temperature to 0 unless it's None + if config_dict.get('temperature') is not None: + config_dict['temperature'] = 0 + # Add JSON output format + config_dict['response_format'] = {"type": "json_object"} + extract_config = GenerativeModelConfig.from_json(config_dict) + + # Create extract_data model with specialized configuration + try: + extract_data_model = model.__class__( + model_name=model.model_name, + generation_config=extract_config, + system_instruction=model.system_instruction + ) + except Exception: + # Fallback: use original model if creation fails + extract_data_model = model + return KnowledgeGraphModelConfig( - extract_data=model, + extract_data=extract_data_model, cypher_generation=model, qa=model, ) diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index 10072d6c..5f26e492 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -1,9 +1,8 @@ import os from typing import Any from typing import Optional -from openai import AzureOpenAI +from .litellm import LiteModel from .model import ( - OutputMethod, GenerativeModel, GenerativeModelConfig, GenerationResponse, @@ -15,6 +14,7 @@ class AzureOpenAiGenerativeModel(GenerativeModel): """ A generative model that interfaces with Azure's OpenAI API for chat completions. + This implementation uses LiteLLM as the backend while maintaining the original API. """ def __init__( @@ -33,27 +33,34 @@ def __init__( system_instruction (Optional[str]): System-level instruction for the model. kwargs (Any): Additional arguments optional by Azure OpenAI API. """ - self.model_name = model_name - self.generation_config = generation_config or GenerativeModelConfig() - self.system_instruction = system_instruction - self.additional_params = kwargs - - # Credentials - self.api_key = os.getenv("AZURE_OPENAI_API_KEY") - self.azure_endpoint = os.getenv("AZURE_ENDPOINT") - self.api_version = os.getenv("AZURE_API_VERSION") - - if not self.api_key or not self.azure_endpoint or not self.api_version: - raise ValueError( - "Missing credentials in the environment: AZURE_OPENAI_API_KEY, AZURE_ENDPOINT, or AZURE_API_VERSION." - ) - - self.client = AzureOpenAI( - azure_endpoint=self.azure_endpoint, - api_version=self.api_version, - api_key=self.api_key, - **self.additional_params, # Azure additional parameters + # Convert to LiteLLM format + lite_model_name = f"azure/{model_name}" + + # Create internal LiteLLM model + self._lite_model = LiteModel( + model_name=lite_model_name, + generation_config=generation_config, + system_instruction=system_instruction, + additional_params=kwargs ) + + # Store original model name for compatibility (without the azure/ prefix) + self._original_model_name = model_name + + @property + def model_name(self) -> str: + """Get the original model name (without azure/ prefix).""" + return self._original_model_name + + @property + def system_instruction(self) -> Optional[str]: + """Get the system instruction from the internal LiteLLM model.""" + return self._lite_model.system_instruction + + @property + def generation_config(self) -> GenerativeModelConfig: + """Get the generation config from the internal LiteLLM model.""" + return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: @@ -68,52 +75,11 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode """ return AzureOpenAiChatSession(self, system_instruction) - def ask(self, message: str) -> GenerationResponse: + def parse_generate_content_response(self, response: any) -> GenerationResponse: """ - Send a message to the model and receive a response. - - Args: - message (str): The user's message input. - - Returns: - GenerationResponse: The model's generated response. - """ - response = self.client.chat.completions.create( - model=self.model_name, - messages=[ - {"role": "system", "content": self.system_instruction}, - {"role": "user", "content": message[:14385]}, - ], - max_tokens=self.generation_config.max_tokens, - temperature=self.generation_config.temperature, - top_p=self.generation_config.top_p, - top_k=self.generation_config.top_k, - stop=self.generation_config.stop, - ) - return self._parse_generate_content_response(response) - - def _parse_generate_content_response(self, response: any) -> GenerationResponse: + Parse the model's response using the internal LiteLLM model. """ - Parse the model's response and extract content for the user. - - Args: - response (any): The raw response from the model. - - Returns: - GenerationResponse: Parsed response containing the generated text and finish reason. - """ - return GenerationResponse( - text=response.choices[0].message.content, - finish_reason=( - FinishReason.STOP - if response.choices[0].finish_reason == "stop" - else ( - FinishReason.MAX_TOKENS - if response.choices[0].finish_reason == "length" - else FinishReason.OTHER - ) - ), - ) + return self._lite_model.parse_generate_content_response(response) def to_json(self) -> dict: """ @@ -150,12 +116,10 @@ def from_json(json: dict) -> "GenerativeModel": class AzureOpenAiChatSession(GenerativeModelChatSession): """ - A chat session for interacting with the Azure OpenAI model, maintaining conversation history. + A chat session for interacting with the Azure OpenAI model. + This implementation delegates to LiteLLM for actual API calls. """ - - _history = [] - def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. @@ -165,33 +129,32 @@ def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Option system_instruction (Optional[str]): Optional system instruction. """ self._model = model - self._chat_history = ( - [{"role": "system", "content": system_instruction}] - if system_instruction is not None - else [] - ) + # Create internal LiteLLM chat session + self._lite_chat = model._lite_model.start_chat(system_instruction) - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: """ Send a message in the chat session and receive the model's response. Args: message (str): The message to send. - output_method (OutputMethod): Format for the model's output. Returns: GenerationResponse: The generated response. """ - generation_config = self._adjust_generation_config(output_method) - self._chat_history.append({"role": "user", "content": message[:14385]}) - response = self._model.client.chat.completions.create( - model=self._model.model_name, - messages=self._chat_history, - **generation_config - ) - content = self._model.parse_generate_content_response(response) - self._chat_history.append({"role": "assistant", "content": content.text}) - return content + # Delegate to LiteLLM chat session + return self._lite_chat.send_message(message) + + def send_message_stream(self, message: str): + """ + Send a message and receive the response in a streaming fashion. + Args: + message (str): The message to send. + Yields: + str: Streamed chunks of the model's response. + """ + # Delegate to LiteLLM chat session + return self._lite_chat.send_message_stream(message) def get_chat_history(self) -> list[dict]: """ @@ -200,53 +163,10 @@ def get_chat_history(self) -> list[dict]: Returns: list[dict]: The chat session's conversation history. """ - return self._chat_history.copy() - - def _adjust_generation_config(self, output_method: OutputMethod): - """ - Adjust the generation configuration based on the output method. - - Args: - output_method (OutputMethod): The desired output method (e.g., default or JSON). - - Returns: - dict: The configuration settings for generation. - """ - config = self._model.generation_config.to_json() - if output_method == OutputMethod.JSON: - config['temperature'] = 0 - config['response_format'] = { "type": "json_object" } - - return config + return self._lite_chat.get_chat_history() def delete_last_message(self): """ Deletes the last message exchange (user message and assistant response) from the chat history. - Preserves the system message if present. - - Example: - Before: - [ - {"role": "system", "content": "System message"}, - {"role": "user", "content": "User message"}, - {"role": "assistant", "content": "Assistant response"}, - ] - After: - [ - {"role": "system", "content": "System message"}, - ] - - Note: Does nothing if the chat history is empty or contains only a system message. - """ - # Keep at least the system message if present - min_length = 1 if self._model.system_instruction else 0 - if len(self._history) - 2 >= min_length: - self._history.pop() - self._history.pop() - else: - # Reset to initial state with just system message if present - self._history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None - else [] - ) + """ + self._lite_chat.delete_last_message() diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 117d55d6..464d1be1 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -1,13 +1,7 @@ import os from typing import Optional -from google.generativeai import ( - GenerativeModel as GoogleGenerativeModel, - GenerationConfig as GoogleGenerationConfig, - configure, - protos, - types,) +from .litellm import LiteModel from .model import ( - OutputMethod, GenerativeModel, GenerativeModelConfig, GenerationResponse, @@ -19,40 +13,50 @@ class GeminiGenerativeModel(GenerativeModel): """ A generative model that interfaces with GoogleAI API for chat completions. + This implementation uses LiteLLM as the backend while maintaining the original API. """ - - _model: GoogleGenerativeModel = None def __init__( self, model_name: str, - generation_config: Optional[GoogleGenerationConfig] = None, + generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, ): """ - Initializes the GoogleGenerativeModel with the specified parameters. + Initializes the GeminiGenerativeModel with the specified parameters. Args: - model_name (str): The name of the GoogleAI model to use. - generation_config (Optional[GoogleGenerationConfig]): Configuration settings for generation. - If not provided, a default instance of `GoogleGenerationConfig` is used. - system_instruction (Optional[str]): An optional system-level instruction to guide the model’s behavior. - - Raises: - TypeError: If `generation_config` is provided but is not an instance of `GoogleGenerationConfig`. - """ - if generation_config is not None and not isinstance(generation_config, GoogleGenerationConfig): - raise TypeError( - "generation_config must be an instance of GoogleGenerationConfig " - "(from google.generativeai import GenerationConfig as GoogleGenerationConfig)." - ) + model_name (str): The name of the Gemini model to use. + generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. + system_instruction (Optional[str]): An optional system-level instruction to guide the model's behavior. + """ + # Convert to LiteLLM format + lite_model_name = f"gemini/{model_name}" - self._model_name = model_name - self._generation_config = generation_config or GoogleGenerationConfig() - self._system_instruction = system_instruction + # Create internal LiteLLM model + self._lite_model = LiteModel( + model_name=lite_model_name, + generation_config=generation_config, + system_instruction=system_instruction + ) - # Configure the API key for Google Generative AI - configure(api_key=os.environ["GOOGLE_API_KEY"]) + # Store original model name for compatibility (without the gemini/ prefix) + self._original_model_name = model_name + + @property + def model_name(self) -> str: + """Get the original model name (without gemini/ prefix).""" + return self._original_model_name + + @property + def system_instruction(self) -> Optional[str]: + """Get the system instruction from the internal LiteLLM model.""" + return self._lite_model.system_instruction + + @property + def generation_config(self) -> GenerativeModelConfig: + """Get the generation config from the internal LiteLLM model.""" + return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -62,43 +66,15 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode system_instruction (Optional[str]): Optional system instruction to guide the chat session. Returns: - GeminiChatSession: A new instance of the chat session. - """ - self._model = GoogleGenerativeModel( - self._model_name, - generation_config=( - self._generation_config - if self._generation_config is not None - else None - ), - system_instruction=system_instruction, - ) - - return GeminiChatSession(self) - - def parse_generate_content_response( - self, response: types.generation_types.GenerateContentResponse - ) -> GenerationResponse: + GenerativeModelChatSession: A new instance of the chat session. """ - Parse the model's response and extract content for the user. - Args: - response (any): The raw response from the model. - Returns: - GenerationResponse: Parsed response containing the generated text and finish reason. - """ - return GenerationResponse( - text=response.text, - finish_reason=( - FinishReason.MAX_TOKENS - if response.candidates[0].finish_reason - == protos.Candidate.FinishReason.MAX_TOKENS - else ( - FinishReason.STOP - if response.candidates[0].finish_reason == protos.Candidate.FinishReason.STOP - else FinishReason.OTHER - ) - ), - ) + return GeminiChatSession(self, system_instruction) + + def parse_generate_content_response(self, response: any) -> GenerationResponse: + """ + Parse the model's response using the internal LiteLLM model. + """ + return self._lite_model.parse_generate_content_response(response) def to_json(self) -> dict: """ @@ -108,101 +84,84 @@ def to_json(self) -> dict: dict: The serialized JSON data. """ return { - "model_name": self._model_name, - "generation_config": { - "temperature": self._generation_config.temperature, - "top_p": self._generation_config.top_p, - "max_output_tokens": self._generation_config.max_output_tokens, - "stop_sequences": self._generation_config.stop_sequences, - "response_mime_type": self._generation_config.response_mime_type, - }, - "system_instruction": self._system_instruction, + "model_name": self.model_name, + "generation_config": self.generation_config.to_json(), + "system_instruction": self.system_instruction, } @staticmethod def from_json(json: dict) -> "GenerativeModel": """ Deserialize a JSON object to create an instance of GeminiGenerativeModel. + Args: json (dict): The serialized JSON data. + Returns: GenerativeModel: A new instance of the model. """ return GeminiGenerativeModel( - model_name=json["model_name"], - generation_config=GoogleGenerationConfig(**json["generation_config"]), + json["model_name"], + generation_config=GenerativeModelConfig.from_json( + json["generation_config"] + ), system_instruction=json["system_instruction"], ) class GeminiChatSession(GenerativeModelChatSession): """ - A chat session for interacting with the GoogleAI model, maintaining conversation history. + A chat session for interacting with the Gemini model. + This implementation delegates to LiteLLM for actual API calls. """ - def __init__(self, model: GeminiGenerativeModel): + def __init__(self, model: GeminiGenerativeModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. Args: model (GeminiGenerativeModel): The model instance for the session. + system_instruction (Optional[str]): Optional system instruction. """ - self._model = model - self._chat_session = self._model._model.start_chat() + # Create internal LiteLLM chat session + self._lite_chat = model._lite_model.start_chat(system_instruction) - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: """ Send a message in the chat session and receive the model's response. Args: message (str): The message to send. - output_method (OutputMethod): Format for the model's output. Returns: GenerationResponse: The generated response. """ - generation_config = self._adjust_generation_config(output_method) - response = self._chat_session.send_message(message, generation_config=generation_config) - return self._model.parse_generate_content_response(response) + # Delegate to LiteLLM chat session + return self._lite_chat.send_message(message) - def _adjust_generation_config(self, output_method: OutputMethod) -> dict: + def send_message_stream(self, message: str): """ - Adjust the generation configuration based on the output method. - + Send a message and receive the response in a streaming fashion. Args: - output_method (OutputMethod): The desired output method (e.g., default or JSON). - + message (str): The message to send. + Yields: + str: Streamed chunks of the model's response. + """ + # Delegate to LiteLLM chat session + return self._lite_chat.send_message_stream(message) + + def get_chat_history(self) -> list[dict]: + """ + Retrieve the conversation history for the current chat session. + Returns: - dict: The configuration settings for generation. + list[dict]: The chat session's conversation history. """ - if output_method == OutputMethod.JSON: - return { - "response_mime_type": "application/json", - "temperature": 0 - } - - return self._model._generation_config + return self._lite_chat.get_chat_history() def delete_last_message(self): """ Deletes the last message exchange (user message and assistant response) from the chat history. - Preserves the system message if present. - - Example: - Before: - [ - {"role": "user", "content": "User message"}, - {"role": "assistant", "content": "Assistant response"}, - ] - After: - [] - - Note: Does nothing if the chat history is empty or contains only a system message. """ - if len(self._chat_session.history) >= 2: - self._chat_session.history.pop() - self._chat_session.history.pop() - else: - self._chat_session.history = [] - + self._lite_chat.delete_last_message() diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index a762c989..a7a507ac 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -3,7 +3,6 @@ from typing import Optional, Iterator from litellm import completion, validate_environment, utils as litellm_utils from .model import ( - OutputMethod, GenerativeModel, GenerativeModelConfig, GenerationResponse, @@ -24,6 +23,7 @@ def __init__( model_name: str, generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, + additional_params: Optional[dict] = None, ): """ Initialize the LiteModel with the required parameters. @@ -39,6 +39,7 @@ def __init__( model_name (str): The name and the provider for the LiteLLM client. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): Instruction to guide the model. + additional_params (Optional[dict]): Additional provider-specific parameters. """ env_val = validate_environment(model_name) @@ -56,6 +57,7 @@ def __init__( self.generation_config = generation_config or GenerativeModelConfig() self.system_instruction = system_instruction + self.additional_params = additional_params or {} def check_valid_key(self, model: str): """ @@ -70,7 +72,7 @@ def check_valid_key(self, model: str): messages = [{"role": "user", "content": "Hey, how's it going?"}] try: completion( - model=model, messages=messages, max_tokens=10 + model=model, messages=messages, max_completion_tokens=10 ) return True except Exception as e: @@ -191,24 +193,23 @@ def __init__(self, model: LiteModel, system_instruction: Optional[str] = None): else [] ) - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: """ Send a message in the chat session and receive the model's response. Args: message (str): The message to send. - output_method (OutputMethod): Format for the model's output. Returns: GenerationResponse: The generated response. """ - generation_config = self._adjust_generation_config(output_method) self._chat_history.append({"role": "user", "content": message}) try: response = completion( model=self._model.model, messages=self._chat_history, - **generation_config + **self._model.generation_config.to_json(), + **self._model.additional_params ) except Exception as e: raise ValueError(f"Error during completion request, please check the credentials - {e}") @@ -226,7 +227,6 @@ def send_message_stream(self, message: str) -> Iterator[str]: Yields: str: Streamed chunks of the model's response. """ - generation_config = self._adjust_generation_config(OutputMethod.DEFAULT) self._chat_history.append({"role": "user", "content": message}) try: @@ -234,7 +234,8 @@ def send_message_stream(self, message: str) -> Iterator[str]: model=self._model.model, messages=self._chat_history, stream=True, # Enable streaming mode - **generation_config + **self._model.generation_config.to_json(), + **self._model.additional_params ) chunks = [] @@ -254,22 +255,6 @@ def send_message_stream(self, message: str) -> Iterator[str]: except Exception as e: raise ValueError(f"Error during streaming request, check credentials - {e}") from e - def _adjust_generation_config(self, output_method: OutputMethod): - """ - Adjust the generation configuration based on the specified output method. - - Args: - output_method (OutputMethod): The desired output method (e.g., default or JSON). - - Returns: - dict: The adjusted configuration settings for generation. - """ - config = self._model.generation_config.to_json() - if output_method == OutputMethod.JSON: - config['temperature'] = 0 - config['response_format'] = { "type": "json_object" } - - return config def get_chat_history(self) -> list[dict]: """ diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index fb5989ca..806e8d58 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -1,4 +1,3 @@ -from enum import Enum from abc import ABC, abstractmethod from typing import Optional, Iterator @@ -8,32 +7,29 @@ class FinishReason: STOP = "STOP" OTHER = "OTHER" -class OutputMethod(Enum): - JSON = 'json' - DEFAULT = 'default' - class GenerativeModelConfig: """ Configuration for a generative model. - - This configuration follows OpenAI-style parameter naming but is designed to be compatible with other generative models. - + + This configuration follows OpenAI-style parameter naming but is designed to be + compatible with other generative models. Supports both predefined and arbitrary parameters. + Args: - temperature (Optional[float]): Controls the randomness of the output. Higher values (e.g., 1.0) make responses more random, - while lower values (e.g., 0.1) make them more deterministic. - top_p (Optional[float]): Nucleus sampling parameter. A value of 0.9 considers only the top 90% of probability mass. + temperature (Optional[float]): Controls randomness of the output. + top_p (Optional[float]): Nucleus sampling parameter. top_k (Optional[int]): Limits sampling to the top-k most probable tokens. - max_tokens (Optional[int]): The maximum number of tokens the model is allowed to generate in a response. - stop (Optional[list[str]]): A list of stop sequences that signal the model to stop generating further tokens. - response_format (Optional[dict]): Specifies the desired format of the response, if supported by the model. + max_tokens (Optional[int]): Maximum number of tokens to generate. + stop (Optional[list[str]]): Stop sequences. + response_format (Optional[dict]): Desired response format. + **kwargs: Any additional parameters not explicitly defined. + Example: >>> config = GenerativeModelConfig( ... temperature=0.5, - ... top_p=0.9, - ... top_k=50, - ... max_tokens=100, - ... stop=[".", "?", "!"] + ... max_tokens=100, ... ) + >>> config.to_json() + {'temperature': 0.5, 'max_tokens': 100} """ def __init__( @@ -44,6 +40,7 @@ def __init__( max_tokens: Optional[int] = None, stop: Optional[list[str]] = None, response_format: Optional[dict] = None, + **kwargs, ): self.temperature = temperature self.top_p = top_p @@ -52,27 +49,45 @@ def __init__( self.stop = stop self.response_format = response_format - def __str__(self) -> str: - return f"GenerativeModelConfig(temperature={self.temperature}, top_p={self.top_p}, top_k={self.top_k}, max_tokens={self.max_tokens}, stop={self.stop})" + # Store extra parameters + for key, value in kwargs.items(): + setattr(self, key, value) + def __str__(self) -> str: + return f"GenerativeModelConfig({', '.join(f'{k}={v}' for k, v in self.to_json().items())})" + def to_json(self) -> dict: - return { - "temperature": self.temperature, - "top_p": self.top_p, - "max_tokens": self.max_tokens, - "stop": self.stop, - "response_format": self.response_format, - } + """ + Serialize the configuration to a dictionary, excluding any fields with None values. + + Returns: + dict: A dictionary containing only the parameters that are explicitly set + (i.e., not None). + + Example: + >>> config = GenerativeModelConfig(temperature=0.7, max_tokens=100) + >>> config.to_json() + {'temperature': 0.7, 'max_tokens': 100} + """ + return {k: v for k, v in self.__dict__.items() if v is not None} @staticmethod def from_json(json: dict) -> "GenerativeModelConfig": - return GenerativeModelConfig( - temperature=json.get("temperature"), - top_p=json.get("top_p"), - top_k=json.get("top_k"), - max_tokens=json.get("max_tokens"), - stop=json.get("stop"), - ) + # Extract known parameters + known_params = { + 'temperature': json.get("temperature"), + 'top_p': json.get("top_p"), + 'top_k': json.get("top_k"), + 'max_tokens': json.get("max_tokens"), + 'stop': json.get("stop"), + 'response_format': json.get("response_format"), + } + + # Extract any additional parameters not in the known set + known_keys = set(known_params.keys()) + extra_params = {k: v for k, v in json.items() if k not in known_keys} + + return GenerativeModelConfig(**known_params, **extra_params) class GenerationResponse: @@ -97,7 +112,7 @@ def __init__(self, model: "GenerativeModel"): self.model = model @abstractmethod - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: pass def send_message_stream(self, message: str) -> Iterator[str]: diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index 2d72ba0d..756ead86 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -1,12 +1,10 @@ import logging from typing import Optional -from ollama import Client, Options +from .litellm import LiteModel from .model import ( - OutputMethod, GenerativeModel, GenerativeModelConfig, GenerationResponse, - FinishReason, GenerativeModelChatSession, ) @@ -16,14 +14,13 @@ class OllamaGenerativeModel(GenerativeModel): """ A generative model that interfaces with the Ollama Client for chat completions. + This implementation uses LiteLLM as the backend while maintaining the original API. """ - client: Client = None - def __init__( self, model_name: str, - generation_config: Optional[GenerativeModelConfig] = None, + generation_config: Optional[GenerativeModelConfig] = GenerativeModelConfig(), system_instruction: Optional[str] = None, host: Optional[str] = None, ): @@ -34,52 +31,50 @@ def __init__( model_name (str): The name of the Ollama model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): Instruction to guide the model. - host (Optional[str]): Host for connecting to the Ollama API. + host (Optional[str]): Host for connecting to the Ollama API (ignored in LiteLLM implementation). """ - self.model_name = model_name - self.generation_config = generation_config or GenerativeModelConfig() - self.system_instruction = system_instruction + # Convert to LiteLLM format + lite_model_name = f"ollama/{model_name}" + + # Handle host parameter for Ollama + additional_params = {} + if host is not None: + additional_params['api_base'] = host # LiteLLM uses api_base for custom endpoints + + # Create internal LiteLLM model + self._lite_model = LiteModel( + model_name=lite_model_name, + generation_config=generation_config, + system_instruction=system_instruction, + additional_params=additional_params + ) + + # Store original model name and host for compatibility + self._original_model_name = model_name self._host = host - try: - self.client = Client(host) - except Exception as e: - logger.error(f"Failed to initialize the Ollama client: {e}") - raise e - self.check_and_pull_model() - - def check_and_pull_model(self) -> None: - """ - Checks if the specified model is available locally, and pulls it if not. - - Logs: - - Info: If the model is already available or after successfully pulling the model. - - Error: If there is a failure in pulling the model. - - Raises: - Exception: If there is an error during the model pull process. - """ - # Get the list of available models - response = self.client.list() # This returns a dictionary - available_models = [model['name'] for model in response['models']] # Extract model names - - # Check if the model is already pulled - if self.model_name in available_models: - logger.info(f"The model '{self.model_name}' is already available.") - else: - logger.info(f"Pulling the model '{self.model_name}'...") - try: - self.client.pull(self.model_name) # Pull the model - logger.info(f"Model '{self.model_name}' pulled successfully.") - except Exception as e: - logger.error(f"Failed to pull the model '{self.model_name}': {e}") + + @property + def model_name(self) -> str: + """Get the original model name (without ollama/ prefix).""" + return self._original_model_name + + @property + def system_instruction(self) -> Optional[str]: + """Get the system instruction from the internal LiteLLM model.""" + return self._lite_model.system_instruction + @property + def generation_config(self) -> GenerativeModelConfig: + """Get the generation config from the internal LiteLLM model.""" + return self._lite_model.generation_config + def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ Start a new chat session. - + Args: system_instruction (Optional[str]): Optional system instruction to guide the chat session. - + Returns: GenerativeModelChatSession: A new instance of the chat session. """ @@ -87,18 +82,9 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode def parse_generate_content_response(self, response: any) -> GenerationResponse: """ - Parse the model's response and extract content for the user. - - Args: - response (any): The raw response from the model. - - Returns: - GenerationResponse: Parsed response containing the generated text. + Parse the model's response using the internal LiteLLM model. """ - return GenerationResponse( - text=response["message"]["content"], - finish_reason=FinishReason.STOP - ) + return self._lite_model.parse_generate_content_response(response) def to_json(self) -> dict: """ @@ -108,9 +94,9 @@ def to_json(self) -> dict: dict: The serialized JSON data. """ return { - "model_name": self._model_name, - "generation_config": self._generation_config.to_json(), - "system_instruction": self._system_instruction, + "model_name": self.model_name, + "generation_config": self.generation_config.to_json(), + "system_instruction": self.system_instruction, } @staticmethod @@ -125,109 +111,67 @@ def from_json(json: dict) -> "GenerativeModel": GenerativeModel: A new instance of the model. """ return OllamaGenerativeModel( - model_name=json["model_name"], + json["model_name"], generation_config=GenerativeModelConfig.from_json( json["generation_config"] ), system_instruction=json["system_instruction"], ) + class OllamaChatSession(GenerativeModelChatSession): """ - A chat session for interacting with the Ollama model, maintaining conversation history. + A chat session for interacting with the Ollama model. + This implementation delegates to LiteLLM for actual API calls. """ - + def __init__(self, model: OllamaGenerativeModel, system_instruction: Optional[str] = None): """ Initialize the chat session and set up the conversation history. Args: model (OllamaGenerativeModel): The model instance for the session. - system_instruction (Optional[str]): Optional system instruction + system_instruction (Optional[str]): Optional system instruction. """ self._model = model - self._chat_history = ( - [{"role": "system", "content": system_instruction}] - if system_instruction is not None - else [] - ) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._chat_history.copy() + # Create internal LiteLLM chat session + self._lite_chat = model._lite_model.start_chat(system_instruction) - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: """ Send a message in the chat session and receive the model's response. Args: message (str): The message to send. - output_method (OutputMethod): Format for the model's output. Returns: GenerationResponse: The generated response. """ - generation_config = self._adjust_generation_config(output_method) - self._chat_history.append({"role": "user", "content": message[:14385]}) - response = self._model.client.chat( - model=self._model.model_name, - messages=self._chat_history, - options=Options(**generation_config) - ) - content = self._model.parse_generate_content_response(response) - self._chat_history.append({"role": "assistant", "content": content.text}) - return content + # Delegate to LiteLLM chat session + return self._lite_chat.send_message(message) - def _adjust_generation_config(self, output_method: OutputMethod) -> dict: + def send_message_stream(self, message: str): """ - Adjust the generation configuration based on the specified output method. - + Send a message and receive the response in a streaming fashion. Args: - output_method (OutputMethod): The desired output method (e.g., default or JSON). + message (str): The message to send. + Yields: + str: Streamed chunks of the model's response. + """ + # Delegate to LiteLLM chat session + return self._lite_chat.send_message_stream(message) + + def get_chat_history(self) -> list[dict]: + """ + Retrieve the conversation history for the current chat session. Returns: - dict: The adjusted configuration settings for generation. + list[dict]: The chat session's conversation history. """ - config = self._model.generation_config.to_json() - if output_method == OutputMethod.JSON: - config['temperature'] = 0 - config['format'] = 'json' - - return config + return self._lite_chat.get_chat_history() def delete_last_message(self): """ Deletes the last message exchange (user message and assistant response) from the chat history. - Preserves the system message if present. - - Example: - Before: - [ - {"role": "system", "content": "System message"}, - {"role": "user", "content": "User message"}, - {"role": "assistant", "content": "Assistant response"}, - ] - After: - [ - {"role": "system", "content": "System message"}, - ] - - Note: Does nothing if the chat history is empty or contains only a system message. - """ - # Keep at least the system message if present - min_length = 1 if self._model.system_instruction else 0 - if len(self._chat_history) - 2 >= min_length: - self._chat_history.pop() - self._chat_history.pop() - else: - # Reset to initial state with just system message if present - self._chat_history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None - else [] - ) \ No newline at end of file + """ + self._lite_chat.delete_last_message() diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index d87ac600..3076001e 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -1,8 +1,7 @@ import os -from openai import OpenAI from typing import Optional +from .litellm import LiteModel, LiteModelChatSession from .model import ( - OutputMethod, GenerativeModel, GenerativeModelConfig, GenerationResponse, @@ -14,14 +13,13 @@ class OpenAiGenerativeModel(GenerativeModel): """ A generative model that interfaces with OpenAI's API for chat completions. + This implementation uses LiteLLM as the backend while maintaining the original API. """ - client: OpenAI = None - def __init__( self, model_name: str, - generation_config: Optional[GenerativeModelConfig] = None, + generation_config: Optional[GenerativeModelConfig] = GenerativeModelConfig(), system_instruction: Optional[str] = None, ): """ @@ -32,12 +30,33 @@ def __init__( generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. """ - self.model_name = model_name - self.generation_config = generation_config or GenerativeModelConfig() - self.system_instruction = system_instruction - if not os.getenv("OPENAI_API_KEY"): - raise ValueError("Missing OpenAI API key in the environment: OPENAI_API_KEY") - self.client = OpenAI() + # Convert to LiteLLM format + lite_model_name = f"openai/{model_name}" + + # Create internal LiteLLM model + self._lite_model = LiteModel( + model_name=lite_model_name, + generation_config=generation_config, + system_instruction=system_instruction + ) + + # Store original model name for compatibility (without the openai/ prefix) + self._original_model_name = model_name + + @property + def model_name(self) -> str: + """Get the original model name (without openai/ prefix).""" + return self._original_model_name + + @property + def system_instruction(self) -> Optional[str]: + """Get the system instruction from the internal LiteLLM model.""" + return self._lite_model.system_instruction + + @property + def generation_config(self) -> GenerativeModelConfig: + """Get the generation config from the internal LiteLLM model.""" + return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -51,18 +70,10 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode return OpenAiChatSession(self, system_instruction) def parse_generate_content_response(self, response: any) -> GenerationResponse: - return GenerationResponse( - text=response.choices[0].message.content, - finish_reason=( - FinishReason.STOP - if response.choices[0].finish_reason == "stop" - else ( - FinishReason.MAX_TOKENS - if response.choices[0].finish_reason == "length" - else FinishReason.OTHER - ) - ), - ) + """ + Parse the model's response using the internal LiteLLM model. + """ + return self._lite_model.parse_generate_content_response(response) def to_json(self) -> dict: """ @@ -71,7 +82,6 @@ def to_json(self) -> dict: Returns: dict: The serialized JSON data. """ - return { "model_name": self.model_name, "generation_config": self.generation_config.to_json(), @@ -100,7 +110,8 @@ def from_json(json: dict) -> "GenerativeModel": class OpenAiChatSession(GenerativeModelChatSession): """ - A chat session for interacting with the OpenAI model, maintaining conversation history. + A chat session for interacting with the OpenAI model. + This implementation delegates to LiteLLM for actual API calls. """ def __init__(self, model: OpenAiGenerativeModel, system_instruction: Optional[str] = None) -> None: @@ -111,86 +122,42 @@ def __init__(self, model: OpenAiGenerativeModel, system_instruction: Optional[st system_instruction (Optional[str]): Optional system instruction. """ self._model = model - self._chat_history = ( - [{"role": "system", "content": system_instruction}] - if system_instruction is not None - else [] - ) + # Create internal LiteLLM chat session + self._lite_chat = model._lite_model.start_chat(system_instruction) - def send_message(self, message: str, output_method: OutputMethod = OutputMethod.DEFAULT) -> GenerationResponse: + def send_message(self, message: str) -> GenerationResponse: """ Send a message in the chat session and receive the model's response. Args: message (str): The message to send. - output_method (OutputMethod): Format for the model's output. Returns: GenerationResponse: The generated response. """ - generation_config = self._adjust_generation_config(output_method) - self._chat_history.append({"role": "user", "content": message[:14385]}) - response = self._model.client.chat.completions.create( - model=self._model.model_name, - messages=self._chat_history, - **generation_config - ) - content = self._model.parse_generate_content_response(response) - self._chat_history.append({"role": "assistant", "content": content.text}) - return content + # Delegate to LiteLLM chat session + return self._lite_chat.send_message(message) - def get_chat_history(self) -> list[dict]: + def send_message_stream(self, message: str): """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. + Send a message and receive the response in a streaming fashion. + Args: + message (str): The message to send. + Yields: + str: Streamed chunks of the model's response. """ - return self._chat_history.copy() + # Delegate to LiteLLM chat session + return self._lite_chat.send_message_stream(message) - def _adjust_generation_config(self, output_method: OutputMethod): + def get_chat_history(self) -> list[dict]: """ - Adjust the generation configuration based on the output method. + Retrieve the conversation history for the current chat session. - Args: - output_method (OutputMethod): The desired output method (e.g., default or JSON). - Returns: - dict: The configuration settings for generation. + list[dict]: The chat session's conversation history. """ - config = self._model.generation_config.to_json() - if output_method == OutputMethod.JSON: - config['temperature'] = 0 - config['response_format'] = { "type": "json_object" } - - return config + return self._lite_chat.get_chat_history() def delete_last_message(self): """ Deletes the last message exchange (user message and assistant response) from the chat history. - Preserves the system message if present. - - Example: - Before: - [ - {"role": "system", "content": "System message"}, - {"role": "user", "content": "User message"}, - {"role": "assistant", "content": "Assistant response"}, - ] - After: - [ - {"role": "system", "content": "System message"}, - ] - - Note: Does nothing if the chat history is empty or contains only a system message. - """ - # Keep at least the system message if present - min_length = 1 if self._model.system_instruction else 0 - if len(self._history) - 2 >= min_length: - self._history.pop() - self._history.pop() - else: - # Reset to initial state with just system message if present - self._history = ( - [{"role": "system", "content": self._model.system_instruction}] - if self._model.system_instruction is not None - else [] - ) + """ + self._lite_chat.delete_last_message() diff --git a/graphrag_sdk/orchestrator/orchestrator.py b/graphrag_sdk/orchestrator/orchestrator.py index 251e9e8e..9f1d73bc 100644 --- a/graphrag_sdk/orchestrator/orchestrator.py +++ b/graphrag_sdk/orchestrator/orchestrator.py @@ -4,7 +4,6 @@ from graphrag_sdk.helpers import extract_json from graphrag_sdk.models import GenerativeModel, GenerativeModelChatSession from .orchestrator_runner import OrchestratorRunner, OrchestratorResult -from graphrag_sdk.models.model import OutputMethod from .execution_plan import ( ExecutionPlan, ) diff --git a/graphrag_sdk/steps/extract_data_step.py b/graphrag_sdk/steps/extract_data_step.py index 6e8a1224..06ef9f8d 100644 --- a/graphrag_sdk/steps/extract_data_step.py +++ b/graphrag_sdk/steps/extract_data_step.py @@ -11,7 +11,6 @@ from graphrag_sdk.document import Document from ratelimit import limits, sleep_and_retry from graphrag_sdk.source import AbstractSource -from graphrag_sdk.models.model import OutputMethod from concurrent.futures import Future, ThreadPoolExecutor from graphrag_sdk.helpers import extract_json, map_dict_to_cypher_properties from graphrag_sdk.ontology import Ontology @@ -188,14 +187,14 @@ def _process_document( responses: list[GenerationResponse] = [] response_idx = 0 - responses.append(self._call_model(chat_session, user_message, output_method=OutputMethod.JSON)) + responses.append(self._call_model(chat_session, user_message)) _task_logger.debug(f"Model response: {responses[response_idx].text}") while responses[response_idx].finish_reason == FinishReason.MAX_TOKENS and response_idx < retries: _task_logger.debug("Asking model to continue") response_idx += 1 - responses.append(self._call_model(chat_session, COMPLETE_DATA_EXTRACTION, output_method=OutputMethod.JSON)) + responses.append(self._call_model(chat_session, COMPLETE_DATA_EXTRACTION)) _task_logger.debug( f"Model response after continue: {responses[response_idx].text}" ) @@ -219,7 +218,6 @@ def _process_document( json_fix_response = self._call_model( self._create_chat(), FIX_JSON_PROMPT.format(json=last_respond, error=str(e)), - output_method=OutputMethod.JSON, ) data = json.loads(extract_json(json_fix_response.text)) _task_logger.debug(f"Fixed JSON: {data}") @@ -351,7 +349,6 @@ def _call_model( chat_session: GenerativeModelChatSession, prompt: str, retry: int = 6, - output_method: OutputMethod = OutputMethod.DEFAULT ) -> GenerationResponse: """ Call the generative model with rate limiting and retries. @@ -360,7 +357,6 @@ def _call_model( chat_session (GenerativeModelChatSession): The chat session for interacting with the model. prompt (str): The prompt to send to the model. retry (Optional[int]): Number of retries in case of quota exceeded or errors. - output_method (Optional[OutputMethod]): The output method for the response. Returns: GenerationResponse: The model's response. @@ -369,7 +365,7 @@ def _call_model( Exception: If an error occurs after exhausting retries. """ try: - return chat_session.send_message(prompt, output_method=output_method) + return chat_session.send_message(prompt) except Exception as e: # If exception is caused by quota exceeded, wait 10 seconds and try again for 6 times if "Quota exceeded" in str(e) and retry > 0: diff --git a/tests/test_auto_create_ontology.py b/tests/test_auto_create_ontology.py index 4a9ec6dc..18689aaf 100644 --- a/tests/test_auto_create_ontology.py +++ b/tests/test_auto_create_ontology.py @@ -24,7 +24,7 @@ def test_auto_detect_ontology(self): sources = [Source(file_path)] - model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001") + model = GeminiGenerativeModel(model_name="gemini-1.5-flash") boundaries = """ Extract entities and relationships from each page diff --git a/tests/test_kg.py b/tests/test_kg.py index 3398eae4..a886a4ae 100644 --- a/tests/test_kg.py +++ b/tests/test_kg.py @@ -68,7 +68,7 @@ def setUpClass(cls): cls.graph_name = "test_kg" - model = GeminiGenerativeModel(model_name="gemini-1.5-flash-001") + model = GeminiGenerativeModel(model_name="gemini-1.5-flash") cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, diff --git a/tests/test_multi_agent.py b/tests/test_multi_agent.py index 02ae5978..ecf77bf6 100644 --- a/tests/test_multi_agent.py +++ b/tests/test_multi_agent.py @@ -6,9 +6,9 @@ from graphrag_sdk.relation import Relation from graphrag_sdk.ontology import Ontology from graphrag_sdk.agents.kg_agent import KGAgent +from graphrag_sdk.models.litellm import LiteModel from graphrag_sdk.orchestrator import Orchestrator from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk.models.gemini import GeminiGenerativeModel from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig load_dotenv() @@ -185,7 +185,7 @@ def setUpClass(cls): ) ) - cls.model = GeminiGenerativeModel("gemini-1.5-flash-001") + cls.model = LiteModel("azure/o3-mini") cls.restaurants_kg = KnowledgeGraph( name="restaurants", ontology=cls.restaurants_ontology, diff --git a/tests/test_ontology_from_kg.py b/tests/test_ontology_from_kg.py index 652359fe..f0ef9618 100644 --- a/tests/test_ontology_from_kg.py +++ b/tests/test_ontology_from_kg.py @@ -55,7 +55,7 @@ def ontology_kg_setup(): ontology.add_relation(Relation(label="IN_CITY", source="Restaurant", target="City")) # Create a model and a knowledge graph. - model = GeminiGenerativeModel("gemini-1.5-flash-001") + model = GeminiGenerativeModel("gemini-1.5-flash") kg = KnowledgeGraph( name="test_ontology", ontology=ontology, From a8211915feb2b261f08d8e9d9f47f173275c2648 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 23 Jun 2025 18:58:08 +0300 Subject: [PATCH 053/136] temp-fixes --- graphrag_sdk/model_config.py | 11 +++++++-- graphrag_sdk/models/model.py | 47 ++++++++++++++++++++++++------------ tests/test_multi_agent.py | 7 ++++-- 3 files changed, 46 insertions(+), 19 deletions(-) diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index e4826c60..8995f8df 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -48,8 +48,15 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ # Take user's existing config and modify for extract_data config_dict = model.generation_config.to_json() - # Override temperature to 0 unless it's None - if config_dict.get('temperature') is not None: + + # Check if temperature was explicitly set by the user + if model.generation_config._temperature_was_set: + # User explicitly set temperature (even if to None), only override if not None + if model.generation_config.temperature is not None: + config_dict['temperature'] = 0 + # If user explicitly set temperature=None, respect that and don't override + else: + # User didn't set temperature (using default None), override to 0 config_dict['temperature'] = 0 # Add JSON output format config_dict['response_format'] = {"type": "json_object"} diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index 806e8d58..74d897af 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -31,18 +31,28 @@ class GenerativeModelConfig: >>> config.to_json() {'temperature': 0.5, 'max_tokens': 100} """ + + # Sentinel value to detect when temperature was not explicitly set + _TEMP_NOT_SET = object() def __init__( self, - temperature: Optional[float] = None, + temperature = _TEMP_NOT_SET, top_p: Optional[float] = None, top_k: Optional[int] = None, max_tokens: Optional[int] = None, - stop: Optional[list[str]] = None, + stop: Optional[list] = None, response_format: Optional[dict] = None, **kwargs, ): - self.temperature = temperature + # Set temperature and track if it was explicitly set + if temperature is self._TEMP_NOT_SET: + self.temperature = None + self._temperature_was_set = False + else: + self.temperature = temperature + self._temperature_was_set = True + self.top_p = top_p self.top_k = top_k self.max_tokens = max_tokens @@ -53,6 +63,7 @@ def __init__( for key, value in kwargs.items(): setattr(self, key, value) + def __str__(self) -> str: return f"GenerativeModelConfig({', '.join(f'{k}={v}' for k, v in self.to_json().items())})" @@ -69,25 +80,31 @@ def to_json(self) -> dict: >>> config.to_json() {'temperature': 0.7, 'max_tokens': 100} """ - return {k: v for k, v in self.__dict__.items() if v is not None} + return {k: v for k, v in self.__dict__.items() if v is not None and k != '_temperature_was_set'} @staticmethod def from_json(json: dict) -> "GenerativeModelConfig": - # Extract known parameters - known_params = { - 'temperature': json.get("temperature"), - 'top_p': json.get("top_p"), - 'top_k': json.get("top_k"), - 'max_tokens': json.get("max_tokens"), - 'stop': json.get("stop"), - 'response_format': json.get("response_format"), - } + # Extract known parameters, but only pass them if they exist in JSON + params = {} + if "temperature" in json: + params['temperature'] = json["temperature"] + # For other parameters, only pass if they exist in JSON to maintain default behavior + if "top_p" in json: + params['top_p'] = json["top_p"] + if "top_k" in json: + params['top_k'] = json["top_k"] + if "max_tokens" in json: + params['max_tokens'] = json["max_tokens"] + if "stop" in json: + params['stop'] = json["stop"] + if "response_format" in json: + params['response_format'] = json["response_format"] # Extract any additional parameters not in the known set - known_keys = set(known_params.keys()) + known_keys = {'temperature', 'top_p', 'top_k', 'max_tokens', 'stop', 'response_format'} extra_params = {k: v for k, v in json.items() if k not in known_keys} - return GenerativeModelConfig(**known_params, **extra_params) + return GenerativeModelConfig(**params, **extra_params) class GenerationResponse: diff --git a/tests/test_multi_agent.py b/tests/test_multi_agent.py index ecf77bf6..6f99a9dc 100644 --- a/tests/test_multi_agent.py +++ b/tests/test_multi_agent.py @@ -9,7 +9,10 @@ from graphrag_sdk.models.litellm import LiteModel from graphrag_sdk.orchestrator import Orchestrator from graphrag_sdk.attribute import Attribute, AttributeType -from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig +from graphrag_sdk import (KnowledgeGraph, + KnowledgeGraphModelConfig, + GenerativeModelConfig) + load_dotenv() logging.basicConfig(level=logging.DEBUG) @@ -185,7 +188,7 @@ def setUpClass(cls): ) ) - cls.model = LiteModel("azure/o3-mini") + cls.model = LiteModel("azure/o3-mini", generation_config=GenerativeModelConfig(temperature=None)) cls.restaurants_kg = KnowledgeGraph( name="restaurants", ontology=cls.restaurants_ontology, From 8c6bf98ce895ceca63a3b85953b93babb0b59387 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 23 Jun 2025 19:10:25 +0300 Subject: [PATCH 054/136] add-keys --- .github/workflows/test.yml | 3 +++ graphrag_sdk/models/azure_openai.py | 2 ++ graphrag_sdk/models/gemini.py | 2 ++ graphrag_sdk/models/ollama.py | 4 +++- graphrag_sdk/models/openai.py | 4 +++- 5 files changed, 13 insertions(+), 2 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 183ef5b5..b583d2dc 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -78,5 +78,8 @@ jobs: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} + AZURE_API_BASE: ${{ secrets.AZURE_API_BASE }} + AZURE_API_VERSION: ${{ secrets.AZURE_API_VERSION }} + AZURE_API_KEY: ${{ secrets.AZURE_API_KEY }} TEST_MODEL: ${{ matrix.model }} # Pass the model as an environment variable run: poetry run pytest diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index 5f26e492..cef0362e 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -35,6 +35,8 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"azure/{model_name}" + + generation_config = generation_config or GenerativeModelConfig() # Create internal LiteLLM model self._lite_model = LiteModel( diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 464d1be1..05aef1ff 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -32,6 +32,8 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"gemini/{model_name}" + + generation_config = generation_config or GenerativeModelConfig() # Create internal LiteLLM model self._lite_model = LiteModel( diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index 756ead86..3d11de22 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -20,7 +20,7 @@ class OllamaGenerativeModel(GenerativeModel): def __init__( self, model_name: str, - generation_config: Optional[GenerativeModelConfig] = GenerativeModelConfig(), + generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, host: Optional[str] = None, ): @@ -35,6 +35,8 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"ollama/{model_name}" + + generation_config = generation_config or GenerativeModelConfig() # Handle host parameter for Ollama additional_params = {} diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index 3076001e..8e4324fe 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -19,7 +19,7 @@ class OpenAiGenerativeModel(GenerativeModel): def __init__( self, model_name: str, - generation_config: Optional[GenerativeModelConfig] = GenerativeModelConfig(), + generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, ): """ @@ -32,6 +32,8 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"openai/{model_name}" + + generation_config = generation_config or GenerativeModelConfig() # Create internal LiteLLM model self._lite_model = LiteModel( From 8e372b5563cd1b2d6f023236514bcc2bee64bafc Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Mon, 23 Jun 2025 19:16:51 +0300 Subject: [PATCH 055/136] fix --- graphrag_sdk/models/openai.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index 8e4324fe..ffc3193d 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -1,6 +1,6 @@ import os from typing import Optional -from .litellm import LiteModel, LiteModelChatSession +from .litellm import LiteModel from .model import ( GenerativeModel, GenerativeModelConfig, From c12582fd25d36736bd50a5ad61be118d6a0acfc5 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 24 Jun 2025 17:42:57 +0300 Subject: [PATCH 056/136] update-usage --- .github/workflows/test.yml | 2 +- README.md | 12 +- examples/movies/demo-movies.ipynb | 48 ++- examples/trip/demo_orchestrator_trip.ipynb | 155 ++++---- examples/ufc/demo-ufc.ipynb | 393 +++++++++++++++++---- examples/ufc/ontology.json | 274 ++++++++++++-- graphrag_sdk/model_config.py | 42 +-- graphrag_sdk/models/azure_openai.py | 4 +- graphrag_sdk/models/gemini.py | 2 - graphrag_sdk/models/litellm.py | 14 +- graphrag_sdk/models/model.py | 16 +- graphrag_sdk/models/ollama.py | 2 - graphrag_sdk/models/openai.py | 4 +- tests/test_rag.py | 2 +- tests/test_streaming_response.py | 2 +- 15 files changed, 745 insertions(+), 227 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index b583d2dc..656bfda8 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -27,7 +27,7 @@ jobs: strategy: matrix: - model: [gemini/gemini-2.0-flash, openai/gpt-4o] # List of models + model: [openai/gpt-4.1] # List of models steps: - uses: actions/checkout@v4 diff --git a/README.md b/README.md index 4d3cad29..72825086 100644 --- a/README.md +++ b/README.md @@ -35,10 +35,10 @@ pip install graphrag_sdk[litellm] ### Configure Credentials. See [.env](.env.template) for examples. * [LiteLLM](https://docs.litellm.ai): A framework supporting inference of large language models, allowing flexibility in deployment and use cases. - To choose vendor use the prefix "specific_vendor/your_model", for example "gemini/gemini-2.0-flash". -* [OpenAI](https://openai.com/index/openai-api) Recommended model:`gpt-4o` + To choose vendor use the prefix "specific_vendor/your_model", for example "openai/gpt-4.1". +* [OpenAI](https://openai.com/index/openai-api) Recommended model:`gpt-4.1` * [Google](https://makersuite.google.com/app/apikey) Recommended model:`gemini-2.0-flash` -* [Azure-OpenAI](https://ai.azure.com) Recommended model:`gpt-4o` +* [Azure-OpenAI](https://ai.azure.com) Recommended model:`gpt-4.1` * [Ollama](https://ollama.com/) Available only to the Q&A step. Recommended models: `llama3`. Ollama models are suitable for the Q&A step only (after the knowledge graph (KG) created). @@ -68,8 +68,8 @@ urls = ["https://www.rottentomatoes.com/m/side_by_side_2012", sources = [URL(url) for url in urls] -# Model - vendor: gemini, model: gemini-2.0-flash -> gemini/gemini-2.0-flash -model = LiteModel(model_name="gemini/gemini-2.0-flash") +# Model - vendor: openai, model: gpt-4.1 -> openai/gpt-4.1 +model = LiteModel(model_name="openai/gpt-4.1") # Ontology Auto-Detection ontology = Ontology.from_sources( @@ -143,7 +143,7 @@ See the [Step 1](#how-to-use) section to understand how to create Knowledge Grap ```python # Define the model -model = LiteModel(model_name="gemini/gemini-2.0-flash") +model = LiteModel(model_name="openai/gpt-4.1") # Create the Knowledge Graph from the predefined ontology. # In this example, we will use the restaurants agent and the attractions agent. diff --git a/examples/movies/demo-movies.ipynb b/examples/movies/demo-movies.ipynb index 6b0d55c0..6ca2668b 100644 --- a/examples/movies/demo-movies.ipynb +++ b/examples/movies/demo-movies.ipynb @@ -22,7 +22,17 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/shubeli/miniconda3/envs/sdk/lib/python3.10/site-packages/pydantic/_internal/_config.py:345: UserWarning: Valid config keys have changed in V2:\n", + "* 'fields' has been removed\n", + " warnings.warn(message, UserWarning)\n" + ] + } + ], "source": [ "import os\n", "import logging\n", @@ -46,14 +56,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "# Get your Credentails from google website, see https://aistudio.google.com/\n", - "os.environ[\"GEMINI_API_KEY\"] = \"\"\n", + "# Set your OpenAI credential in .env file\n", + "# OPENAI_API_KEY=your_api_key\n", "\n", - "# Get your Credentails from Falkor website, see https://app.falkordb.cloud\n", + "# Get your Credentials from Falkor website, see https://app.falkordb.cloud\n", "falkor_host = \"\"\n", "falkor_port = None\n", "falkor_username = \"\"\n", @@ -96,11 +106,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Process Documents: 100%|██████████| 7/7 [00:43<00:00, 6.16s/it]\n" + ] + } + ], "source": [ - "model = LiteModel(model_name=\"gemini/gemini-2.0-flash\")\n", + "model = LiteModel(model_name=\"openai/gpt-4.1\")\n", "\n", "boundaries = \"\"\"\n", " Extract only the most relevant information about all the movies, actors, and directors over the text.\n", @@ -127,7 +145,15 @@ "cell_type": "code", "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Process Documents: 100%|██████████| 6/6 [00:59<00:00, 9.86s/it]\n" + ] + } + ], "source": [ "kg = KnowledgeGraph(\n", " name=\"movies\",\n", @@ -197,7 +223,7 @@ ], "metadata": { "kernelspec": { - "display_name": "graphrag-sdk-ceBr3E7y-py3.12", + "display_name": "sdk", "language": "python", "name": "python3" }, @@ -211,7 +237,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.3" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/examples/trip/demo_orchestrator_trip.ipynb b/examples/trip/demo_orchestrator_trip.ipynb index 989197f3..b99d101c 100644 --- a/examples/trip/demo_orchestrator_trip.ipynb +++ b/examples/trip/demo_orchestrator_trip.ipynb @@ -15,14 +15,23 @@ "metadata": {}, "outputs": [], "source": [ - "!pip install graphrag_sdk[openai]" + "!pip install graphrag_sdk[litellm]" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/shubeli/miniconda3/envs/sdk/lib/python3.10/site-packages/pydantic/_internal/_config.py:345: UserWarning: Valid config keys have changed in V2:\n", + "* 'fields' has been removed\n", + " warnings.warn(message, UserWarning)\n" + ] + }, { "data": { "text/plain": [ @@ -39,7 +48,7 @@ "from dotenv import load_dotenv\n", "from graphrag_sdk.orchestrator import Orchestrator\n", "from graphrag_sdk.agents.kg_agent import KGAgent\n", - "from graphrag_sdk.models.openai import OpenAiGenerativeModel\n", + "from graphrag_sdk.models.litellm import LiteModel\n", "from graphrag_sdk import (\n", " Ontology, Entity, Relation, Attribute, AttributeType, KnowledgeGraph, KnowledgeGraphModelConfig\n", ")\n", @@ -48,7 +57,8 @@ "load_dotenv()\n", "\n", "# Configuration\n", - "# OPENAI_API_KEY = \"sk-\"# OpenAI API key" + "# Set your OpenAI credential in .env file\n", + "# OPENAI_API_KEY=your_api_key" ] }, { @@ -247,12 +257,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Define the model\n", - "model = OpenAiGenerativeModel(\"gpt-4o\")\n", + "# Using OpenAI with gpt-4.1 as default (temperature=0 by default)\n", + "model = LiteModel()\n", "\n", "# Create the KG from the predefined ontology.\n", "# Restaurants KG\n", @@ -359,7 +370,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -389,13 +400,15 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ + "model_orchestrator = LiteModel(\"o3-mini\")\n", + "\n", "# Initialize the orchestrator and register agents\n", "orchestrator = Orchestrator(\n", - " model,\n", + " model_orchestrator,\n", " backstory=\"You are a trip planner, and you want to provide the best possible itinerary for your clients.\",\n", ")\n", "orchestrator.register_agent(restaurants_agent)\n", @@ -407,42 +420,53 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Certainly! Here's a detailed two-day itinerary for your trip to Rome, ensuring you make the most out of your visit to this historically rich and vibrant city. We’ve arranged a balanced mix of iconic attractions and delightful dining experiences for your enjoyment.\n", + "Dear Traveler,\n", + "\n", + "Here is your detailed two-day itinerary for a memorable trip to Rome, designed to help you experience the city's rich history, culture, and culinary delights. I’ve combined the top attractions with excellent dining recommendations to ensure you have a well-rounded experience.\n", + "\n", + "────────────────────────────\n", + "Day 1:\n", + "────────────────────────────\n", + "• Morning – Begin your day with a visit to the Colosseum. This iconic ancient amphitheater not only offers a glimpse into the grandeur of ancient Rome but also provides a stirring reminder of the gladiatorial contests and public spectacles that once took place there.\n", + "\n", + "• Afternoon – Head over to the Vatican Museums. This renowned collection of art and historical artifacts, accumulated by Popes over centuries, is a must-see. The museums offer fascinating insights into Renaissance art and history, making it a perfect cultural stop.\n", "\n", - "**Day 1: Discovering Ancient Rome and Modern Flavors**\n", - "- **Morning: Colosseum**\n", - " Start your day by visiting the Colosseum, the iconic ancient amphitheater known for its gladiatorial contests and grand spectacles. Allow yourself a few hours to explore the structure and absorb the rich history of ancient Rome that it represents.\n", + "• Lunch Suggestion – Enjoy lunch at Trattoria da Enzo. This well-loved eatery is known for its traditional Roman dishes and warm, inviting atmosphere, making it an ideal spot to recharge after your cultural explorations.\n", "\n", - "- **Lunch: Tonnarello**\n", - " After exploring, head to Tonnarello, a restaurant praised for its casual ambiance and delicious Roman cuisine. Enjoy dishes like homemade pasta and meatballs while soaking in the atmosphere of authentic Roman hospitality. \n", + "• Evening – Conclude the day with a leisurely stroll to the Trevi Fountain. As you admire its exquisite Baroque artistry, take part in the charming tradition of tossing a coin for good luck.\n", "\n", - "- **Afternoon: Trevi Fountain**\n", - " Rejuvenated from lunch, stroll towards the Trevi Fountain. This Baroque masterpiece not only offers stunning sculptures but also the tradition of coin tossing, promising a future return trip to Rome.\n", + "• Dinner Suggestion – For dinner, consider dining at Il Pagliaccio, a Michelin-starred restaurant offering contemporary Italian cuisine, which promises a refined dining experience to cap off your day.\n", "\n", - "- **Dinner: Il Pagliaccio**\n", - " Conclude your first day with dinner at Il Pagliaccio. This Michelin-starred restaurant offers a contemporary Italian dining experience, perfect for indulging in exquisite flavors and creative dishes.\n", + "────────────────────────────\n", + "Day 2:\n", + "────────────────────────────\n", + "• Morning – Start your day with a visit to the Basilica di Santa Maria Maggiore. This magnificent basilica, celebrated for its rich history and impressive architecture, provides a serene and inspiring start to your morning.\n", "\n", - "**Day 2: Religious Artistry and Cozy Feasts**\n", - "- **Morning: Vatican Museums**\n", - " Begin your second day by exploring the Vatican Museums, home to centuries of art collected by the Popes. Allocate sufficient time here to truly appreciate the vast collections, including the Sistine Chapel's renowned ceiling.\n", + "• Afternoon – Spend your afternoon revisiting your favorite spots from Day 1 or simply enjoy a relaxed, wandering walk through Rome’s picturesque historic streets. This free time allows you to soak in the city’s atmosphere at your own pace.\n", "\n", - "- **Lunch: Trattoria da Enzo**\n", - " For a cozy and traditional Roman dining experience, visit Trattoria da Enzo. Known for its welcoming atmosphere and scrumptious local dishes, it provides the perfect lunchtime escape.\n", + "• Lunch Suggestion – For a casual yet satisfying meal, try Tonnarello. This local restaurant offers authentic Roman dishes like pasta and meatballs, perfect for a midday break with a welcoming ambiance.\n", "\n", - "- **Afternoon: Basilica di Santa Maria Maggiore**\n", - " Spend your afternoon visiting the Basilica di Santa Maria Maggiore. This major basilica is renowned for its impressive architecture and deep historical roots, representing a significant piece of Rome's religious heritage.\n", + "• Evening – Unwind by relaxing at a local café. Enjoy a leisurely evening soak in the Mediterranean atmosphere, reflecting on your experiences and the vibrant life of Rome.\n", "\n", - "- **Evening: Stroll through Rome**\n", - " Conclude your Roman adventure with a leisurely evening walk through the city's streets, taking in the lively Italian spirit as you reminisce over the sights and experiences from the past two days.\n", + "• Dinner Suggestion – You have the option for dinner at either Il Pagliaccio for a fine dining experience or Trattoria da Enzo if you prefer a more traditional Roman meal. Both options promise delightful flavors and excellent service.\n", "\n", - "This itinerary ensures a wonderful balance between exploration of Rome's historical grandeur and indulgence in its exquisite culinary offerings. Enjoy your trip!\n" + "────────────────────────────\n", + "Reasoning Behind the Itinerary:\n", + "• Historical and Cultural Immersion: Visits to classic landmarks such as the Colosseum, Vatican Museums, and Basilica di Santa Maria Maggiore ensure you experience Rome's rich history and art.\n", + "• Culinary Experiences: Restaurant recommendations have been carefully selected to provide both traditional Roman cuisine and modern, refined dining experiences, catering to varying moods and palates.\n", + "• Balanced Timing: The itinerary is structured to provide a mix of guided tours and personal leisure time, allowing you to explore at your own pace while still taking in the must-see attractions.\n", + "\n", + "I hope this itinerary meets your expectations and helps you enjoy a truly engaging and delicious trip to Rome. Enjoy your travels and feel free to refer back to this plan whenever you need inspiration during your visit!\n", + "\n", + "Best wishes for a wonderful journey,\n", + "Your Trip Planning Team\n" ] } ], @@ -452,14 +476,21 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Certainly! Based on the two-day itinerary for Rome that was previously provided to you, the restaurant mentioned for dinner on the first day is \"Il Pagliaccio.\" This restaurant is renowned for its elegant ambiance and Michelin-starred contemporary Italian cuisine, offering a perfect dining experience to conclude your day of exploring ancient Rome. Enjoy your dinner and the remarkable culinary delights it has to offer!\n" + "Dear Traveler,\n", + "\n", + "Thank you for your inquiry. Based on the itinerary details provided, the recommended restaurant for dinner on Day 1 is \"Il Pagliaccio.\" This Michelin-starred restaurant was selected for its elegant ambiance and contemporary Italian cuisine, ensuring a refined dining experience that complements the rich cultural exploration of your trip.\n", + "\n", + "I hope this clear and concise response helps you in planning your dining experience. Enjoy your journey and the delightful culinary offerings of Rome!\n", + "\n", + "Best regards,\n", + "Your Trip Planning Team\n" ] } ], @@ -470,42 +501,41 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Certainly! I've updated your two-day itinerary for Rome with a new dinner option for the first day. Here is the revised itinerary:\n", - "\n", - "**Day 1: Discovering Ancient Rome and Modern Flavors**\n", - "- **Morning: Colosseum**\n", - " Begin your day with a visit to the iconic Colosseum, where you'll delve into the historical essence of ancient Rome. Take a few hours to explore this magnificent structure and the stories it holds about the past.\n", + "Dear Traveler,\n", "\n", - "- **Lunch: Tonnarello**\n", - " Enjoy your lunch at Tonnarello, a restaurant highly praised for its casual ambiance and delicious Roman cuisines such as pasta and meatballs. This spot also features patio seating and acoustic guitar, enhancing your dining experience.\n", + "Thank you for your request. I have updated your itinerary by replacing the original Day 1 dinner restaurant with an alternative option. Please find your updated itinerary below:\n", "\n", - "- **Afternoon: Trevi Fountain**\n", - " After lunch, take a leisurely walk to the Trevi Fountain. Revel in the beauty of this Baroque masterpiece, famous for its stunning sculptures and the tradition of tossing a coin for a promise to return.\n", + "────────────────────────────\n", + "Day 1:\n", + "────────────────────────────\n", + "• Lunch – Enjoy a delightful meal at Trattoria da Enzo, a cozy trattoria celebrated for its traditional Roman dishes and warm atmosphere.\n", "\n", - "- **Dinner: Tonnarello (Alternative choice)**\n", - " For dinner, continue enjoying the delightful offerings at Tonnarello. With its refreshing and laid-back atmosphere, you can relish more of their simple yet satisfying Roman dishes, ensuring a memorable end to your day.\n", + "• Dinner – For dinner, you'll now have the chance to experience Tonnarello, a charming restaurant offering a casual setting with delicious pasta, meatballs, and other classic Roman dishes. This venue features patio seating accompanied by acoustic guitar, providing a relaxed yet engaging dining experience.\n", "\n", - "**Day 2: Religious Artistry and Cozy Feasts**\n", - "- **Morning: Vatican Museums**\n", - " Begin your second day by exploring the Vatican Museums, where vast collections of art amassed by the Popes await you. Take your time to appreciate these historical artifacts, including the Sistine Chapel's awe-inspiring ceiling.\n", + "────────────────────────────\n", + "Day 2:\n", + "────────────────────────────\n", + "• Lunch – Once again, Tonnarello offers a satisfying meal with its array of authentic Roman dishes, ideal for a casual stop.\n", "\n", - "- **Lunch: Trattoria da Enzo**\n", - " Experience a cozy and traditional Roman ambiance at Trattoria da Enzo for lunch. Known for its welcoming atmosphere and scrumptious local dishes, it serves as a perfect midday retreat.\n", + "• Dinner – Conclude your Day 2 dining experience at Trattoria da Enzo, which ensures you continue to enjoy the comfort and traditional flavors of Roman cuisine.\n", "\n", - "- **Afternoon: Basilica di Santa Maria Maggiore**\n", - " Spend the afternoon at the Basilica di Santa Maria Maggiore. This basilica is celebrated for its impressive architecture and historical significance, providing a deep dive into Rome's religious heritage.\n", + "────────────────────────────\n", + "Reasoning Behind the Update:\n", + "• By replacing the Day 1 dinner restaurant with Tonnarello, the itinerary now offers variety and caters to a preference for a more casual dining environment with a lively ambiance.\n", + "• The updated plan maintains a balanced culinary experience by mixing both traditional and casual dining options, giving you a more diverse taste of Rome’s vibrant food culture.\n", + "• The overall itinerary is structured to enhance your travel experience while allowing you to immerse yourself in the local flavors and atmosphere of Rome.\n", "\n", - "- **Evening: Stroll through Rome**\n", - " End your Roman adventure with a relaxed evening stroll through the city's lively streets, taking in the sights and sounds while reminiscing about your enriching experiences over the past two days.\n", + "I hope you enjoy this updated itinerary and that it meets your expectations. Have a wonderful trip and enjoy every moment of your Roman adventure!\n", "\n", - "This updated itinerary ensures you have a fulfilled and delightful experience while exploring the cultural and culinary richness of Rome. Enjoy your trip!\n" + "Best regards,\n", + "Your Trip Planning Team\n" ] } ], @@ -516,26 +546,33 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Certainly! For the two-day itinerary in Rome that was previously provided, the attraction mentioned for the morning on the first day is the **Colosseum**. This iconic ancient amphitheater is known for its gladiatorial contests and grand spectacles, making it a must-see when exploring the history and culture of ancient Rome. Visiting the Colosseum allows you to delve into Rome's fascinating past and appreciate the architectural marvels and historical significance of this world-renowned site. Enjoy your exploration of this magnificent landmark!\n" + "Dear Traveler,\n", + "\n", + "Thank you for your inquiry. Based on the itinerary details, the attraction scheduled for the morning of Day 1 is the Colosseum. The Colosseum, an iconic monument of ancient Rome, was chosen as it provides a firsthand look into the rich history and architectural prowess of the Roman Empire, setting a perfect tone for your day of exploration.\n", + "\n", + "I hope this detailed explanation helps you understand your itinerary better. Enjoy your visit to this magnificent historical site and have a wonderful trip!\n", + "\n", + "Best regards,\n", + "Your Trip Planning Team\n" ] } ], "source": [ - "runner = orchestrator.ask(\"Please tell me attraction on the morning at the first day that you mention in the itinerary of the trip\")\n", + "runner = orchestrator.ask(\"Please tell me the attraction on the morning at the first day that you mention in the itinerary of the trip\")\n", "print(runner.output)" ] } ], "metadata": { "kernelspec": { - "display_name": "graphrag-sdk-ceBr3E7y-py3.12", + "display_name": "sdk", "language": "python", "name": "python3" }, @@ -549,7 +586,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.3" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/examples/ufc/demo-ufc.ipynb b/examples/ufc/demo-ufc.ipynb index 43eca283..2fa95529 100644 --- a/examples/ufc/demo-ufc.ipynb +++ b/examples/ufc/demo-ufc.ipynb @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -29,7 +29,7 @@ "True" ] }, - "execution_count": 2, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -41,14 +41,15 @@ "from dotenv import load_dotenv\n", "from graphrag_sdk.source import Source\n", "from graphrag_sdk import KnowledgeGraph, Ontology\n", - "from graphrag_sdk.models.openai import OpenAiGenerativeModel\n", + "from graphrag_sdk.models.litellm import LiteModel\n", "from graphrag_sdk.model_config import KnowledgeGraphModelConfig\n", "\n", "# Load environment variables\n", "load_dotenv()\n", "\n", "# Configuration\n", - "# OPENAI_API_KEY = \"sk-\"# OpenAI API key" + "# Set your OpenAI credential in .env file\n", + "# OPENAI_API_KEY = \"your-api-key\"" ] }, { @@ -62,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -88,7 +89,15 @@ "cell_type": "code", "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Process Documents: 100%|██████████| 2/2 [00:35<00:00, 17.79s/it]\n" + ] + } + ], "source": [ "# Define the percentage of files that will be used to auto-create the ontology.\n", "percent = 0.1 # This represents 10%. You can adjust this value (e.g., 0.2 for 20%).\n", @@ -99,7 +108,8 @@ "\"\"\"\n", "\n", "# Define the model to be used for the ontology\n", - "model = OpenAiGenerativeModel(model_name=\"gpt-4o\")\n", + "# Using OpenAI with gpt-4.1 as default (temperature=0 by default)\n", + "model = LiteModel()\n", "\n", "# Randomly select a percentage of files from sources.\n", "sampled_sources = random.sample(sources, round(len(sources) * percent))\n", @@ -134,7 +144,7 @@ "{\n", " \"entities\": [\n", " {\n", - " \"label\": \"Person\",\n", + " \"label\": \"Event\",\n", " \"attributes\": [\n", " {\n", " \"name\": \"name\",\n", @@ -143,46 +153,40 @@ " \"required\": true\n", " },\n", " {\n", - " \"name\": \"nickname\",\n", + " \"name\": \"date\",\n", " \"type\": \"string\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"location\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", " }\n", " ],\n", " \"description\": \"\"\n", " },\n", " {\n", - " \"label\": \"FightEvent\",\n", + " \"label\": \"Fight\",\n", " \"attributes\": [\n", " {\n", - " \"name\": \"name\",\n", + " \"name\": \"fight_id\",\n", " \"type\": \"string\",\n", " \"unique\": true,\n", " \"required\": true\n", " },\n", " {\n", - " \"name\": \"date\",\n", - " \"type\": \"string\",\n", + " \"name\": \"title_bout\",\n", + " \"type\": \"boolean\",\n", " \"unique\": false,\n", " \"required\": true\n", " },\n", " {\n", - " \"name\": \"location\",\n", - " \"type\": \"string\",\n", - " \"unique\": false,\n", - " \"required\": true\n", - " }\n", - " ],\n", - " \"description\": \"\"\n", - " },\n", - " {\n", - " \"label\": \"Bout\",\n", - " \"attributes\": [\n", - " {\n", " \"name\": \"weight_class\",\n", " \"type\": \"string\",\n", " \"unique\": false,\n", - " \"required\": true\n", + " \"required\": false\n", " },\n", " {\n", " \"name\": \"method\",\n", @@ -206,127 +210,376 @@ " \"name\": \"time_format\",\n", " \"type\": \"string\",\n", " \"unique\": false,\n", - " \"required\": true\n", + " \"required\": false\n", " },\n", " {\n", - " \"name\": \"referee\",\n", + " \"name\": \"details\",\n", " \"type\": \"string\",\n", " \"unique\": false,\n", " \"required\": false\n", " }\n", " ],\n", " \"description\": \"\"\n", - " }\n", - " ],\n", - " \"relations\": [\n", + " },\n", " {\n", - " \"label\": \"FOUGHT_IN\",\n", - " \"source\": {\n", - " \"label\": \"Person\"\n", - " },\n", - " \"target\": {\n", - " \"label\": \"Bout\"\n", - " },\n", + " \"label\": \"Person\",\n", " \"attributes\": [\n", " {\n", - " \"name\": \"result\",\n", + " \"name\": \"name\",\n", + " \"type\": \"string\",\n", + " \"unique\": true,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"nickname\",\n", " \"type\": \"string\",\n", " \"unique\": false,\n", + " \"required\": false\n", + " }\n", + " ],\n", + " \"description\": \"\"\n", + " },\n", + " {\n", + " \"label\": \"Referee\",\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"name\",\n", + " \"type\": \"string\",\n", + " \"unique\": true,\n", + " \"required\": true\n", + " }\n", + " ],\n", + " \"description\": \"\"\n", + " },\n", + " {\n", + " \"label\": \"FightStatistics\",\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"statistics_id\",\n", + " \"type\": \"string\",\n", + " \"unique\": true,\n", " \"required\": true\n", " },\n", " {\n", " \"name\": \"knockdowns\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"significant_strikes\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"significant_strikes_attempted\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"significant_strikes_percentage\",\n", - " \"type\": \"string\",\n", + " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"total_strikes\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"total_strikes_attempted\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"takedowns\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"takedowns_attempted\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"takedown_percentage\",\n", - " \"type\": \"string\",\n", + " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"submissions_attempted\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"passes\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", - " \"required\": false\n", + " \"required\": true\n", " },\n", " {\n", " \"name\": \"reversals\",\n", " \"type\": \"number\",\n", " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ],\n", + " \"description\": \"\"\n", + " },\n", + " {\n", + " \"label\": \"RoundStatistics\",\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"round_statistics_id\",\n", + " \"type\": \"string\",\n", + " \"unique\": true,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"round_number\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"knockdowns\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"significant_strikes\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"significant_strikes_attempted\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"significant_strikes_percentage\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"takedown_percentage\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"submissions_attempted\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"reversals\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ],\n", + " \"description\": \"\"\n", + " },\n", + " {\n", + " \"label\": \"SignificantStrikeBreakdown\",\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"breakdown_id\",\n", + " \"type\": \"string\",\n", + " \"unique\": true,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"head\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"body\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"leg\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"distance\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"clinch\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " },\n", + " {\n", + " \"name\": \"ground\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ],\n", + " \"description\": \"\"\n", + " }\n", + " ],\n", + " \"relations\": [\n", + " {\n", + " \"label\": \"HOSTED\",\n", + " \"source\": {\n", + " \"label\": \"Event\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"Fight\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"main_event\",\n", + " \"type\": \"boolean\",\n", + " \"unique\": false,\n", " \"required\": false\n", " }\n", " ]\n", " },\n", " {\n", - " \"label\": \"PART_OF_EVENT\",\n", + " \"label\": \"PARTICIPATED\",\n", " \"source\": {\n", - " \"label\": \"Bout\"\n", + " \"label\": \"Person\"\n", " },\n", " \"target\": {\n", - " \"label\": \"FightEvent\"\n", + " \"label\": \"Fight\"\n", " },\n", - " \"attributes\": []\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"result\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ]\n", " },\n", " {\n", - " \"label\": \"PART_OF\",\n", + " \"label\": \"OFFICIATED\",\n", " \"source\": {\n", - " \"label\": \"Bout\"\n", + " \"label\": \"Referee\"\n", " },\n", " \"target\": {\n", - " \"label\": \"FightEvent\"\n", + " \"label\": \"Fight\"\n", " },\n", - " \"attributes\": []\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"role\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"label\": \"HAS_STATISTICS\",\n", + " \"source\": {\n", + " \"label\": \"Fight\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"FightStatistics\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"fighter_name\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"label\": \"HAS_ROUND_STATISTICS\",\n", + " \"source\": {\n", + " \"label\": \"Fight\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"RoundStatistics\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"fighter_name\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"label\": \"HAS_BREAKDOWN\",\n", + " \"source\": {\n", + " \"label\": \"FightStatistics\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"SignificantStrikeBreakdown\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"round_number\",\n", + " \"type\": \"number\",\n", + " \"unique\": false,\n", + " \"required\": false\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"label\": \"HAS_ROUND_BREAKDOWN\",\n", + " \"source\": {\n", + " \"label\": \"RoundStatistics\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"SignificantStrikeBreakdown\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"breakdown_id\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": true\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"label\": \"PARTICIPATED_AS_REFEREE\",\n", + " \"source\": {\n", + " \"label\": \"Referee\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"Event\"\n", + " },\n", + " \"attributes\": [\n", + " {\n", + " \"name\": \"role\",\n", + " \"type\": \"string\",\n", + " \"unique\": false,\n", + " \"required\": false\n", + " }\n", + " ]\n", " }\n", " ]\n", "}\n" @@ -350,7 +603,15 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Process Documents: 100%|██████████| 8/8 [01:18<00:00, 9.77s/it]\n" + ] + } + ], "source": [ "# After approving the ontology, load it from disk.\n", "ontology_file = \"ontology.json\"\n", @@ -383,8 +644,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'question': 'Who is Salsa Boy?', 'response': 'Waldo Cortes-Acosta is Salsa Boy.', 'context': '[[\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\']]', 'cypher': \"MATCH (p:Person) WHERE p.nickname CONTAINS 'Salsa Boy' RETURN p\"}\n", - "{'question': 'Tell me about one of his fights?', 'response': 'Waldo Cortes-Acosta, also known as Salsa Boy, fought in a bout at UFC 284: Makhachev vs. Volkanovski, held on February 11, 2023, in Perth, Western Australia, Australia. He won the fight by submission in the second round, at 4:05. In this fight, he displayed impressive skills with 52 significant strikes out of 101 attempted, achieving a 51.49% success rate. He also attempted 4 takedowns, successfully completing 3 for a 75.00% success rate, and attempted 1 submission.', 'context': '[[\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\', \\'()-[:FOUGHT_IN{knockdowns:0,passes:0,result:\"Win\",reversals:0,significant_strikes:52,significant_strikes_attempted:101,significant_strikes_percentage:\"51.49%\",submissions_attempted:1,takedown_percentage:\"75.00%\",takedowns:3,takedowns_attempted:4,total_strikes:130,total_strikes_attempted:204}]->()\\', \\'(:Bout{method:\"Submission\",referee:\"Osiris Maia\",round:2,time:\"4:05\",time_format:\"3 Rounds (5-5-5)\",weight_class:\"Lightweight\"})\\', \\'(:FightEvent{date:\"2023-02-11\",location:\"Perth, Western Australia, Australia\",name:\"UFC 284: Makhachev vs. Volkanovski\"})\\']]', 'cypher': \"MATCH (p:Person)-[f:FOUGHT_IN]->(b:Bout)-[:PART_OF_EVENT]->(e:FightEvent) WHERE p.nickname CONTAINS 'Salsa Boy' RETURN p, f, b, e LIMIT 1\"}\n" + "{'question': 'Who is Salsa Boy?', 'response': 'Salsa Boy is Waldo Cortes-Acosta.', 'context': '[[\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\']]', 'cypher': \"\\nMATCH (p:Person)\\nWHERE p.nickname CONTAINS 'Salsa Boy'\\nRETURN p\\n\"}\n", + "{'question': 'Tell me about one of his fights?', 'response': 'Waldo Cortes-Acosta, also known as Salsa Boy, fought Lukasz Brzeski at UFC Fight Night: Holloway vs. The Korean Zombie on August 26, 2023. He won the fight by KO/TKO with punches to the head at distance in the first round at 3:01. The bout was in the Heavyweight division and was scheduled for 3 rounds.', 'context': '[[\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\', \\'()-[:PARTICIPATED{result:\"Win\"}]->()\\', \\'(:Fight{details:\"Punches to Head At Distance\",fight_id:\"Waldo Cortes-Acosta v Lukasz Brzeski UFC Fight Night: Holloway vs. The Korean Zombie 2023-08-26\",method:\"KO/TKO\",round:1,time:\"3:01\",time_format:\"3 Rounds (5-5-5)\",title_bout:False,weight_class:\"Heavyweight\"})\\'], [\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\', \\'()-[:PARTICIPATED{result:\"Win\"}]->()\\', \\'(:Fight{details:\"Decision\",fight_id:\"Arlovski_vs_Cortes-Acosta_UFCFN_2024-01-13\",method:\"Decision - Unanimous\",round:3,time:\"5:00\",time_format:\"3 Rounds (5-5-5)\",title_bout:False,weight_class:\"Heavyweight\"})\\'], [\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\', \\'()-[:PARTICIPATED{result:\"Win\"}]->()\\', \\'(:Fight{details:\"Decision\",fight_id:\"WaldoCortesAcosta_vs_RobelisDespaigne_UFCFN_Lewis_Nascimento_2024-05-11\",method:\"Decision - Unanimous\",round:3,time:\"5:00\",time_format:\"3 Rounds (5-5-5)\",title_bout:False,weight_class:\"Heavyweight\"})\\'], [\\'(:Person{name:\"Waldo Cortes-Acosta\",nickname:\"Salsa Boy\"})\\', \\'()-[:PARTICIPATED{result:\"Loss\"}]->()\\', \\'(:Fight{details:\"Decision\",fight_id:\"MarcosRogerioDeLima_vs_WaldoCortesAcosta_UFCFightNightSongVsSimon_2023-04-29\",method:\"Decision - Unanimous\",round:3,time:\"5:00\",time_format:\"3 Rounds (5-5-5)\",title_bout:False,weight_class:\"Heavyweight\"})\\']]', 'cypher': \"\\nMATCH (p:Person)-[pa:PARTICIPATED]->(f:Fight)\\nWHERE p.name CONTAINS 'Waldo Cortes-Acosta'\\nRETURN p, pa, f\\n\"}\n" ] } ], @@ -400,7 +661,7 @@ ], "metadata": { "kernelspec": { - "display_name": "graphrag-sdk-ceBr3E7y-py3.12", + "display_name": "sdk", "language": "python", "name": "python3" }, @@ -414,7 +675,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.3" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/examples/ufc/ontology.json b/examples/ufc/ontology.json index 8565fe68..d0ee2570 100644 --- a/examples/ufc/ontology.json +++ b/examples/ufc/ontology.json @@ -4,7 +4,7 @@ "label": "Event", "attributes": [ { - "name": "title", + "name": "name", "type": "string", "unique": true, "required": true @@ -28,11 +28,23 @@ "label": "Fight", "attributes": [ { - "name": "title", + "name": "fight_id", "type": "string", "unique": true, "required": true }, + { + "name": "title_bout", + "type": "boolean", + "unique": false, + "required": true + }, + { + "name": "weight_class", + "type": "string", + "unique": false, + "required": false + }, { "name": "method", "type": "string", @@ -40,28 +52,34 @@ "required": true }, { - "name": "rounds", + "name": "round", "type": "number", "unique": false, "required": true }, { - "name": "referee", + "name": "time", "type": "string", "unique": false, "required": true }, { - "name": "result_details", + "name": "time_format", "type": "string", "unique": false, - "required": true + "required": false + }, + { + "name": "details", + "type": "string", + "unique": false, + "required": false } ], "description": "" }, { - "label": "Fighter", + "label": "Person", "attributes": [ { "name": "name", @@ -74,11 +92,17 @@ "type": "string", "unique": false, "required": false - }, + } + ], + "description": "" + }, + { + "label": "Referee", + "attributes": [ { - "name": "outcome", + "name": "name", "type": "string", - "unique": false, + "unique": true, "required": true } ], @@ -88,7 +112,7 @@ "label": "FightStatistics", "attributes": [ { - "name": "fighter_name", + "name": "statistics_id", "type": "string", "unique": true, "required": true @@ -167,48 +191,252 @@ } ], "description": "" + }, + { + "label": "RoundStatistics", + "attributes": [ + { + "name": "round_statistics_id", + "type": "string", + "unique": true, + "required": true + }, + { + "name": "round_number", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "knockdowns", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "significant_strikes", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "significant_strikes_attempted", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "significant_strikes_percentage", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "takedown_percentage", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "submissions_attempted", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "reversals", + "type": "number", + "unique": false, + "required": true + } + ], + "description": "" + }, + { + "label": "SignificantStrikeBreakdown", + "attributes": [ + { + "name": "breakdown_id", + "type": "string", + "unique": true, + "required": true + }, + { + "name": "head", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "body", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "leg", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "distance", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "clinch", + "type": "number", + "unique": false, + "required": true + }, + { + "name": "ground", + "type": "number", + "unique": false, + "required": true + } + ], + "description": "" } ], "relations": [ { - "label": "PART_OF", + "label": "HOSTED", "source": { + "label": "Event" + }, + "target": { "label": "Fight" }, + "attributes": [ + { + "name": "main_event", + "type": "boolean", + "unique": false, + "required": false + } + ] + }, + { + "label": "PARTICIPATED", + "source": { + "label": "Person" + }, "target": { - "label": "Event" + "label": "Fight" }, - "attributes": [] + "attributes": [ + { + "name": "result", + "type": "string", + "unique": false, + "required": true + } + ] }, { - "label": "PARTICIPATED_IN", + "label": "OFFICIATED", "source": { - "label": "Fighter" + "label": "Referee" }, "target": { "label": "Fight" }, - "attributes": [] + "attributes": [ + { + "name": "role", + "type": "string", + "unique": false, + "required": true + } + ] }, { - "label": "RELATED_STATS", + "label": "HAS_STATISTICS", "source": { - "label": "FightStatistics" + "label": "Fight" }, "target": { - "label": "Fighter" + "label": "FightStatistics" }, - "attributes": [] + "attributes": [ + { + "name": "fighter_name", + "type": "string", + "unique": false, + "required": true + } + ] }, { - "label": "HAS_STATS", + "label": "HAS_ROUND_STATISTICS", "source": { "label": "Fight" }, "target": { + "label": "RoundStatistics" + }, + "attributes": [ + { + "name": "fighter_name", + "type": "string", + "unique": false, + "required": true + } + ] + }, + { + "label": "HAS_BREAKDOWN", + "source": { "label": "FightStatistics" }, - "attributes": [] + "target": { + "label": "SignificantStrikeBreakdown" + }, + "attributes": [ + { + "name": "round_number", + "type": "number", + "unique": false, + "required": false + } + ] + }, + { + "label": "HAS_ROUND_BREAKDOWN", + "source": { + "label": "RoundStatistics" + }, + "target": { + "label": "SignificantStrikeBreakdown" + }, + "attributes": [ + { + "name": "breakdown_id", + "type": "string", + "unique": false, + "required": true + } + ] + }, + { + "label": "PARTICIPATED_AS_REFEREE", + "source": { + "label": "Referee" + }, + "target": { + "label": "Event" + }, + "attributes": [ + { + "name": "role", + "type": "string", + "unique": false, + "required": false + } + ] } ] } \ No newline at end of file diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index 8995f8df..c806c0e0 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -1,5 +1,5 @@ -from graphrag_sdk.models import (GenerativeModel, - GenerativeModelConfig) +import copy +from graphrag_sdk.models import GenerativeModel class KnowledgeGraphModelConfig: @@ -27,6 +27,9 @@ def __init__( cypher_generation (GenerativeModel): The generative model for Cypher query generation. qa (GenerativeModel): The generative model for question answering. """ + # Ensure the extract_data model is configured for structured data extraction + extract_data.generation_config.response_format = {"type": "json_object"} + self.extract_data = extract_data self.cypher_generation = cypher_generation self.qa = qa @@ -36,8 +39,7 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ Creates a new KnowledgeGraphModelConfig instance with the given generative model. - The extract_data model will be configured with temperature=0 and JSON response format - for structured data extraction. + The extract_data model will be configured with JSON response format for structured data extraction. Args: model (GenerativeModel): The generative model to use. @@ -45,33 +47,11 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": Returns: KnowledgeGraphModelConfig: The new KnowledgeGraphModelConfig instance. - """ - # Take user's existing config and modify for extract_data - config_dict = model.generation_config.to_json() - - # Check if temperature was explicitly set by the user - if model.generation_config._temperature_was_set: - # User explicitly set temperature (even if to None), only override if not None - if model.generation_config.temperature is not None: - config_dict['temperature'] = 0 - # If user explicitly set temperature=None, respect that and don't override - else: - # User didn't set temperature (using default None), override to 0 - config_dict['temperature'] = 0 - # Add JSON output format - config_dict['response_format'] = {"type": "json_object"} - extract_config = GenerativeModelConfig.from_json(config_dict) - - # Create extract_data model with specialized configuration - try: - extract_data_model = model.__class__( - model_name=model.model_name, - generation_config=extract_config, - system_instruction=model.system_instruction - ) - except Exception: - # Fallback: use original model if creation fails - extract_data_model = model + """ + # Ensure the extract_data model is configured for structured data extraction + extract_data_model = copy.deepcopy(model) + extract_data_model.generation_config.response_format = {"type": "json_object"} + return KnowledgeGraphModelConfig( extract_data=extract_data_model, diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index cef0362e..f57c85af 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -19,7 +19,7 @@ class AzureOpenAiGenerativeModel(GenerativeModel): def __init__( self, - model_name: str, + model_name: str = "gpt-4.1", generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, **kwargs: Any, @@ -36,8 +36,6 @@ def __init__( # Convert to LiteLLM format lite_model_name = f"azure/{model_name}" - generation_config = generation_config or GenerativeModelConfig() - # Create internal LiteLLM model self._lite_model = LiteModel( model_name=lite_model_name, diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 05aef1ff..464d1be1 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -32,8 +32,6 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"gemini/{model_name}" - - generation_config = generation_config or GenerativeModelConfig() # Create internal LiteLLM model self._lite_model = LiteModel( diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index a7a507ac..d5ffe5e9 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -20,7 +20,7 @@ class LiteModel(GenerativeModel): def __init__( self, - model_name: str, + model_name: str = "openai/gpt-4.1", generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, additional_params: Optional[dict] = None, @@ -30,13 +30,13 @@ def __init__( LiteLLM model_name format: / Examples: - - openai/gpt-4o - - azure/gpt-4o + - openai/gpt-4.1 + - azure/gpt-4.1 - gemini/gemini-1.5-pro - ollama/llama3:8b Args: - model_name (str): The name and the provider for the LiteLLM client. + model_name (str): The name and the provider for the LiteLLM client. Defaults to "openai/gpt-4.1". generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): Instruction to guide the model. additional_params (Optional[dict]): Additional provider-specific parameters. @@ -54,8 +54,12 @@ def __init__( if not self.check_valid_key(model_name): raise ValueError(f"Invalid keys for model {model_name}.") - + if self.model_name == "gpt-4.1": + # Set default temperature to 0 for gpt-4.1 + if generation_config is None: + generation_config = GenerativeModelConfig(temperature=0) self.generation_config = generation_config or GenerativeModelConfig() + self.system_instruction = system_instruction self.additional_params = additional_params or {} diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index 74d897af..4580c923 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -31,13 +31,10 @@ class GenerativeModelConfig: >>> config.to_json() {'temperature': 0.5, 'max_tokens': 100} """ - - # Sentinel value to detect when temperature was not explicitly set - _TEMP_NOT_SET = object() def __init__( self, - temperature = _TEMP_NOT_SET, + temperature: Optional[float] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, max_tokens: Optional[int] = None, @@ -45,14 +42,7 @@ def __init__( response_format: Optional[dict] = None, **kwargs, ): - # Set temperature and track if it was explicitly set - if temperature is self._TEMP_NOT_SET: - self.temperature = None - self._temperature_was_set = False - else: - self.temperature = temperature - self._temperature_was_set = True - + self.temperature = temperature self.top_p = top_p self.top_k = top_k self.max_tokens = max_tokens @@ -80,7 +70,7 @@ def to_json(self) -> dict: >>> config.to_json() {'temperature': 0.7, 'max_tokens': 100} """ - return {k: v for k, v in self.__dict__.items() if v is not None and k != '_temperature_was_set'} + return {k: v for k, v in self.__dict__.items() if v is not None} @staticmethod def from_json(json: dict) -> "GenerativeModelConfig": diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index 3d11de22..66f4daf5 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -35,8 +35,6 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"ollama/{model_name}" - - generation_config = generation_config or GenerativeModelConfig() # Handle host parameter for Ollama additional_params = {} diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index ffc3193d..7876fe3c 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -18,7 +18,7 @@ class OpenAiGenerativeModel(GenerativeModel): def __init__( self, - model_name: str, + model_name: str = "gpt-4.1", generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, ): @@ -32,8 +32,6 @@ def __init__( """ # Convert to LiteLLM format lite_model_name = f"openai/{model_name}" - - generation_config = generation_config or GenerativeModelConfig() # Create internal LiteLLM model self._lite_model = LiteModel( diff --git a/tests/test_rag.py b/tests/test_rag.py index 866f4644..6beffb4e 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -112,7 +112,7 @@ def knowledge_graph_setup(movie_actor_ontology): Sets up the knowledge graph using the provided ontology. """ # Get the model name from the environment variable, with a default - model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash") + model_name = os.getenv("TEST_MODEL", "openai/gpt-4.1") graph_name = model_name.split("/")[0] # Configure the model with zero temperature for deterministic outputs diff --git a/tests/test_streaming_response.py b/tests/test_streaming_response.py index 786b3092..f6b2b9b4 100644 --- a/tests/test_streaming_response.py +++ b/tests/test_streaming_response.py @@ -90,7 +90,7 @@ def knowledge_graph_setup(movie_actor_ontology): Sets up the knowledge graph using the provided ontology. """ # Get the model name from the environment variable, with a default - model_name = os.getenv("TEST_MODEL", "gemini/gemini-2.0-flash") + model_name = os.getenv("TEST_MODEL", "openai/gpt-4.1") graph_name = model_name.split("/")[0] # Configure the model with zero temperature for deterministic outputs From 018a1307bab00d11c9a4103781334d860d086217 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Tue, 24 Jun 2025 17:45:50 +0300 Subject: [PATCH 057/136] wordlist --- .wordlist.txt | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.wordlist.txt b/.wordlist.txt index eda06f4f..1502caae 100644 --- a/.wordlist.txt +++ b/.wordlist.txt @@ -38,4 +38,5 @@ APIs Embeddings NLP graphrag -gemini \ No newline at end of file +gemini +gpt \ No newline at end of file From 25f7e77cbd23d7d682375aa313ca233d127bebe9 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:09:56 +0300 Subject: [PATCH 058/136] update-provider-usage --- .github/workflows/test.yml | 2 +- graphrag_sdk/models/azure_openai.py | 95 ++++++---------------------- graphrag_sdk/models/gemini.py | 98 +++++++---------------------- graphrag_sdk/models/litellm.py | 14 ++++- graphrag_sdk/models/model.py | 41 ++++-------- graphrag_sdk/models/ollama.py | 95 +++++++--------------------- graphrag_sdk/models/openai.py | 89 ++++++-------------------- pyproject.toml | 51 +++++++++++---- tests/test_multi_agent.py | 2 +- 9 files changed, 142 insertions(+), 345 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 656bfda8..c28cacd9 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -62,7 +62,7 @@ jobs: curl -sSL https://install.python-poetry.org | python3 - - name: Install dependencies - run: poetry install --with test --extras "all" + run: poetry install --with test - name: Wait for Ollama to be ready run: | diff --git a/graphrag_sdk/models/azure_openai.py b/graphrag_sdk/models/azure_openai.py index f57c85af..547e81bc 100644 --- a/graphrag_sdk/models/azure_openai.py +++ b/graphrag_sdk/models/azure_openai.py @@ -1,20 +1,20 @@ -import os from typing import Any from typing import Optional -from .litellm import LiteModel +from .litellm import LiteModel, LiteModelChatSession from .model import ( GenerativeModel, GenerativeModelConfig, - GenerationResponse, - FinishReason, GenerativeModelChatSession, ) -class AzureOpenAiGenerativeModel(GenerativeModel): +class AzureOpenAiGenerativeModel(LiteModel): """ A generative model that interfaces with Azure's OpenAI API for chat completions. - This implementation uses LiteLLM as the backend while maintaining the original API. + + Inherits from LiteModel and automatically converts Azure OpenAI model names to + LiteLLM format internally (e.g., "gpt-4o" -> "azure/gpt-4o") while + exposing the original model name through the public API. """ def __init__( @@ -31,13 +31,11 @@ def __init__( model_name (str): Name of the Azure OpenAI model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. - kwargs (Any): Additional arguments optional by Azure OpenAI API. + kwargs (Any): Additional arguments required by Azure OpenAI API. """ - # Convert to LiteLLM format + # Convert to LiteLLM format and call parent constructor lite_model_name = f"azure/{model_name}" - - # Create internal LiteLLM model - self._lite_model = LiteModel( + super().__init__( model_name=lite_model_name, generation_config=generation_config, system_instruction=system_instruction, @@ -51,17 +49,6 @@ def __init__( def model_name(self) -> str: """Get the original model name (without azure/ prefix).""" return self._original_model_name - - @property - def system_instruction(self) -> Optional[str]: - """Get the system instruction from the internal LiteLLM model.""" - return self._lite_model.system_instruction - - @property - def generation_config(self) -> GenerativeModelConfig: - """Get the generation config from the internal LiteLLM model.""" - return self._lite_model.generation_config - def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -75,21 +62,15 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode """ return AzureOpenAiChatSession(self, system_instruction) - def parse_generate_content_response(self, response: any) -> GenerationResponse: - """ - Parse the model's response using the internal LiteLLM model. - """ - return self._lite_model.parse_generate_content_response(response) - def to_json(self) -> dict: """ Serialize the model's configuration and state to JSON format. Returns: - dict: The serialized JSON data. + dict: The serialized JSON data with clean Azure OpenAI model names. """ return { - "model_name": self.model_name, + "model_name": self.model_name, # Return original model name without azure/ prefix "generation_config": self.generation_config.to_json(), "system_instruction": self.system_instruction, } @@ -103,7 +84,7 @@ def from_json(json: dict) -> "GenerativeModel": json (dict): The serialized JSON data. Returns: - GenerativeModel: A new instance of the model. + GenerativeModel: A new instance of AzureOpenAiGenerativeModel. """ return AzureOpenAiGenerativeModel( json["model_name"], @@ -114,13 +95,16 @@ def from_json(json: dict) -> "GenerativeModel": ) -class AzureOpenAiChatSession(GenerativeModelChatSession): +class AzureOpenAiChatSession(LiteModelChatSession): """ A chat session for interacting with the Azure OpenAI model. - This implementation delegates to LiteLLM for actual API calls. + + This implementation inherits from LiteModelChatSession to leverage all chat functionality + without any code duplication. All methods (send_message, send_message_stream, + get_chat_history, delete_last_message) are inherited from the parent class. """ - def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Optional[str] = None): + def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Optional[str] = None) -> None: """ Initialize the chat session and set up the conversation history. @@ -128,45 +112,4 @@ def __init__(self, model: AzureOpenAiGenerativeModel, system_instruction: Option model (AzureOpenAiGenerativeModel): The model instance for the session. system_instruction (Optional[str]): Optional system instruction. """ - self._model = model - # Create internal LiteLLM chat session - self._lite_chat = model._lite_model.start_chat(system_instruction) - - def send_message(self, message: str) -> GenerationResponse: - """ - Send a message in the chat session and receive the model's response. - - Args: - message (str): The message to send. - - Returns: - GenerationResponse: The generated response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message(message) - - def send_message_stream(self, message: str): - """ - Send a message and receive the response in a streaming fashion. - Args: - message (str): The message to send. - Yields: - str: Streamed chunks of the model's response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message_stream(message) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._lite_chat.get_chat_history() - - def delete_last_message(self): - """ - Deletes the last message exchange (user message and assistant response) from the chat history. - """ - self._lite_chat.delete_last_message() + super().__init__(model, system_instruction) diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 464d1be1..0d0c5c3f 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -1,19 +1,19 @@ -import os from typing import Optional -from .litellm import LiteModel +from .litellm import LiteModel, LiteModelChatSession from .model import ( GenerativeModel, GenerativeModelConfig, - GenerationResponse, - FinishReason, GenerativeModelChatSession, ) -class GeminiGenerativeModel(GenerativeModel): +class GeminiGenerativeModel(LiteModel): """ A generative model that interfaces with GoogleAI API for chat completions. - This implementation uses LiteLLM as the backend while maintaining the original API. + + Inherits from LiteModel and automatically converts Gemini model names to + LiteLLM format internally (e.g., "gemini-1.5-pro" -> "gemini/gemini-1.5-pro") while + exposing the original model name through the public API. """ def __init__( @@ -23,18 +23,16 @@ def __init__( system_instruction: Optional[str] = None, ): """ - Initializes the GeminiGenerativeModel with the specified parameters. + Initialize the GeminiGenerativeModel with required parameters. Args: - model_name (str): The name of the Gemini model to use. + model_name (str): Name of the Gemini model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. - system_instruction (Optional[str]): An optional system-level instruction to guide the model's behavior. + system_instruction (Optional[str]): System-level instruction for the model. """ - # Convert to LiteLLM format + # Convert to LiteLLM format and call parent constructor lite_model_name = f"gemini/{model_name}" - - # Create internal LiteLLM model - self._lite_model = LiteModel( + super().__init__( model_name=lite_model_name, generation_config=generation_config, system_instruction=system_instruction @@ -47,16 +45,6 @@ def __init__( def model_name(self) -> str: """Get the original model name (without gemini/ prefix).""" return self._original_model_name - - @property - def system_instruction(self) -> Optional[str]: - """Get the system instruction from the internal LiteLLM model.""" - return self._lite_model.system_instruction - - @property - def generation_config(self) -> GenerativeModelConfig: - """Get the generation config from the internal LiteLLM model.""" - return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -70,21 +58,15 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode """ return GeminiChatSession(self, system_instruction) - def parse_generate_content_response(self, response: any) -> GenerationResponse: - """ - Parse the model's response using the internal LiteLLM model. - """ - return self._lite_model.parse_generate_content_response(response) - def to_json(self) -> dict: """ Serialize the model's configuration and state to JSON format. Returns: - dict: The serialized JSON data. + dict: The serialized JSON data with clean Gemini model names. """ return { - "model_name": self.model_name, + "model_name": self.model_name, # Return original model name without gemini/ prefix "generation_config": self.generation_config.to_json(), "system_instruction": self.system_instruction, } @@ -98,7 +80,7 @@ def from_json(json: dict) -> "GenerativeModel": json (dict): The serialized JSON data. Returns: - GenerativeModel: A new instance of the model. + GenerativeModel: A new instance of GeminiGenerativeModel. """ return GeminiGenerativeModel( json["model_name"], @@ -109,13 +91,16 @@ def from_json(json: dict) -> "GenerativeModel": ) -class GeminiChatSession(GenerativeModelChatSession): +class GeminiChatSession(LiteModelChatSession): """ A chat session for interacting with the Gemini model. - This implementation delegates to LiteLLM for actual API calls. + + This implementation inherits from LiteModelChatSession to leverage all chat functionality + without any code duplication. All methods (send_message, send_message_stream, + get_chat_history, delete_last_message) are inherited from the parent class. """ - def __init__(self, model: GeminiGenerativeModel, system_instruction: Optional[str] = None): + def __init__(self, model: GeminiGenerativeModel, system_instruction: Optional[str] = None) -> None: """ Initialize the chat session and set up the conversation history. @@ -123,45 +108,4 @@ def __init__(self, model: GeminiGenerativeModel, system_instruction: Optional[st model (GeminiGenerativeModel): The model instance for the session. system_instruction (Optional[str]): Optional system instruction. """ - self._model = model - # Create internal LiteLLM chat session - self._lite_chat = model._lite_model.start_chat(system_instruction) - - def send_message(self, message: str) -> GenerationResponse: - """ - Send a message in the chat session and receive the model's response. - - Args: - message (str): The message to send. - - Returns: - GenerationResponse: The generated response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message(message) - - def send_message_stream(self, message: str): - """ - Send a message and receive the response in a streaming fashion. - Args: - message (str): The message to send. - Yields: - str: Streamed chunks of the model's response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message_stream(message) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._lite_chat.get_chat_history() - - def delete_last_message(self): - """ - Deletes the last message exchange (user message and assistant response) from the chat history. - """ - self._lite_chat.delete_last_message() + super().__init__(model, system_instruction) diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index d5ffe5e9..81e53e99 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -1,7 +1,15 @@ import logging -from ollama import Client from typing import Optional, Iterator from litellm import completion, validate_environment, utils as litellm_utils + +# Optional import for Ollama +try: + from ollama import Client as OllamaClient + OLLAMA_AVAILABLE = True +except ImportError: + OllamaClient = None + OLLAMA_AVAILABLE = False + from .model import ( GenerativeModel, GenerativeModelConfig, @@ -49,7 +57,9 @@ def __init__( self.model = model_name if provider == "ollama": - self.ollama_client = Client() + if not OLLAMA_AVAILABLE: + raise ValueError("Ollama client not available. Install with: pip install ollama") + self.ollama_client = OllamaClient() self.check_and_pull_model() if not self.check_valid_key(model_name): raise ValueError(f"Invalid keys for model {model_name}.") diff --git a/graphrag_sdk/models/model.py b/graphrag_sdk/models/model.py index 4580c923..bdb2ad11 100644 --- a/graphrag_sdk/models/model.py +++ b/graphrag_sdk/models/model.py @@ -18,7 +18,7 @@ class GenerativeModelConfig: temperature (Optional[float]): Controls randomness of the output. top_p (Optional[float]): Nucleus sampling parameter. top_k (Optional[int]): Limits sampling to the top-k most probable tokens. - max_tokens (Optional[int]): Maximum number of tokens to generate. + max_completion_tokens (Optional[int]): Maximum number of tokens to generate. stop (Optional[list[str]]): Stop sequences. response_format (Optional[dict]): Desired response format. **kwargs: Any additional parameters not explicitly defined. @@ -26,10 +26,11 @@ class GenerativeModelConfig: Example: >>> config = GenerativeModelConfig( ... temperature=0.5, - ... max_tokens=100, + ... max_completion_tokens=100, + ... stop=["\n", "END"] ... ) >>> config.to_json() - {'temperature': 0.5, 'max_tokens': 100} + {'temperature': 0.5, 'max_completion_tokens': 100, 'stop': ['\n', 'END']} """ def __init__( @@ -37,7 +38,7 @@ def __init__( temperature: Optional[float] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, - max_tokens: Optional[int] = None, + max_completion_tokens: Optional[int] = None, stop: Optional[list] = None, response_format: Optional[dict] = None, **kwargs, @@ -45,7 +46,7 @@ def __init__( self.temperature = temperature self.top_p = top_p self.top_k = top_k - self.max_tokens = max_tokens + self.max_completion_tokens = max_completion_tokens self.stop = stop self.response_format = response_format @@ -66,36 +67,16 @@ def to_json(self) -> dict: (i.e., not None). Example: - >>> config = GenerativeModelConfig(temperature=0.7, max_tokens=100) + >>> config = GenerativeModelConfig(temperature=0.7, max_completion_tokens=100) >>> config.to_json() - {'temperature': 0.7, 'max_tokens': 100} + {'temperature': 0.7, 'max_completion_tokens': 100} """ - return {k: v for k, v in self.__dict__.items() if v is not None} + return {k: v for k, v in vars(self).items() if v is not None} @staticmethod def from_json(json: dict) -> "GenerativeModelConfig": - # Extract known parameters, but only pass them if they exist in JSON - params = {} - if "temperature" in json: - params['temperature'] = json["temperature"] - # For other parameters, only pass if they exist in JSON to maintain default behavior - if "top_p" in json: - params['top_p'] = json["top_p"] - if "top_k" in json: - params['top_k'] = json["top_k"] - if "max_tokens" in json: - params['max_tokens'] = json["max_tokens"] - if "stop" in json: - params['stop'] = json["stop"] - if "response_format" in json: - params['response_format'] = json["response_format"] - - # Extract any additional parameters not in the known set - known_keys = {'temperature', 'top_p', 'top_k', 'max_tokens', 'stop', 'response_format'} - extra_params = {k: v for k, v in json.items() if k not in known_keys} - - return GenerativeModelConfig(**params, **extra_params) - + # Simply pass all JSON data as kwargs - the constructor will handle it + return GenerativeModelConfig(**json) class GenerationResponse: diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index 66f4daf5..ef28a22b 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -1,20 +1,22 @@ import logging from typing import Optional -from .litellm import LiteModel +from .litellm import LiteModel, LiteModelChatSession from .model import ( GenerativeModel, GenerativeModelConfig, - GenerationResponse, GenerativeModelChatSession, ) logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) -class OllamaGenerativeModel(GenerativeModel): +class OllamaGenerativeModel(LiteModel): """ A generative model that interfaces with the Ollama Client for chat completions. - This implementation uses LiteLLM as the backend while maintaining the original API. + + Inherits from LiteModel and automatically converts Ollama model names to + LiteLLM format internally (e.g., "llama3:8b" -> "ollama/llama3:8b") while + exposing the original model name through the public API. """ def __init__( @@ -30,8 +32,8 @@ def __init__( Args: model_name (str): The name of the Ollama model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. - system_instruction (Optional[str]): Instruction to guide the model. - host (Optional[str]): Host for connecting to the Ollama API (ignored in LiteLLM implementation). + system_instruction (Optional[str]): System-level instruction for the model. + host (Optional[str]): Host for connecting to the Ollama API. """ # Convert to LiteLLM format lite_model_name = f"ollama/{model_name}" @@ -41,32 +43,21 @@ def __init__( if host is not None: additional_params['api_base'] = host # LiteLLM uses api_base for custom endpoints - # Create internal LiteLLM model - self._lite_model = LiteModel( + # Call parent constructor + super().__init__( model_name=lite_model_name, generation_config=generation_config, system_instruction=system_instruction, additional_params=additional_params ) - # Store original model name and host for compatibility + # Store original model name for compatibility (without the ollama/ prefix) self._original_model_name = model_name - self._host = host @property def model_name(self) -> str: """Get the original model name (without ollama/ prefix).""" return self._original_model_name - - @property - def system_instruction(self) -> Optional[str]: - """Get the system instruction from the internal LiteLLM model.""" - return self._lite_model.system_instruction - - @property - def generation_config(self) -> GenerativeModelConfig: - """Get the generation config from the internal LiteLLM model.""" - return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -80,21 +71,15 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode """ return OllamaChatSession(self, system_instruction) - def parse_generate_content_response(self, response: any) -> GenerationResponse: - """ - Parse the model's response using the internal LiteLLM model. - """ - return self._lite_model.parse_generate_content_response(response) - def to_json(self) -> dict: """ Serialize the model's configuration and state to JSON format. Returns: - dict: The serialized JSON data. + dict: The serialized JSON data with clean Ollama model names. """ return { - "model_name": self.model_name, + "model_name": self.model_name, # Return original model name without ollama/ prefix "generation_config": self.generation_config.to_json(), "system_instruction": self.system_instruction, } @@ -108,7 +93,7 @@ def from_json(json: dict) -> "GenerativeModel": json (dict): The serialized JSON data. Returns: - GenerativeModel: A new instance of the model. + GenerativeModel: A new instance of OllamaGenerativeModel. """ return OllamaGenerativeModel( json["model_name"], @@ -119,13 +104,16 @@ def from_json(json: dict) -> "GenerativeModel": ) -class OllamaChatSession(GenerativeModelChatSession): +class OllamaChatSession(LiteModelChatSession): """ A chat session for interacting with the Ollama model. - This implementation delegates to LiteLLM for actual API calls. + + This implementation inherits from LiteModelChatSession to leverage all chat functionality + without any code duplication. All methods (send_message, send_message_stream, + get_chat_history, delete_last_message) are inherited from the parent class. """ - def __init__(self, model: OllamaGenerativeModel, system_instruction: Optional[str] = None): + def __init__(self, model: OllamaGenerativeModel, system_instruction: Optional[str] = None) -> None: """ Initialize the chat session and set up the conversation history. @@ -133,45 +121,4 @@ def __init__(self, model: OllamaGenerativeModel, system_instruction: Optional[st model (OllamaGenerativeModel): The model instance for the session. system_instruction (Optional[str]): Optional system instruction. """ - self._model = model - # Create internal LiteLLM chat session - self._lite_chat = model._lite_model.start_chat(system_instruction) - - def send_message(self, message: str) -> GenerationResponse: - """ - Send a message in the chat session and receive the model's response. - - Args: - message (str): The message to send. - - Returns: - GenerationResponse: The generated response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message(message) - - def send_message_stream(self, message: str): - """ - Send a message and receive the response in a streaming fashion. - Args: - message (str): The message to send. - Yields: - str: Streamed chunks of the model's response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message_stream(message) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._lite_chat.get_chat_history() - - def delete_last_message(self): - """ - Deletes the last message exchange (user message and assistant response) from the chat history. - """ - self._lite_chat.delete_last_message() + super().__init__(model, system_instruction) diff --git a/graphrag_sdk/models/openai.py b/graphrag_sdk/models/openai.py index 7876fe3c..51ea1a47 100644 --- a/graphrag_sdk/models/openai.py +++ b/graphrag_sdk/models/openai.py @@ -1,19 +1,19 @@ -import os from typing import Optional -from .litellm import LiteModel +from .litellm import LiteModel, LiteModelChatSession from .model import ( GenerativeModel, GenerativeModelConfig, - GenerationResponse, - FinishReason, GenerativeModelChatSession, ) -class OpenAiGenerativeModel(GenerativeModel): +class OpenAiGenerativeModel(LiteModel): """ A generative model that interfaces with OpenAI's API for chat completions. - This implementation uses LiteLLM as the backend while maintaining the original API. + + Inherits from LiteModel and automatically converts OpenAI model names to + LiteLLM format internally (e.g., "gpt-4o" -> "openai/gpt-4o") while + exposing the original model name through the public API. """ def __init__( @@ -30,11 +30,9 @@ def __init__( generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. """ - # Convert to LiteLLM format + # Convert to LiteLLM format and call parent constructor lite_model_name = f"openai/{model_name}" - - # Create internal LiteLLM model - self._lite_model = LiteModel( + super().__init__( model_name=lite_model_name, generation_config=generation_config, system_instruction=system_instruction @@ -47,16 +45,6 @@ def __init__( def model_name(self) -> str: """Get the original model name (without openai/ prefix).""" return self._original_model_name - - @property - def system_instruction(self) -> Optional[str]: - """Get the system instruction from the internal LiteLLM model.""" - return self._lite_model.system_instruction - - @property - def generation_config(self) -> GenerativeModelConfig: - """Get the generation config from the internal LiteLLM model.""" - return self._lite_model.generation_config def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ @@ -69,21 +57,15 @@ def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeMode """ return OpenAiChatSession(self, system_instruction) - def parse_generate_content_response(self, response: any) -> GenerationResponse: - """ - Parse the model's response using the internal LiteLLM model. - """ - return self._lite_model.parse_generate_content_response(response) - def to_json(self) -> dict: """ Serialize the model's configuration and state to JSON format. Returns: - dict: The serialized JSON data. + dict: The serialized JSON data with clean OpenAI model names. """ return { - "model_name": self.model_name, + "model_name": self.model_name, # Return original model name without openai/ prefix "generation_config": self.generation_config.to_json(), "system_instruction": self.system_instruction, } @@ -97,7 +79,7 @@ def from_json(json: dict) -> "GenerativeModel": json (dict): The serialized JSON data. Returns: - GenerativeModel: A new instance of the model. + GenerativeModel: A new instance of OpenAiGenerativeModel. """ return OpenAiGenerativeModel( json["model_name"], @@ -108,56 +90,21 @@ def from_json(json: dict) -> "GenerativeModel": ) -class OpenAiChatSession(GenerativeModelChatSession): +class OpenAiChatSession(LiteModelChatSession): """ A chat session for interacting with the OpenAI model. - This implementation delegates to LiteLLM for actual API calls. + + This implementation inherits from LiteModelChatSession to leverage all chat functionality + without any code duplication. All methods (send_message, send_message_stream, + get_chat_history, delete_last_message) are inherited from the parent class. """ def __init__(self, model: OpenAiGenerativeModel, system_instruction: Optional[str] = None) -> None: """ Initialize the chat session and set up the conversation history. + Args: model (OpenAiGenerativeModel): The model instance for the session. system_instruction (Optional[str]): Optional system instruction. """ - self._model = model - # Create internal LiteLLM chat session - self._lite_chat = model._lite_model.start_chat(system_instruction) - - def send_message(self, message: str) -> GenerationResponse: - """ - Send a message in the chat session and receive the model's response. - Args: - message (str): The message to send. - Returns: - GenerationResponse: The generated response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message(message) - - def send_message_stream(self, message: str): - """ - Send a message and receive the response in a streaming fashion. - Args: - message (str): The message to send. - Yields: - str: Streamed chunks of the model's response. - """ - # Delegate to LiteLLM chat session - return self._lite_chat.send_message_stream(message) - - def get_chat_history(self) -> list[dict]: - """ - Retrieve the conversation history for the current chat session. - - Returns: - list[dict]: The chat session's conversation history. - """ - return self._lite_chat.get_chat_history() - - def delete_last_message(self): - """ - Deletes the last message exchange (user message and assistant response) from the chat history. - """ - self._lite_chat.delete_last_message() + super().__init__(model, system_instruction) diff --git a/pyproject.toml b/pyproject.toml index 01694915..4f82ba63 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "graphrag_sdk" -version = "0.7.1" +version = "0.8.0" license = "MIT" description = "Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] @@ -23,19 +23,44 @@ python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" rich = "^13.9.4" ipykernel = "^6.29.5" -vertexai = { version = "^1.49.0", optional = true } -ollama = { version = "^0.2.1", optional = true } -openai = { version = "^1.35.9", optional = true } -google-generativeai = { version = "^0.8.1", optional = true } -litellm = { version = "^1.52.14", optional = true } +# Core LLM integration (default dependencies) +litellm = "^1.52.14" +ollama = "^0.2.1" [tool.poetry.extras] -all = ["vertexai", "ollama", "openai", "google-generativeai", "litellm"] -ollama = ["ollama"] -openai = ["openai"] -vertexai = ["vertexai"] -google-generativeai = ["google-generativeai"] -litellm = ["litellm", "ollama"] +# LiteLLM proxy and server functionality +litellm-proxy = [ + "litellm[proxy]" +] + +# LiteLLM extended proxy features (enterprise, Azure, etc.) +litellm-extra-proxy = [ + "litellm[extra_proxy]" +] + +# LiteLLM utility functions +litellm-utils = [ + "litellm[utils]" +] + +# LiteLLM caching functionality +litellm-caching = [ + "litellm[caching]" +] + +# Common combinations +litellm-full-proxy = [ + "litellm[proxy,extra_proxy]" +] + +litellm-complete = [ + "litellm[proxy,extra_proxy,utils,caching]" +] + +# All litellm features +all-litellm-features = [ + "litellm[proxy,extra_proxy,utils,caching]" +] [tool.poetry.group.test.dependencies] pytest = "^8.2.1" @@ -55,4 +80,4 @@ build-backend = "poetry.core.masonry.api" log_cli = true log_cli_level = "INFO" log_cli_format = "%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)" -log_cli_date_format = "%Y-%m-%d %H:%M:%S" +log_cli_date_format = "%Y-%m-%d %H:%M:%S" \ No newline at end of file diff --git a/tests/test_multi_agent.py b/tests/test_multi_agent.py index 6f99a9dc..535aadaa 100644 --- a/tests/test_multi_agent.py +++ b/tests/test_multi_agent.py @@ -188,7 +188,7 @@ def setUpClass(cls): ) ) - cls.model = LiteModel("azure/o3-mini", generation_config=GenerativeModelConfig(temperature=None)) + cls.model = LiteModel("azure/o3-mini") cls.restaurants_kg = KnowledgeGraph( name="restaurants", ontology=cls.restaurants_ontology, From 6a0a6bdff839ab823e91371b8521d198fdc0eeb7 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:17:53 +0300 Subject: [PATCH 059/136] update-inst --- README.md | 6 +----- pyproject.toml | 37 +------------------------------------ 2 files changed, 2 insertions(+), 41 deletions(-) diff --git a/README.md b/README.md index 72825086..9c9b2ff5 100644 --- a/README.md +++ b/README.md @@ -25,11 +25,7 @@ docker run -p 6379:6379 -p 3000:3000 -it --rm -v ./data:/data falkordb/falkordb ### Dependencies: ```sh -# For all LLM providers -pip install graphrag_sdk[all] - -# For specific LLM provider (Example: LiteLLM) -pip install graphrag_sdk[litellm] +pip install graphrag_sdk ``` ### Configure Credentials. See [.env](.env.template) for examples. diff --git a/pyproject.toml b/pyproject.toml index 4f82ba63..0386c6b5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -27,41 +27,6 @@ ipykernel = "^6.29.5" litellm = "^1.52.14" ollama = "^0.2.1" -[tool.poetry.extras] -# LiteLLM proxy and server functionality -litellm-proxy = [ - "litellm[proxy]" -] - -# LiteLLM extended proxy features (enterprise, Azure, etc.) -litellm-extra-proxy = [ - "litellm[extra_proxy]" -] - -# LiteLLM utility functions -litellm-utils = [ - "litellm[utils]" -] - -# LiteLLM caching functionality -litellm-caching = [ - "litellm[caching]" -] - -# Common combinations -litellm-full-proxy = [ - "litellm[proxy,extra_proxy]" -] - -litellm-complete = [ - "litellm[proxy,extra_proxy,utils,caching]" -] - -# All litellm features -all-litellm-features = [ - "litellm[proxy,extra_proxy,utils,caching]" -] - [tool.poetry.group.test.dependencies] pytest = "^8.2.1" deepeval = "^2.2.6" @@ -80,4 +45,4 @@ build-backend = "poetry.core.masonry.api" log_cli = true log_cli_level = "INFO" log_cli_format = "%(asctime)s [%(levelname)8s] %(message)s (%(filename)s:%(lineno)s)" -log_cli_date_format = "%Y-%m-%d %H:%M:%S" \ No newline at end of file +log_cli_date_format = "%Y-%m-%d %H:%M:%S" From d0e5d78dd3b3641e0dd29ad295e2f388606a451b Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:28:26 +0300 Subject: [PATCH 060/136] fix-tets --- graphrag_sdk/models/litellm.py | 23 ++++++++++++++--------- tests/test_multi_agent.py | 3 +-- 2 files changed, 15 insertions(+), 11 deletions(-) diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 81e53e99..496cf19f 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -53,7 +53,7 @@ def __init__( env_val = validate_environment(model_name) if not env_val['keys_in_environment']: raise ValueError(f"Missing {env_val['missing_keys']} in the environment.") - self.model_name, provider, _, _ = litellm_utils.get_llm_provider(model_name) + self._internal_model_name, provider, _, _ = litellm_utils.get_llm_provider(model_name) self.model = model_name if provider == "ollama": @@ -64,7 +64,7 @@ def __init__( if not self.check_valid_key(model_name): raise ValueError(f"Invalid keys for model {model_name}.") - if self.model_name == "gpt-4.1": + if self._internal_model_name == "gpt-4.1": # Set default temperature to 0 for gpt-4.1 if generation_config is None: generation_config = GenerativeModelConfig(temperature=0) @@ -73,6 +73,11 @@ def __init__( self.system_instruction = system_instruction self.additional_params = additional_params or {} + @property + def model_name(self) -> str: + """Get the model name.""" + return self._internal_model_name + def check_valid_key(self, model: str): """ Checks if the environment key is valid for a specific model by making a litellm.completion call with max_tokens=10 @@ -108,16 +113,16 @@ def check_and_pull_model(self) -> None: available_models = [model['name'] for model in response['models']] # Extract model names # Check if the model is already pulled - if self.model_name in available_models: - logger.info(f"The model '{self.model_name}' is already available.") + if self._internal_model_name in available_models: + logger.info(f"The model '{self._internal_model_name}' is already available.") else: - logger.info(f"Pulling the model '{self.model_name}'...") + logger.info(f"Pulling the model '{self._internal_model_name}'...") try: - self.ollama_client.pull(self.model_name) # Pull the model - logger.info(f"Model '{self.model_name}' pulled successfully.") + self.ollama_client.pull(self._internal_model_name) # Pull the model + logger.info(f"Model '{self._internal_model_name}' pulled successfully.") except Exception as e: - logger.error(f"Failed to pull the model '{self.model_name}': {e}") - raise ValueError(f"Failed to pull the model '{self.model_name}': {e}") + logger.error(f"Failed to pull the model '{self._internal_model_name}': {e}") + raise ValueError(f"Failed to pull the model '{self._internal_model_name}': {e}") def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ diff --git a/tests/test_multi_agent.py b/tests/test_multi_agent.py index 535aadaa..172197ef 100644 --- a/tests/test_multi_agent.py +++ b/tests/test_multi_agent.py @@ -10,8 +10,7 @@ from graphrag_sdk.orchestrator import Orchestrator from graphrag_sdk.attribute import Attribute, AttributeType from graphrag_sdk import (KnowledgeGraph, - KnowledgeGraphModelConfig, - GenerativeModelConfig) + KnowledgeGraphModelConfig) load_dotenv() From fe4778ababce3864145d0fff1abc8dfc5ae6112f Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:33:07 +0300 Subject: [PATCH 061/136] fix-poe --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c28cacd9..0095e243 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -57,9 +57,9 @@ jobs: version: ">= 363.0.0" - name: Install Poetry - if: steps.cache.outputs.cache-hit != true run: | curl -sSL https://install.python-poetry.org | python3 - + echo "$HOME/.local/bin" >> $GITHUB_PATH - name: Install dependencies run: poetry install --with test From a6a98bad0fb5e541f3352b918bbb36171f1610da Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:36:44 +0300 Subject: [PATCH 062/136] fix-test-int --- .github/workflows/test.yml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 0095e243..d9048809 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -35,7 +35,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v5 with: - python-version: 3.9.15 # Update with desired Python version + python-version: 3.10 # Compatible with project requirements (>=3.10.0,<3.14) - name: Cache Poetry virtualenv id: cache @@ -62,7 +62,9 @@ jobs: echo "$HOME/.local/bin" >> $GITHUB_PATH - name: Install dependencies - run: poetry install --with test + run: | + poetry lock --no-update + poetry install --with test - name: Wait for Ollama to be ready run: | From 5c8ee4d952338ae5bbfcbc2c00213c92cbc93f03 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:39:22 +0300 Subject: [PATCH 063/136] test-py311 --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index d9048809..2c2b2151 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -35,7 +35,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v5 with: - python-version: 3.10 # Compatible with project requirements (>=3.10.0,<3.14) + python-version: 3.11 # Compatible with project requirements (>=3.10.0,<3.14) - name: Cache Poetry virtualenv id: cache From c7311d61333fadfe33921200c255eecd1f38c72f Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 14:57:33 +0300 Subject: [PATCH 064/136] update-lock --- .github/workflows/test.yml | 8 +- poetry.lock | 6133 +++++++++++++++++++++--------------- 2 files changed, 3589 insertions(+), 2552 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 2c2b2151..c95d44a3 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -35,7 +35,7 @@ jobs: - name: Set up Python uses: actions/setup-python@v5 with: - python-version: 3.11 # Compatible with project requirements (>=3.10.0,<3.14) + python-version: 3.11.0 # Update with desired Python version - name: Cache Poetry virtualenv id: cache @@ -57,14 +57,12 @@ jobs: version: ">= 363.0.0" - name: Install Poetry + if: steps.cache.outputs.cache-hit != true run: | curl -sSL https://install.python-poetry.org | python3 - - echo "$HOME/.local/bin" >> $GITHUB_PATH - name: Install dependencies - run: | - poetry lock --no-update - poetry install --with test + run: poetry install --with test - name: Wait for Ollama to be ready run: | diff --git a/poetry.lock b/poetry.lock index b86128f4..1d8535dd 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,102 +2,112 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.4" +version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"}, - {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"}, + {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, + {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, ] [[package]] name = "aiohttp" -version = "3.11.11" +version = "3.12.13" description = 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"sha256:b65a0a2123300dd71281a7bf6e64d65a0759287df52729bdd1ae2e47dc311a3d"}, +] + +[package.dependencies] +google-auth = "*" +httplib2 = ">=0.19.0" + +[[package]] +name = "google-generativeai" +version = "0.8.5" +description = "Google Generative AI High level API client library and tools." +optional = false +python-versions = ">=3.9" +files = [ + {file = "google_generativeai-0.8.5-py3-none-any.whl", hash = "sha256:22b420817fb263f8ed520b33285f45976d5b21e904da32b80d4fd20c055123a2"}, +] + +[package.dependencies] +google-ai-generativelanguage = "0.6.15" +google-api-core = "*" +google-api-python-client = "*" +google-auth = ">=2.15.0" +protobuf = "*" +pydantic = "*" +tqdm = "*" +typing-extensions = "*" + +[package.extras] +dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "pyyaml"] + [[package]] name = "googleapis-common-protos" version = "1.70.0" @@ -1506,6 +1654,22 @@ files = [ [package.extras] protobuf = ["grpcio-tools (>=1.73.0)"] +[[package]] +name = "grpcio-status" +version = "1.71.0" +description = "Status proto mapping for gRPC" +optional = false +python-versions = ">=3.9" +files = [ + {file = "grpcio_status-1.71.0-py3-none-any.whl", hash = "sha256:843934ef8c09e3e858952887467f8256aac3910c55f077a359a65b2b3cde3e68"}, + {file = "grpcio_status-1.71.0.tar.gz", hash = "sha256:11405fed67b68f406b3f3c7c5ae5104a79d2d309666d10d61b152e91d28fb968"}, +] + +[package.dependencies] +googleapis-common-protos = ">=1.5.5" +grpcio = ">=1.71.0" +protobuf = ">=5.26.1,<6.0dev" + [[package]] name = "h11" version = "0.16.0" @@ -1558,6 +1722,20 @@ http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] trio = ["trio (>=0.22.0,<1.0)"] +[[package]] +name = "httplib2" +version = "0.22.0" +description = "A comprehensive HTTP client library." +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +files = [ + {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"}, + {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"}, +] + +[package.dependencies] +pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""} + [[package]] name = "httpx" version = "0.27.2" @@ -3717,8 +3895,8 @@ files = [ [package.dependencies] googleapis-common-protos = ">=1.52,<2.0" grpcio = [ - {version = ">=1.63.2,<2.0.0", markers = "python_version < \"3.13\""}, {version = ">=1.66.2,<2.0.0", markers = "python_version >= \"3.13\""}, + {version = ">=1.63.2,<2.0.0", markers = "python_version < \"3.13\""}, ] opentelemetry-api = ">=1.15,<2.0" opentelemetry-exporter-otlp-proto-common = "1.34.1" @@ -3942,9 +4120,9 @@ files = [ [package.dependencies] numpy = [ + {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, {version = ">=1.22.4", markers = "python_version < \"3.11\""}, {version = ">=1.23.2", markers = "python_version == \"3.11\""}, - {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, ] python-dateutil = ">=2.8.2" pytz = ">=2020.1" @@ -4342,6 +4520,23 @@ files = [ {file = "propcache-0.3.2.tar.gz", hash = "sha256:20d7d62e4e7ef05f221e0db2856b979540686342e7dd9973b815599c7057e168"}, ] +[[package]] +name = "proto-plus" +version = "1.26.1" +description = "Beautiful, Pythonic protocol buffers" +optional = false +python-versions = ">=3.7" +files = [ + {file = "proto_plus-1.26.1-py3-none-any.whl", hash = "sha256:13285478c2dcf2abb829db158e1047e2f1e8d63a077d94263c2b88b043c75a66"}, + {file = "proto_plus-1.26.1.tar.gz", hash = "sha256:21a515a4c4c0088a773899e23c7bbade3d18f9c66c73edd4c7ee3816bc96a012"}, +] + +[package.dependencies] +protobuf = ">=3.19.0,<7.0.0" + +[package.extras] +testing = ["google-api-core (>=1.31.5)"] + [[package]] name = "protobuf" version = "5.29.5" @@ -4410,6 +4605,31 @@ files = [ [package.extras] tests = ["pytest"] +[[package]] +name = "pyasn1" +version = "0.6.1" +description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"}, + {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"}, +] + +[[package]] +name = "pyasn1-modules" +version = "0.4.2" +description = "A collection of ASN.1-based protocols modules" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pyasn1_modules-0.4.2-py3-none-any.whl", hash = "sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a"}, + {file = "pyasn1_modules-0.4.2.tar.gz", hash = "sha256:677091de870a80aae844b1ca6134f54652fa2c8c5a52aa396440ac3106e941e6"}, +] + +[package.dependencies] +pyasn1 = ">=0.6.1,<0.7.0" + [[package]] name = "pycparser" version = "2.22" @@ -4625,6 +4845,20 @@ pyyaml = "*" [package.extras] extra = ["pygments (>=2.19.1)"] +[[package]] +name = "pyparsing" +version = "3.2.3" +description = "pyparsing module - Classes and methods to define and execute parsing grammars" +optional = false +python-versions = ">=3.9" +files = [ + {file = "pyparsing-3.2.3-py3-none-any.whl", hash = "sha256:a749938e02d6fd0b59b356ca504a24982314bb090c383e3cf201c95ef7e2bfcf"}, + {file = "pyparsing-3.2.3.tar.gz", hash = "sha256:b9c13f1ab8b3b542f72e28f634bad4de758ab3ce4546e4301970ad6fa77c38be"}, +] + +[package.extras] +diagrams = ["jinja2", "railroad-diagrams"] + [[package]] name = "pypdf" version = "4.3.1" @@ -5404,6 +5638,20 @@ files = [ {file = "rpds_py-0.25.1.tar.gz", hash = "sha256:8960b6dac09b62dac26e75d7e2c4a22efb835d827a7278c34f72b2b84fa160e3"}, ] +[[package]] +name = "rsa" +version = "4.9.1" +description = "Pure-Python RSA implementation" +optional = false +python-versions = "<4,>=3.6" +files = [ + {file = "rsa-4.9.1-py3-none-any.whl", hash = "sha256:68635866661c6836b8d39430f97a996acbd61bfa49406748ea243539fe239762"}, + {file = "rsa-4.9.1.tar.gz", hash = "sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75"}, +] + +[package.dependencies] +pyasn1 = ">=0.1.3" + [[package]] name = "secretstorage" version = "3.3.3" @@ -6213,6 +6461,17 @@ files = [ [package.extras] dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"] +[[package]] +name = "uritemplate" +version = "4.2.0" +description = "Implementation of RFC 6570 URI Templates" +optional = false +python-versions = ">=3.9" +files = [ + {file = "uritemplate-4.2.0-py3-none-any.whl", hash = "sha256:962201ba1c4edcab02e60f9a0d3821e82dfc5d2d6662a21abd533879bdb8a686"}, + {file = "uritemplate-4.2.0.tar.gz", hash = "sha256:480c2ed180878955863323eea31b0ede668795de182617fef9c6ca09e6ec9d0e"}, +] + [[package]] name = "urllib3" version = "2.5.0" @@ -6706,4 +6965,4 @@ cffi = ["cffi (>=1.11)"] [metadata] lock-version = "2.0" python-versions = ">=3.10.0,<3.14" -content-hash = "7b83e6d11da0d76231918ca3cc41b971f6f37615dc9fa123ad2b9764651e0808" +content-hash = "0d443e408ea9c122a4a9fc36bb240015438322dd6811f66522ec6afce97bc676" diff --git a/pyproject.toml b/pyproject.toml index 0386c6b5..2410c0bf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,6 +30,7 @@ ollama = "^0.2.1" [tool.poetry.group.test.dependencies] pytest = "^8.2.1" deepeval = "^2.2.6" +google-generativeai = "^0.8.5" [tool.poetry.group.dev.dependencies] sphinx = "^7.3.7" From a31dcaa19354533f280d6c9e9ca09f04530f7410 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 15:10:43 +0300 Subject: [PATCH 066/136] update-lock --- poetry.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 827dc700..645db378 100644 --- a/poetry.lock +++ b/poetry.lock @@ -4121,8 +4121,8 @@ files = [ [package.dependencies] numpy = [ {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, - {version = ">=1.22.4", markers = "python_version < \"3.11\""}, {version = ">=1.23.2", markers = "python_version == \"3.11\""}, + {version = ">=1.22.4", markers = "python_version < \"3.11\""}, ] python-dateutil = ">=2.8.2" pytz = ">=2020.1" From 8b7c17b80be108bcd4751b64c63b338c47a88b4a Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 25 Jun 2025 15:57:07 +0300 Subject: [PATCH 067/136] rev-toml --- .github/workflows/test.yml | 2 +- poetry.lock | 3214 +++++++++++------------------------- pyproject.toml | 15 +- 3 files changed, 994 insertions(+), 2237 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c95d44a3..5b0dcfcb 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -62,7 +62,7 @@ jobs: curl -sSL https://install.python-poetry.org | python3 - - name: Install dependencies - run: poetry install --with test + run: poetry install --with test --extras "all" - name: Wait for Ollama to be ready run: | diff --git a/poetry.lock b/poetry.lock index 645db378..94869122 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -6,6 +6,7 @@ version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, @@ -17,6 +18,7 @@ version = "3.12.13" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiohttp-3.12.13-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5421af8f22a98f640261ee48aae3a37f0c41371e99412d55eaf2f8a46d5dad29"}, {file = "aiohttp-3.12.13-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0fcda86f6cb318ba36ed8f1396a6a4a3fd8f856f84d426584392083d10da4de0"}, @@ -117,7 +119,7 @@ propcache = ">=0.2.0" yarl = ">=1.17.0,<2.0" [package.extras] -speedups = ["Brotli", "aiodns (>=3.3.0)", "brotlicffi"] +speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "brotlicffi ; platform_python_implementation != \"CPython\""] [[package]] name = "aiosignal" @@ -125,6 +127,7 @@ version = "1.3.2" description = "aiosignal: a list of registered asynchronous callbacks" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5"}, {file = "aiosignal-1.3.2.tar.gz", hash = "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54"}, @@ -139,6 +142,7 @@ version = "0.7.16" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"}, {file = 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No external dependencies." -optional = false -python-versions = "*" -files = [ - {file = "filetype-1.2.0-py2.py3-none-any.whl", hash = "sha256:7ce71b6880181241cf7ac8697a2f1eb6a8bd9b429f7ad6d27b8db9ba5f1c2d25"}, - {file = "filetype-1.2.0.tar.gz", hash = "sha256:66b56cd6474bf41d8c54660347d37afcc3f7d1970648de365c102ef77548aadb"}, -] +typing = ["typing-extensions (>=4.12.2) ; python_version < \"3.11\""] [[package]] name = "fix-busted-json" @@ -1185,6 +935,7 @@ version = "0.0.18" description = "Fixes broken JSON string objects" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "fix-busted-json-0.0.18.tar.gz", hash = "sha256:93c5dab7cae3b5d0b055f2c7043f9fe727a88a80d0be753c5f2c20bb9b69672f"}, {file = "fix_busted_json-0.0.18-py3-none-any.whl", hash = "sha256:fdce0e02c9a810b3aa28e1c3c32c24b21b44e89f6315ec25d2b963bd52a6ef03"}, @@ -1196,6 +947,7 @@ version = "1.5.1" description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" optional = false python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" +groups = ["dev"] files = [ {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"}, {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"}, @@ -1207,6 +959,7 @@ version = "1.7.0" description = "A list-like structure which implements collections.abc.MutableSequence" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "frozenlist-1.7.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cc4df77d638aa2ed703b878dd093725b72a824c3c546c076e8fdf276f78ee84a"}, {file = "frozenlist-1.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:716a9973a2cc963160394f701964fe25012600f3d311f60c790400b00e568b61"}, @@ -1320,6 +1073,7 @@ version = "2025.5.1" description = "File-system specification" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "fsspec-2025.5.1-py3-none-any.whl", hash = "sha256:24d3a2e663d5fc735ab256263c4075f374a174c3410c0b25e5bd1970bceaa462"}, {file = "fsspec-2025.5.1.tar.gz", hash = "sha256:2e55e47a540b91843b755e83ded97c6e897fa0942b11490113f09e9c443c2475"}, @@ -1353,29 +1107,14 @@ test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"] tqdm = ["tqdm"] -[[package]] -name = "ghp-import" -version = "2.1.0" -description = "Copy your docs directly to the gh-pages branch." -optional = false -python-versions = "*" -files = [ - {file = "ghp-import-2.1.0.tar.gz", hash = "sha256:9c535c4c61193c2df8871222567d7fd7e5014d835f97dc7b7439069e2413d343"}, - {file = "ghp_import-2.1.0-py3-none-any.whl", hash = "sha256:8337dd7b50877f163d4c0289bc1f1c7f127550241988d568c1db512c4324a619"}, -] - -[package.dependencies] -python-dateutil = ">=2.8.1" - -[package.extras] -dev = ["flake8", "markdown", "twine", "wheel"] - [[package]] name = "google-ai-generativelanguage" version = "0.6.15" description = "Google Ai Generativelanguage API client library" -optional = false +optional = true python-versions = ">=3.7" +groups = ["main"] +markers = "extra == \"all\" or extra == \"google-generativeai\"" files = [ {file = "google_ai_generativelanguage-0.6.15-py3-none-any.whl", hash = "sha256:5a03ef86377aa184ffef3662ca28f19eeee158733e45d7947982eb953c6ebb6c"}, {file = "google_ai_generativelanguage-0.6.15.tar.gz", hash = "sha256:8f6d9dc4c12b065fe2d0289026171acea5183ebf2d0b11cefe12f3821e159ec3"}, @@ -1385,8 +1124,8 @@ files = [ google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]} google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev" proto-plus = [ + {version = ">=1.22.3,<2.0.0dev"}, {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""}, - {version = ">=1.22.3,<2.0.0dev", markers = "python_version < \"3.13\""}, ] protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev" @@ -1394,8 +1133,10 @@ protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4 name = "google-api-core" version = "2.25.1" description = "Google API client core library" -optional = false +optional = true python-versions = ">=3.7" +groups = ["main"] +markers = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\"" files = [ {file = "google_api_core-2.25.1-py3-none-any.whl", hash = "sha256:8a2a56c1fef82987a524371f99f3bd0143702fecc670c72e600c1cda6bf8dbb7"}, {file = "google_api_core-2.25.1.tar.gz", hash = "sha256:d2aaa0b13c78c61cb3f4282c464c046e45fbd75755683c9c525e6e8f7ed0a5e8"}, @@ -1410,18 +1151,18 @@ grpcio = [ ] grpcio-status = [ {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}, - {version = ">=1.33.2,<2.0.0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""}, + {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""}, ] proto-plus = [ + {version = ">=1.22.3,<2.0.0"}, {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""}, - {version = ">=1.22.3,<2.0.0", markers = "python_version < \"3.13\""}, ] protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0" requests 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+groups = ["main"] +markers = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\"" files = [ {file = "proto_plus-1.26.1-py3-none-any.whl", hash = "sha256:13285478c2dcf2abb829db158e1047e2f1e8d63a077d94263c2b88b043c75a66"}, {file = "proto_plus-1.26.1.tar.gz", hash = "sha256:21a515a4c4c0088a773899e23c7bbade3d18f9c66c73edd4c7ee3816bc96a012"}, @@ -4543,6 +3551,7 @@ version = "5.29.5" description = "" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "protobuf-5.29.5-cp310-abi3-win32.whl", hash = "sha256:3f1c6468a2cfd102ff4703976138844f78ebd1fb45f49011afc5139e9e283079"}, {file = "protobuf-5.29.5-cp310-abi3-win_amd64.whl", hash = "sha256:3f76e3a3675b4a4d867b52e4a5f5b78a2ef9565549d4037e06cf7b0942b1d3fc"}, @@ -4556,6 +3565,7 @@ files = [ {file = "protobuf-5.29.5-py3-none-any.whl", hash = "sha256:6cf42630262c59b2d8de33954443d94b746c952b01434fc58a417fdbd2e84bd5"}, {file = "protobuf-5.29.5.tar.gz", hash = "sha256:bc1463bafd4b0929216c35f437a8e28731a2b7fe3d98bb77a600efced5a15c84"}, ] +markers = {main = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\""} [[package]] name = "psutil" @@ -4563,6 +3573,7 @@ version = "7.0.0" description = "Cross-platform lib for process and system monitoring in Python. NOTE: the syntax of this script MUST be kept compatible with Python 2.7." optional = false python-versions = ">=3.6" +groups = ["main", "dev"] files = [ {file = "psutil-7.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:101d71dc322e3cffd7cea0650b09b3d08b8e7c4109dd6809fe452dfd00e58b25"}, {file = "psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:39db632f6bb862eeccf56660871433e111b6ea58f2caea825571951d4b6aa3da"}, @@ -4586,10 +3597,12 @@ version = "0.7.0" description = "Run a subprocess in a pseudo terminal" optional = false python-versions = "*" +groups = ["main", "dev"] files = [ {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"}, {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"}, ] +markers = {main = "sys_platform != \"win32\" and sys_platform != \"emscripten\"", dev = "sys_platform != \"win32\" and sys_platform != \"emscripten\" or os_name != \"nt\""} [[package]] name = "pure-eval" @@ -4597,6 +3610,7 @@ version = "0.2.3" description = "Safely evaluate AST nodes without side effects" optional = false python-versions = "*" +groups = ["main", "dev"] files = [ {file = "pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0"}, {file = "pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42"}, @@ -4611,10 +3625,12 @@ version = "0.6.1" description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"}, {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"}, ] +markers = {main = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\""} [[package]] name = "pyasn1-modules" @@ -4622,10 +3638,12 @@ version = "0.4.2" description = "A collection of ASN.1-based protocols modules" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "pyasn1_modules-0.4.2-py3-none-any.whl", hash = "sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a"}, {file = "pyasn1_modules-0.4.2.tar.gz", hash = "sha256:677091de870a80aae844b1ca6134f54652fa2c8c5a52aa396440ac3106e941e6"}, ] +markers = {main = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\""} [package.dependencies] pyasn1 = ">=0.6.1,<0.7.0" @@ -4636,10 +3654,12 @@ version = "2.22" description = "C parser in Python" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] files = [ {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"}, {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"}, ] +markers = {main = "implementation_name == \"pypy\""} [[package]] name = "pydantic" @@ -4647,6 +3667,7 @@ version = "2.11.7" description = "Data validation using Python type hints" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "pydantic-2.11.7-py3-none-any.whl", hash = "sha256:dde5df002701f6de26248661f6835bbe296a47bf73990135c7d07ce741b9623b"}, {file = "pydantic-2.11.7.tar.gz", hash = "sha256:d989c3c6cb79469287b1569f7447a17848c998458d49ebe294e975b9baf0f0db"}, @@ -4660,7 +3681,7 @@ typing-inspection = ">=0.4.0" [package.extras] email = ["email-validator (>=2.0.0)"] -timezone = ["tzdata"] +timezone = ["tzdata ; python_version >= \"3.9\" and platform_system == \"Windows\""] [[package]] name = "pydantic-core" @@ -4668,6 +3689,7 @@ version = "2.33.2" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "pydantic_core-2.33.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2b3d326aaef0c0399d9afffeb6367d5e26ddc24d351dbc9c636840ac355dc5d8"}, {file = "pydantic_core-2.33.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0e5b2671f05ba48b94cb90ce55d8bdcaaedb8ba00cc5359f6810fc918713983d"}, @@ -4773,35 +3795,13 @@ files = [ [package.dependencies] typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0" -[[package]] -name = "pydantic-settings" -version = "2.10.1" -description = "Settings management using Pydantic" -optional = false -python-versions = ">=3.9" -files = [ - {file = "pydantic_settings-2.10.1-py3-none-any.whl", hash = "sha256:a60952460b99cf661dc25c29c0ef171721f98bfcb52ef8d9ea4c943d7c8cc796"}, - {file = "pydantic_settings-2.10.1.tar.gz", hash = "sha256:06f0062169818d0f5524420a360d632d5857b83cffd4d42fe29597807a1614ee"}, -] - -[package.dependencies] -pydantic = ">=2.7.0" -python-dotenv = ">=0.21.0" -typing-inspection = ">=0.4.0" - 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version = "3.2.3" description = "pyparsing module - Classes and methods to define and execute parsing grammars" -optional = false +optional = true python-versions = ">=3.9" +groups = ["main"] +markers = "extra == \"all\" or extra == \"google-generativeai\"" files = [ {file = "pyparsing-3.2.3-py3-none-any.whl", hash = "sha256:a749938e02d6fd0b59b356ca504a24982314bb090c383e3cf201c95ef7e2bfcf"}, {file = "pyparsing-3.2.3.tar.gz", hash = "sha256:b9c13f1ab8b3b542f72e28f634bad4de758ab3ce4546e4301970ad6fa77c38be"}, @@ -4865,6 +3850,7 @@ version = "4.3.1" description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "pypdf-4.3.1-py3-none-any.whl", hash = "sha256:64b31da97eda0771ef22edb1bfecd5deee4b72c3d1736b7df2689805076d6418"}, {file = "pypdf-4.3.1.tar.gz", hash = "sha256:b2f37fe9a3030aa97ca86067a56ba3f9d3565f9a791b305c7355d8392c30d91b"}, @@ -4874,10 +3860,10 @@ files = [ typing_extensions = {version = ">=4.0", markers = "python_version < \"3.11\""} [package.extras] -crypto = ["PyCryptodome", "cryptography"] +crypto = ["PyCryptodome ; python_version == \"3.6\"", "cryptography ; python_version >= \"3.7\""] dev = ["black", "flit", "pip-tools", "pre-commit (<2.18.0)", "pytest-cov", "pytest-socket", "pytest-timeout", "pytest-xdist", "wheel"] docs = ["myst_parser", "sphinx", "sphinx_rtd_theme"] -full = ["Pillow (>=8.0.0)", "PyCryptodome", "cryptography"] +full = ["Pillow (>=8.0.0)", "PyCryptodome ; python_version == \"3.6\"", "cryptography ; python_version >= \"3.7\""] image = ["Pillow (>=8.0.0)"] [[package]] @@ -4886,6 +3872,7 @@ version = "8.4.1" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest-8.4.1-py3-none-any.whl", hash = "sha256:539c70ba6fcead8e78eebbf1115e8b589e7565830d7d006a8723f19ac8a0afb7"}, {file = "pytest-8.4.1.tar.gz", hash = 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flaky failures" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "pytest-rerunfailures-12.0.tar.gz", hash = "sha256:784f462fa87fe9bdf781d0027d856b47a4bfe6c12af108f6bd887057a917b48e"}, {file = "pytest_rerunfailures-12.0-py3-none-any.whl", hash = "sha256:9a1afd04e21b8177faf08a9bbbf44de7a0fe3fc29f8ddbe83b9684bd5f8f92a9"}, @@ -4956,6 +3946,7 @@ version = "3.7.0" description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest_xdist-3.7.0-py3-none-any.whl", hash = "sha256:7d3fbd255998265052435eb9daa4e99b62e6fb9cfb6efd1f858d4d8c0c7f0ca0"}, {file = "pytest_xdist-3.7.0.tar.gz", hash = "sha256:f9248c99a7c15b7d2f90715df93610353a485827bc06eefb6566d23f6400f126"}, @@ -4976,6 +3967,7 @@ version = "0.2.0" description = "A python implementation of the ABC Software metric" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "python-abc-0.2.0.tar.gz", hash = "sha256:90017d09fbac7bde4b64b2c7e1b5d22da9055b64b821d1a2b4dc805b450b251a"}, ] @@ -4986,6 +3978,7 @@ version = "2.9.0.post0" description = "Extensions to the standard Python datetime module" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main", "dev", "test"] files = [ {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, @@ -5000,6 +3993,7 @@ version = "1.1.1" description = "Read key-value pairs from a .env file and set them as environment variables" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "python_dotenv-1.1.1-py3-none-any.whl", hash = "sha256:31f23644fe2602f88ff55e1f5c79ba497e01224ee7737937930c448e4d0e24dc"}, {file = "python_dotenv-1.1.1.tar.gz", hash = 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python-versions = ">=3.10.0,<3.14" -content-hash = "a36dfccb03c9a6389a546f920f43f93909e9f310b1ca8c33b3ed383285861a80" +content-hash = "8e36dfa54df9c199a6dcf41adcf454f24daad30e9167ec8f641a10b099b6a22b" diff --git a/pyproject.toml b/pyproject.toml index aea7f5f1..2b27858d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,7 +14,6 @@ python = ">=3.10.0,<3.14" falkordb = "^1.0.9" typing-extensions = "^4.12.1" bs4 = "^0.0.2" -pypdf = "^4.2.0" backoff = "^2.2.1" requests = "^2.32.3" python-abc = "^0.2.0" @@ -28,6 +27,7 @@ openai = { version = "^1.35.9", optional = true } google-generativeai = { version = "^0.8.1", optional = true } litellm = "^1.73.1" ollama = "^0.5.1" +pypdf = "^5.9.0" [tool.poetry.extras] all = ["vertexai", "openai", "google-generativeai"] From 6eb851af7522c1876efea793032719563b9cf89a Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Mon, 11 Aug 2025 19:41:09 +0300 Subject: [PATCH 069/136] Fix poetry and pip file --- poetry.lock | 13 +-------- pyproject.toml | 1 - requirements.txt | 75 ++++++++++++++---------------------------------- 3 files changed, 22 insertions(+), 67 deletions(-) diff --git a/poetry.lock b/poetry.lock index 94869122..27d88e3c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3961,17 +3961,6 @@ psutil = ["psutil (>=3.0)"] setproctitle = ["setproctitle"] testing = ["filelock"] -[[package]] -name = "python-abc" -version = "0.2.0" -description = "A python implementation of the ABC Software metric" -optional = false -python-versions = "*" -groups = ["main"] -files = [ - {file = "python-abc-0.2.0.tar.gz", hash = "sha256:90017d09fbac7bde4b64b2c7e1b5d22da9055b64b821d1a2b4dc805b450b251a"}, -] - [[package]] name = "python-dateutil" version = "2.9.0.post0" @@ -5715,4 +5704,4 @@ vertexai = ["vertexai"] [metadata] lock-version = "2.1" python-versions = ">=3.10.0,<3.14" -content-hash = "a36dfccb03c9a6389a546f920f43f93909e9f310b1ca8c33b3ed383285861a80" +content-hash = "27a805b5df66fb53014401380823306ed7019efb68bd449964f72ddd9bccd1c2" diff --git a/pyproject.toml b/pyproject.toml index aea7f5f1..30f0fed1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,7 +17,6 @@ bs4 = "^0.0.2" pypdf = "^4.2.0" backoff = "^2.2.1" requests = "^2.32.3" -python-abc = "^0.2.0" ratelimit = "^2.2.1" python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" diff --git a/requirements.txt b/requirements.txt index 550d2e56..cfc3fb7b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,54 +1,21 @@ -appnope==0.1.4 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and platform_system == "Darwin" -asttokens==2.4.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -async-timeout==5.0.1 ; python_full_version >= "3.9.0" and python_full_version < "3.11.3" -backoff==2.2.1 ; python_full_version >= "3.9.0" and python_version < "4.0" -beautifulsoup4==4.12.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -bs4==0.0.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -certifi==2024.8.30 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -cffi==1.17.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" -charset-normalizer==3.4.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -colorama==0.4.6 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform == "win32" -comm==0.2.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -debugpy==1.8.8 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -decorator==5.1.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -exceptiongroup==1.2.2 ; python_version >= "3.9" and python_version < "3.11" -executing==2.1.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -falkordb==1.0.9 ; python_full_version >= "3.9.0" and python_version < "4.0" -fix-busted-json==0.0.18 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -idna==3.10 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -importlib-metadata==8.5.0 ; python_full_version >= "3.9.0" and python_version < "3.10" -ipykernel==6.29.5 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ipython==8.18.1 ; python_version >= "3.9" and python_full_version < "4.0.0" -jedi==0.19.2 ; python_version >= "3.9" and python_full_version < "4.0.0" -jupyter-client==8.6.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -jupyter-core==5.7.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -matplotlib-inline==0.1.7 ; python_version >= "3.9" and python_full_version < "4.0.0" -nest-asyncio==1.6.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -packaging==24.2 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -parso==0.8.4 ; python_version >= "3.9" and python_full_version < "4.0.0" -pexpect==4.9.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" -platformdirs==4.3.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -prompt-toolkit==3.0.48 ; python_version >= "3.9" and python_full_version < "4.0.0" -psutil==6.1.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ptyprocess==0.7.0 ; python_version >= "3.9" and python_full_version < "4.0.0" and sys_platform != "win32" -pure-eval==0.2.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -pycparser==2.22 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" and implementation_name == "pypy" -pygments==2.18.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -pypdf==4.3.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-abc==0.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-dateutil==2.9.0.post0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -python-dotenv==1.0.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -pywin32==308 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_full_version >= "3.9.0" and python_full_version < "4.0.0" -pyzmq==26.2.0 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -ratelimit==2.2.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -redis==5.2.0 ; python_full_version >= "3.9.0" and python_version < "4.0" -requests==2.32.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -six==1.16.0 ; python_version >= "3.9" and python_full_version < "4.0.0" -soupsieve==2.6 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -stack-data==0.6.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -tornado==6.4.1 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -traitlets==5.14.3 ; python_version >= "3.9" and python_full_version < "4.0.0" -typing-extensions==4.12.2 ; python_version >= "3.9" and python_full_version < "4.0.0" -urllib3==2.2.3 ; python_full_version >= "3.9.0" and python_full_version < "4.0.0" -wcwidth==0.2.13 ; python_version >= "3.9" and python_full_version < "4.0.0" -zipp==3.21.0 ; python_version >= "3.9" and python_version < "3.10" \ No newline at end of file +# Main Dependencies - Keep in sync with pyproject.toml [tool.poetry.dependencies] +# This file should only contain DIRECT dependencies, not transitive ones +falkordb>=1.0.9 +typing-extensions>=4.12.1 +bs4>=0.0.2 +pypdf>=4.2.0 +backoff>=2.2.1 +requests>=2.32.3 +ratelimit>=2.2.1 +python-dotenv>=1.0.1 +fix-busted-json>=0.0.18 +rich>=13.9.4 +ipykernel>=6.29.5 +litellm>=1.73.1 +ollama>=0.5.1 + +# Optional AI Model Dependencies (install with extras) +# pip install graphrag-sdk[openai] for OpenAI +# pip install graphrag-sdk[vertexai] for Vertex AI +# pip install graphrag-sdk[google-generativeai] for Google AI +# pip install graphrag-sdk[all] for all AI models \ No newline at end of file From ccf16297ad1ad5085df8a5a73bf811d72b82ec81 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Tue, 12 Aug 2025 11:15:36 +0300 Subject: [PATCH 070/136] update gemini version --- graphrag_sdk/models/gemini.py | 2 +- graphrag_sdk/models/litellm.py | 2 +- tests/test_auto_create_ontology.py | 2 +- tests/test_kg.py | 2 +- tests/test_ontology_from_kg.py | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/graphrag_sdk/models/gemini.py b/graphrag_sdk/models/gemini.py index 0d0c5c3f..3a73a4de 100644 --- a/graphrag_sdk/models/gemini.py +++ b/graphrag_sdk/models/gemini.py @@ -12,7 +12,7 @@ class GeminiGenerativeModel(LiteModel): A generative model that interfaces with GoogleAI API for chat completions. Inherits from LiteModel and automatically converts Gemini model names to - LiteLLM format internally (e.g., "gemini-1.5-pro" -> "gemini/gemini-1.5-pro") while + LiteLLM format internally (e.g., "gemini-2.0-flash" -> "gemini/gemini-2.0-flash") while exposing the original model name through the public API. """ diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 496cf19f..e611b4d1 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -40,7 +40,7 @@ def __init__( Examples: - openai/gpt-4.1 - azure/gpt-4.1 - - gemini/gemini-1.5-pro + - gemini/gemini-2.0-flash-exp - ollama/llama3:8b Args: diff --git a/tests/test_auto_create_ontology.py b/tests/test_auto_create_ontology.py index 18689aaf..28353b0d 100644 --- a/tests/test_auto_create_ontology.py +++ b/tests/test_auto_create_ontology.py @@ -24,7 +24,7 @@ def test_auto_detect_ontology(self): sources = [Source(file_path)] - model = GeminiGenerativeModel(model_name="gemini-1.5-flash") + model = GeminiGenerativeModel(model_name="gemini-2.0-flash") boundaries = """ Extract entities and relationships from each page diff --git a/tests/test_kg.py b/tests/test_kg.py index a886a4ae..05433def 100644 --- a/tests/test_kg.py +++ b/tests/test_kg.py @@ -68,7 +68,7 @@ def setUpClass(cls): cls.graph_name = "test_kg" - model = GeminiGenerativeModel(model_name="gemini-1.5-flash") + model = GeminiGenerativeModel(model_name="gemini-2.0-flash") cls.kg = KnowledgeGraph( name=cls.graph_name, ontology=cls.ontology, diff --git a/tests/test_ontology_from_kg.py b/tests/test_ontology_from_kg.py index f0ef9618..761d7ae9 100644 --- a/tests/test_ontology_from_kg.py +++ b/tests/test_ontology_from_kg.py @@ -55,7 +55,7 @@ def ontology_kg_setup(): ontology.add_relation(Relation(label="IN_CITY", source="Restaurant", target="City")) # Create a model and a knowledge graph. - model = GeminiGenerativeModel("gemini-1.5-flash") + model = GeminiGenerativeModel("gemini-2.0-flash") kg = KnowledgeGraph( name="test_ontology", ontology=ontology, From 73e772fc70adb7a4f33eab1c4f466e0f93ee9091 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Tue, 12 Aug 2025 12:46:49 +0300 Subject: [PATCH 071/136] fix ai comments --- poetry.lock | 89 ++++++++++++++++++++---------------------------- pyproject.toml | 6 ++-- requirements.txt | 25 +++++++------- 3 files changed, 52 insertions(+), 68 deletions(-) diff --git a/poetry.lock b/poetry.lock index 27d88e3c..a392738b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -214,7 +214,7 @@ version = "0.1.4" description = "Disable App Nap on macOS >= 10.9" optional = false python-versions = ">=3.6" -groups = ["main", "dev"] +groups = ["dev"] markers = "platform_system == \"Darwin\"" files = [ {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, @@ -300,7 +300,7 @@ version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, @@ -427,21 +427,6 @@ webencodings = "*" [package.extras] css = ["tinycss2 (>=1.1.0,<1.5)"] -[[package]] -name = "bs4" -version = "0.0.2" -description = "Dummy package for Beautiful Soup (beautifulsoup4)" -optional = false -python-versions = "*" -groups = ["main"] -files = [ - {file = "bs4-0.0.2-py2.py3-none-any.whl", hash = "sha256:abf8742c0805ef7f662dce4b51cca104cffe52b835238afc169142ab9b3fbccc"}, - {file = "bs4-0.0.2.tar.gz", hash = "sha256:a48685c58f50fe127722417bae83fe6badf500d54b55f7e39ffe43b798653925"}, -] - -[package.dependencies] -beautifulsoup4 = "*" - [[package]] name = "cachetools" version = "5.5.2" @@ -473,7 +458,7 @@ version = "1.17.1" description = "Foreign Function Interface for Python calling C code." optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"}, {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"}, @@ -543,7 +528,6 @@ files = [ {file = "cffi-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:d016c76bdd850f3c626af19b0542c9677ba156e4ee4fccfdd7848803533ef662"}, {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"}, ] -markers = {main = "implementation_name == \"pypy\""} [package.dependencies] pycparser = "*" @@ -676,7 +660,7 @@ files = [ {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, ] -markers = {main = "sys_platform == \"win32\" or platform_system == \"Windows\"", dev = "sys_platform == \"win32\"", test = "platform_system == \"Windows\" or sys_platform == \"win32\""} +markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\"", test = "platform_system == \"Windows\" or sys_platform == \"win32\""} [[package]] name = "comm" @@ -684,7 +668,7 @@ version = "0.2.2" description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "comm-0.2.2-py3-none-any.whl", hash = "sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3"}, {file = "comm-0.2.2.tar.gz", hash = "sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e"}, @@ -702,7 +686,7 @@ version = "1.8.14" description = "An implementation of the Debug Adapter Protocol for Python" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "debugpy-1.8.14-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:93fee753097e85623cab1c0e6a68c76308cd9f13ffdf44127e6fab4fbf024339"}, {file = "debugpy-1.8.14-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3d937d93ae4fa51cdc94d3e865f535f185d5f9748efb41d0d49e33bf3365bd79"}, @@ -738,7 +722,7 @@ version = "5.2.1" description = "Decorators for Humans" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "decorator-5.2.1-py3-none-any.whl", hash = "sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a"}, {file = "decorator-5.2.1.tar.gz", hash = "sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360"}, @@ -874,7 +858,7 @@ version = "2.2.0" description = "Get the currently executing AST node of a frame, and other information" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "executing-2.2.0-py2.py3-none-any.whl", hash = "sha256:11387150cad388d62750327a53d3339fad4888b39a6fe233c3afbb54ecffd3aa"}, {file = "executing-2.2.0.tar.gz", hash = "sha256:5d108c028108fe2551d1a7b2e8b713341e2cb4fc0aa7dcf966fa4327a5226755"}, @@ -1826,7 +1810,7 @@ version = "6.29.5" description = "IPython Kernel for Jupyter" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "ipykernel-6.29.5-py3-none-any.whl", hash = "sha256:afdb66ba5aa354b09b91379bac28ae4afebbb30e8b39510c9690afb7a10421b5"}, {file = "ipykernel-6.29.5.tar.gz", hash = "sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215"}, @@ -1860,7 +1844,7 @@ version = "8.37.0" description = "IPython: Productive Interactive Computing" optional = false python-versions = ">=3.10" -groups = ["main", "dev"] +groups = ["dev"] markers = "python_version < \"3.11\"" files = [ {file = "ipython-8.37.0-py3-none-any.whl", hash = "sha256:ed87326596b878932dbcb171e3e698845434d8c61b8d8cd474bf663041a9dcf2"}, @@ -1900,7 +1884,7 @@ version = "9.3.0" description = "IPython: Productive Interactive Computing" optional = false python-versions = ">=3.11" -groups = ["main", "dev"] +groups = ["dev"] markers = "python_version >= \"3.11\"" files = [ {file = "ipython-9.3.0-py3-none-any.whl", hash = "sha256:1a0b6dd9221a1f5dddf725b57ac0cb6fddc7b5f470576231ae9162b9b3455a04"}, @@ -1934,7 +1918,7 @@ version = "1.1.1" description = "Defines a variety of Pygments lexers for highlighting IPython code." optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] markers = "python_version >= \"3.11\"" files = [ {file = "ipython_pygments_lexers-1.1.1-py3-none-any.whl", hash = "sha256:a9462224a505ade19a605f71f8fa63c2048833ce50abc86768a0d81d876dc81c"}, @@ -1987,7 +1971,7 @@ version = "0.19.2" description = "An autocompletion tool for Python that can be used for text editors." optional = false python-versions = ">=3.6" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"}, {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"}, @@ -2204,7 +2188,7 @@ version = "8.6.3" description = "Jupyter protocol implementation and client libraries" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "jupyter_client-8.6.3-py3-none-any.whl", hash = "sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f"}, {file = "jupyter_client-8.6.3.tar.gz", hash = "sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419"}, @@ -2252,7 +2236,7 @@ version = "5.8.1" description = "Jupyter core package. A base package on which Jupyter projects rely." optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "jupyter_core-5.8.1-py3-none-any.whl", hash = "sha256:c28d268fc90fb53f1338ded2eb410704c5449a358406e8a948b75706e24863d0"}, {file = "jupyter_core-5.8.1.tar.gz", hash = "sha256:0a5f9706f70e64786b75acba995988915ebd4601c8a52e534a40b51c95f59941"}, @@ -2584,7 +2568,7 @@ version = "0.1.7" description = "Inline Matplotlib backend for Jupyter" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "matplotlib_inline-0.1.7-py3-none-any.whl", hash = "sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca"}, {file = "matplotlib_inline-0.1.7.tar.gz", hash = "sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90"}, @@ -2831,7 +2815,7 @@ version = "1.6.0" description = "Patch asyncio to allow nested event loops" optional = false python-versions = ">=3.5" -groups = ["main", "dev", "test"] +groups = ["dev", "test"] files = [ {file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"}, {file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"}, @@ -3283,7 +3267,7 @@ version = "0.8.4" description = "A Python Parser" optional = false python-versions = ">=3.6" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "parso-0.8.4-py2.py3-none-any.whl", hash = "sha256:a418670a20291dacd2dddc80c377c5c3791378ee1e8d12bffc35420643d43f18"}, {file = "parso-0.8.4.tar.gz", hash = "sha256:eb3a7b58240fb99099a345571deecc0f9540ea5f4dd2fe14c2a99d6b281ab92d"}, @@ -3299,7 +3283,7 @@ version = "4.9.0" description = "Pexpect allows easy control of interactive console applications." optional = false python-versions = "*" -groups = ["main", "dev"] +groups = ["dev"] markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\"" files = [ {file = "pexpect-4.9.0-py2.py3-none-any.whl", hash = "sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523"}, @@ -3315,7 +3299,7 @@ version = "4.3.8" description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`." optional = false python-versions = ">=3.9" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "platformdirs-4.3.8-py3-none-any.whl", hash = "sha256:ff7059bb7eb1179e2685604f4aaf157cfd9535242bd23742eadc3c13542139b4"}, {file = "platformdirs-4.3.8.tar.gz", hash = "sha256:3d512d96e16bcb959a814c9f348431070822a6496326a4be0911c40b5a74c2bc"}, @@ -3409,7 +3393,7 @@ version = "3.0.51" description = "Library for building powerful interactive command lines in Python" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "prompt_toolkit-3.0.51-py3-none-any.whl", hash = "sha256:52742911fde84e2d423e2f9a4cf1de7d7ac4e51958f648d9540e0fb8db077b07"}, {file = "prompt_toolkit-3.0.51.tar.gz", hash = "sha256:931a162e3b27fc90c86f1b48bb1fb2c528c2761475e57c9c06de13311c7b54ed"}, @@ -3573,7 +3557,7 @@ version = "7.0.0" description = "Cross-platform lib for process and system monitoring in Python. NOTE: the syntax of this script MUST be kept compatible with Python 2.7." optional = false python-versions = ">=3.6" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "psutil-7.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:101d71dc322e3cffd7cea0650b09b3d08b8e7c4109dd6809fe452dfd00e58b25"}, {file = "psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:39db632f6bb862eeccf56660871433e111b6ea58f2caea825571951d4b6aa3da"}, @@ -3597,12 +3581,12 @@ version = "0.7.0" description = "Run a subprocess in a pseudo terminal" optional = false python-versions = "*" -groups = ["main", "dev"] +groups = ["dev"] +markers = "os_name != \"nt\" or sys_platform != \"win32\" and sys_platform != \"emscripten\"" files = [ {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"}, {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"}, ] -markers = {main = "sys_platform != \"win32\" and sys_platform != \"emscripten\"", dev = "sys_platform != \"win32\" and sys_platform != \"emscripten\" or os_name != \"nt\""} [[package]] name = "pure-eval" @@ -3610,7 +3594,7 @@ version = "0.2.3" description = "Safely evaluate AST nodes without side effects" optional = false python-versions = "*" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0"}, {file = "pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42"}, @@ -3654,12 +3638,11 @@ version = "2.22" description = "C parser in Python" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"}, {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"}, ] -markers = {main = "implementation_name == \"pypy\""} [[package]] name = "pydantic" @@ -3972,6 +3955,7 @@ files = [ {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, ] +markers = {main = "extra == \"all\" or extra == \"vertexai\""} [package.dependencies] six = ">=1.5" @@ -4024,7 +4008,7 @@ version = "310" description = "Python for Window Extensions" optional = false python-versions = "*" -groups = ["main", "dev", "test"] +groups = ["dev", "test"] files = [ {file = "pywin32-310-cp310-cp310-win32.whl", hash = "sha256:6dd97011efc8bf51d6793a82292419eba2c71cf8e7250cfac03bba284454abc1"}, {file = "pywin32-310-cp310-cp310-win_amd64.whl", hash = "sha256:c3e78706e4229b915a0821941a84e7ef420bf2b77e08c9dae3c76fd03fd2ae3d"}, @@ -4043,7 +4027,7 @@ files = [ {file = "pywin32-310-cp39-cp39-win32.whl", hash = "sha256:851c8d927af0d879221e616ae1f66145253537bbdd321a77e8ef701b443a9a1a"}, {file = "pywin32-310-cp39-cp39-win_amd64.whl", hash = "sha256:96867217335559ac619f00ad70e513c0fcf84b8a3af9fc2bba3b59b97da70475"}, ] -markers = {main = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\"", dev = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\"", test = "platform_system == \"Windows\""} +markers = {dev = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\"", test = "platform_system == \"Windows\""} [[package]] name = "pywinpty" @@ -4132,7 +4116,7 @@ version = "27.0.0" description = "Python bindings for 0MQ" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "pyzmq-27.0.0-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:b973ee650e8f442ce482c1d99ca7ab537c69098d53a3d046676a484fd710c87a"}, {file = "pyzmq-27.0.0-cp310-cp310-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:661942bc7cd0223d569d808f2e5696d9cc120acc73bf3e88a1f1be7ab648a7e4"}, @@ -4759,6 +4743,7 @@ files = [ {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, ] +markers = {main = "extra == \"all\" or extra == \"vertexai\""} [[package]] name = "sniffio" @@ -4973,7 +4958,7 @@ version = "0.6.3" description = "Extract data from python stack frames and tracebacks for informative displays" optional = false python-versions = "*" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"}, {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"}, @@ -5189,7 +5174,7 @@ version = "6.5.1" description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." optional = false python-versions = ">=3.9" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "tornado-6.5.1-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:d50065ba7fd11d3bd41bcad0825227cc9a95154bad83239357094c36708001f7"}, {file = "tornado-6.5.1-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:9e9ca370f717997cb85606d074b0e5b247282cf5e2e1611568b8821afe0342d6"}, @@ -5233,7 +5218,7 @@ version = "5.14.3" description = "Traitlets Python configuration system" optional = false python-versions = ">=3.8" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"}, {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"}, @@ -5403,7 +5388,7 @@ version = "0.2.13" description = "Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" -groups = ["main", "dev"] +groups = ["dev"] files = [ {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, @@ -5703,5 +5688,5 @@ vertexai = ["vertexai"] [metadata] lock-version = "2.1" -python-versions = ">=3.10.0,<3.14" -content-hash = "27a805b5df66fb53014401380823306ed7019efb68bd449964f72ddd9bccd1c2" +python-versions = "^3.10.0, <3.14" +content-hash = "8c03327e4cc58092444e4b5786327f866997ec12b430669e2563f8f8f458ed68" diff --git a/pyproject.toml b/pyproject.toml index 30f0fed1..d0f6eac6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,10 +10,10 @@ homepage = "http://RAG-SDK.readthedocs.io" keywords = ['RAG', 'Graph-RAG', 'KnowledgeGraph'] [tool.poetry.dependencies] -python = ">=3.10.0,<3.14" +python = "^3.10.0, <3.14" falkordb = "^1.0.9" typing-extensions = "^4.12.1" -bs4 = "^0.0.2" +beautifulsoup4 = "^4.12.3" pypdf = "^4.2.0" backoff = "^2.2.1" requests = "^2.32.3" @@ -21,7 +21,6 @@ ratelimit = "^2.2.1" python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" rich = "^13.9.4" -ipykernel = "^6.29.5" vertexai = { version = "^1.49.0", optional = true } openai = { version = "^1.35.9", optional = true } google-generativeai = { version = "^0.8.1", optional = true } @@ -43,6 +42,7 @@ sphinx = "^7.3.7" sphinx-rtd-theme = "^2.0.0" pandas = "^2.2.2" jupyter = "^1.0.0" +ipykernel = "^6.29.5" [build-system] requires = ["poetry-core"] diff --git a/requirements.txt b/requirements.txt index cfc3fb7b..a05be866 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,18 +1,17 @@ # Main Dependencies - Keep in sync with pyproject.toml [tool.poetry.dependencies] # This file should only contain DIRECT dependencies, not transitive ones -falkordb>=1.0.9 -typing-extensions>=4.12.1 -bs4>=0.0.2 -pypdf>=4.2.0 -backoff>=2.2.1 -requests>=2.32.3 -ratelimit>=2.2.1 -python-dotenv>=1.0.1 -fix-busted-json>=0.0.18 -rich>=13.9.4 -ipykernel>=6.29.5 -litellm>=1.73.1 -ollama>=0.5.1 +falkordb>=1.0.9,<2.0.0 +typing-extensions>=4.12.1,<5.0.0 +beautifulsoup4>=4.12.3,<5.0.0 +pypdf>=4.2.0,<5.0.0 +backoff>=2.2.1,<3.0.0 +requests>=2.32.3,<3.0.0 +ratelimit>=2.2.1,<3.0.0 +python-dotenv>=1.0.1,<2.0.0 +fix-busted-json>=0.0.18,<0.1.0 +rich>=13.9.4,<14.0.0 +litellm>=1.73.1,<2.0.0 +ollama>=0.5.1,<1.0.0 # Optional AI Model Dependencies (install with extras) # pip install graphrag-sdk[openai] for OpenAI From 9e8cc67bec3713210693c0ecd011be534a8ca3cd Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Tue, 12 Aug 2025 13:01:02 +0300 Subject: [PATCH 072/136] fix ai comments --- requirements.txt | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/requirements.txt b/requirements.txt index a05be866..246fcc4f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,8 +13,12 @@ rich>=13.9.4,<14.0.0 litellm>=1.73.1,<2.0.0 ollama>=0.5.1,<1.0.0 -# Optional AI Model Dependencies (install with extras) -# pip install graphrag-sdk[openai] for OpenAI -# pip install graphrag-sdk[vertexai] for Vertex AI -# pip install graphrag-sdk[google-generativeai] for Google AI -# pip install graphrag-sdk[all] for all AI models \ No newline at end of file +# Core model providers (always installed): +# - litellm: LLM router/abstraction layer +# - ollama: Local model support + +# Optional AI Model Dependencies (install with extras): +# pip install graphrag-sdk[openai] # OpenAI models +# pip install graphrag-sdk[vertexai] # Google Vertex AI +# pip install graphrag-sdk[google-generativeai] # Google AI Studio +# pip install graphrag-sdk[all] # All optional providers \ No newline at end of file From 4aba542012660c9d08787a12681ce1b81d66378f Mon Sep 17 00:00:00 2001 From: Gal Shubeli <124919062+galshubeli@users.noreply.github.com> Date: Tue, 12 Aug 2025 13:25:34 +0300 Subject: [PATCH 073/136] Update litellm.py --- graphrag_sdk/models/litellm.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index e611b4d1..84ac8422 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -40,7 +40,7 @@ def __init__( Examples: - openai/gpt-4.1 - azure/gpt-4.1 - - gemini/gemini-2.0-flash-exp + - gemini/gemini-2.0-flash - ollama/llama3:8b Args: From 8d549d503714e1b61573516847b81ca04b845c92 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 13:35:14 +0300 Subject: [PATCH 074/136] remove deps, ollama included inside litellm --- graphrag_sdk/models/litellm.py | 40 -- poetry.lock | 604 +---------------------------- pyproject.toml | 11 +- requirements.txt | 13 +- tests/test_auto_create_ontology.py | 7 +- 5 files changed, 23 insertions(+), 652 deletions(-) diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 84ac8422..1e64568e 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -2,14 +2,6 @@ from typing import Optional, Iterator from litellm import completion, validate_environment, utils as litellm_utils -# Optional import for Ollama -try: - from ollama import Client as OllamaClient - OLLAMA_AVAILABLE = True -except ImportError: - OllamaClient = None - OLLAMA_AVAILABLE = False - from .model import ( GenerativeModel, GenerativeModelConfig, @@ -56,11 +48,6 @@ def __init__( self._internal_model_name, provider, _, _ = litellm_utils.get_llm_provider(model_name) self.model = model_name - if provider == "ollama": - if not OLLAMA_AVAILABLE: - raise ValueError("Ollama client not available. Install with: pip install ollama") - self.ollama_client = OllamaClient() - self.check_and_pull_model() if not self.check_valid_key(model_name): raise ValueError(f"Invalid keys for model {model_name}.") @@ -97,33 +84,6 @@ def check_valid_key(self, model: str): except Exception as e: return False - def check_and_pull_model(self) -> None: - """ - Checks if the specified model is available locally, and pulls it if not. - - Logs: - - Info: If the model is already available or after successfully pulling the model. - - Error: If there is a failure in pulling the model. - - Raises: - Exception: If there is an error during the model pull process. - """ - # Get the list of available models - response = self.ollama_client.list() # This returns a dictionary - available_models = [model['name'] for model in response['models']] # Extract model names - - # Check if the model is already pulled - if self._internal_model_name in available_models: - logger.info(f"The model '{self._internal_model_name}' is already available.") - else: - logger.info(f"Pulling the model '{self._internal_model_name}'...") - try: - self.ollama_client.pull(self._internal_model_name) # Pull the model - logger.info(f"Model '{self._internal_model_name}' pulled successfully.") - except Exception as e: - logger.error(f"Failed to pull the model '{self._internal_model_name}': {e}") - raise ValueError(f"Failed to pull the model '{self._internal_model_name}': {e}") - def start_chat(self, system_instruction: Optional[str] = None) -> GenerativeModelChatSession: """ Start a new chat session. diff --git a/poetry.lock b/poetry.lock index a392738b..48b40959 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -433,12 +433,11 @@ version = "5.5.2" description = "Extensible memoizing collections and decorators" optional = false python-versions = ">=3.7" -groups = ["main", "test"] +groups = ["test"] files = [ {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"}, {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"}, ] -markers = {main = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\""} [[package]] name = "certifi" @@ -793,19 +792,6 @@ files = [ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, ] -[[package]] -name = "docstring-parser" -version = "0.16" -description = "Parse Python docstrings in reST, Google and Numpydoc format" -optional = true -python-versions = ">=3.6,<4.0" -groups = ["main"] -markers = "extra == \"all\" or extra == \"vertexai\"" -files = [ - {file = "docstring_parser-0.16-py3-none-any.whl", hash = "sha256:bf0a1387354d3691d102edef7ec124f219ef639982d096e26e3b60aeffa90637"}, - {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"}, -] - [[package]] name = "docutils" version = "0.20.1" @@ -1091,97 +1077,17 @@ test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"] tqdm = ["tqdm"] -[[package]] -name = "google-ai-generativelanguage" -version = "0.6.15" -description = "Google Ai Generativelanguage API client library" -optional = true -python-versions = ">=3.7" -groups = ["main"] -markers = "extra == \"all\" or extra == \"google-generativeai\"" -files = [ - {file = "google_ai_generativelanguage-0.6.15-py3-none-any.whl", hash = "sha256:5a03ef86377aa184ffef3662ca28f19eeee158733e45d7947982eb953c6ebb6c"}, - {file = "google_ai_generativelanguage-0.6.15.tar.gz", hash = "sha256:8f6d9dc4c12b065fe2d0289026171acea5183ebf2d0b11cefe12f3821e159ec3"}, -] - -[package.dependencies] -google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]} -google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev" -proto-plus = [ - {version = ">=1.22.3,<2.0.0dev"}, - {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""}, -] -protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev" - -[[package]] -name = "google-api-core" -version = "2.25.1" -description = "Google API client core library" -optional = true -python-versions = ">=3.7" -groups = ["main"] -markers = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\"" -files = [ - {file = "google_api_core-2.25.1-py3-none-any.whl", hash = "sha256:8a2a56c1fef82987a524371f99f3bd0143702fecc670c72e600c1cda6bf8dbb7"}, - {file = "google_api_core-2.25.1.tar.gz", hash = "sha256:d2aaa0b13c78c61cb3f4282c464c046e45fbd75755683c9c525e6e8f7ed0a5e8"}, -] - -[package.dependencies] -google-auth = ">=2.14.1,<3.0.0" -googleapis-common-protos = ">=1.56.2,<2.0.0" -grpcio = [ - {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}, - {version = ">=1.33.2,<2.0.0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""}, -] -grpcio-status = [ - {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}, - {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""}, -] -proto-plus = [ - {version = ">=1.22.3,<2.0.0"}, - {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""}, -] -protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0" -requests = ">=2.18.0,<3.0.0" - -[package.extras] -async-rest = ["google-auth[aiohttp] (>=2.35.0,<3.0.0)"] -grpc = ["grpcio (>=1.33.2,<2.0.0)", "grpcio (>=1.49.1,<2.0.0) ; python_version >= \"3.11\"", "grpcio-status (>=1.33.2,<2.0.0)", "grpcio-status (>=1.49.1,<2.0.0) ; python_version >= \"3.11\""] -grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"] -grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"] - -[[package]] -name = "google-api-python-client" -version = "2.173.0" -description = "Google API Client Library for Python" -optional = true -python-versions = ">=3.7" -groups = ["main"] -markers = "extra == \"all\" or extra == \"google-generativeai\"" -files = [ - {file = "google_api_python_client-2.173.0-py3-none-any.whl", hash = "sha256:16a8e81c772dd116f5c4ee47d83643149e1367dc8fb4f47cb471fbcb5c7d7ac7"}, - {file = "google_api_python_client-2.173.0.tar.gz", hash = "sha256:b537bc689758f4be3e6f40d59a6c0cd305abafdea91af4bc66ec31d40c08c804"}, -] - -[package.dependencies] -google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0" -google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0" -google-auth-httplib2 = ">=0.2.0,<1.0.0" -httplib2 = ">=0.19.0,<1.0.0" -uritemplate = ">=3.0.1,<5" - [[package]] name = "google-auth" version = "2.40.3" description = "Google Authentication Library" optional = false python-versions = ">=3.7" -groups = ["main", "test"] +groups = ["test"] files = [ {file = "google_auth-2.40.3-py2.py3-none-any.whl", hash = "sha256:1370d4593e86213563547f97a92752fc658456fe4514c809544f330fed45a7ca"}, {file = "google_auth-2.40.3.tar.gz", hash = "sha256:500c3a29adedeb36ea9cf24b8d10858e152f2412e3ca37829b3fa18e33d63b77"}, ] -markers = {main = "extra == \"all\" or extra == \"vertexai\" or extra == \"google-generativeai\""} [package.dependencies] cachetools = ">=2.0.0,<6.0" @@ -1198,222 +1104,6 @@ requests = ["requests (>=2.20.0,<3.0.0)"] testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "flask", "freezegun", "grpcio", "mock", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"] urllib3 = ["packaging", "urllib3"] -[[package]] -name = "google-auth-httplib2" -version = "0.2.0" -description = "Google Authentication Library: httplib2 transport" -optional = true -python-versions = "*" -groups = ["main"] -markers = "extra 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-lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"] -metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"] -pipelines = ["pyyaml (>=5.3.1,<7)"] -prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<=0.109.1)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"] -preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"] -private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"] -rapid-evaluation = ["nest-asyncio (>=1.0.0,<1.6.0)", "pandas (>=1.0.0,<2.2.0)"] -ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3) ; python_version < \"3.11\"", "ray[default] (>=2.5,<=2.9.3) ; python_version == \"3.11\""] -ray-testing = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pytest-xdist", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3) ; python_version < \"3.11\"", "ray[default] (>=2.5,<=2.9.3) ; python_version == \"3.11\"", "ray[train] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "scikit-learn", "tensorflow", "torch (>=2.0.0,<2.1.0)", "xgboost", "xgboost-ray"] -reasoningengine = ["cloudpickle (>=2.2.1,<3.0)", "pydantic (<3)"] -tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev) ; python_version <= \"3.11\""] -testing = ["bigframes ; python_version >= \"3.10\"", "cloudpickle (<3.0)", "cloudpickle (>=2.2.1,<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "nest-asyncio (>=1.0.0,<1.6.0)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1) ; python_version == \"3.11\"", "pyarrow (>=14.0.0) ; python_version >= \"3.12\"", "pyarrow (>=3.0.0,<8.0dev) ; python_version < \"3.11\"", "pyarrow (>=6.0.1)", "pydantic (<2)", "pydantic (<3)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3) ; python_version < \"3.11\"", "ray[default] (>=2.5,<=2.9.3) ; python_version == \"3.11\"", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0) ; python_version <= \"3.11\"", "tensorflow (==2.16.1) ; python_version > \"3.11\"", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev) ; python_version <= \"3.11\"", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0) ; python_version <= \"3.11\"", "torch (>=2.2.0) ; python_version > \"3.11\"", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"] -vizier = ["google-vizier (>=0.1.6)"] -xai = ["tensorflow (>=2.3.0,<3.0.0dev)"] - [[package]] name = "wcwidth" version = "0.2.13" @@ -5680,13 +5118,7 @@ enabler = ["pytest-enabler (>=2.2)"] test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] -[extras] -all = ["google-generativeai", "openai", "vertexai"] -google-generativeai = ["google-generativeai"] -openai = ["openai"] -vertexai = ["vertexai"] - [metadata] lock-version = "2.1" python-versions = "^3.10.0, <3.14" -content-hash = "8c03327e4cc58092444e4b5786327f866997ec12b430669e2563f8f8f458ed68" +content-hash = "88d705e9f71cb9a5dde3ab2c84e4326b5b52327283590cc8d8bf06d0039c81aa" diff --git a/pyproject.toml b/pyproject.toml index d0f6eac6..85f799e4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "graphrag_sdk" -version = "0.8.0" +version = "0.8.1" license = "MIT" description = "Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] @@ -21,17 +21,10 @@ ratelimit = "^2.2.1" python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" rich = "^13.9.4" -vertexai = { version = "^1.49.0", optional = true } -openai = { version = "^1.35.9", optional = true } -google-generativeai = { version = "^0.8.1", optional = true } litellm = "^1.73.1" -ollama = "^0.5.1" [tool.poetry.extras] -all = ["vertexai", "openai", "google-generativeai"] -openai = ["openai"] -vertexai = ["vertexai"] -google-generativeai = ["google-generativeai"] +# All optional extras removed - litellm handles all providers [tool.poetry.group.test.dependencies] pytest = "^8.2.1" diff --git a/requirements.txt b/requirements.txt index 246fcc4f..600ddfd9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,15 +10,4 @@ ratelimit>=2.2.1,<3.0.0 python-dotenv>=1.0.1,<2.0.0 fix-busted-json>=0.0.18,<0.1.0 rich>=13.9.4,<14.0.0 -litellm>=1.73.1,<2.0.0 -ollama>=0.5.1,<1.0.0 - -# Core model providers (always installed): -# - litellm: LLM router/abstraction layer -# - ollama: Local model support - -# Optional AI Model Dependencies (install with extras): -# pip install graphrag-sdk[openai] # OpenAI models -# pip install graphrag-sdk[vertexai] # Google Vertex AI -# pip install graphrag-sdk[google-generativeai] # Google AI Studio -# pip install graphrag-sdk[all] # All optional providers \ No newline at end of file +litellm>=1.73.1,<2.0.0 \ No newline at end of file diff --git a/tests/test_auto_create_ontology.py b/tests/test_auto_create_ontology.py index 28353b0d..8d83adb5 100644 --- a/tests/test_auto_create_ontology.py +++ b/tests/test_auto_create_ontology.py @@ -3,15 +3,12 @@ from graphrag_sdk.ontology import Ontology import unittest from graphrag_sdk.source import Source -from graphrag_sdk.models.gemini import GeminiGenerativeModel -import vertexai +from graphrag_sdk.models.litellm import LiteModel import os import logging logging.basicConfig(level=logging.DEBUG) -vertexai.init(project=os.getenv("PROJECT_ID"), location=os.getenv("REGION")) - class TestAutoDetectOntology(unittest.TestCase): """ @@ -24,7 +21,7 @@ def test_auto_detect_ontology(self): sources = [Source(file_path)] - model = GeminiGenerativeModel(model_name="gemini-2.0-flash") + model = LiteModel(model_name="gemini/gemini-2.0-flash") boundaries = """ Extract entities and relationships from each page From 5ff0c5b353f1ddf865c48034ac6a2bafc449943b Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 14:20:15 +0300 Subject: [PATCH 075/136] auto generate requirements.txt file from toml via ci --- .github/workflows/sync-dependencies.yml | 81 +++++++++++++++++++++++++ requirements.txt | 13 ---- 2 files changed, 81 insertions(+), 13 deletions(-) create mode 100644 .github/workflows/sync-dependencies.yml delete mode 100644 requirements.txt diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml new file mode 100644 index 00000000..474d63a7 --- /dev/null +++ b/.github/workflows/sync-dependencies.yml @@ -0,0 +1,81 @@ +name: Sync Dependencies + +on: + push: + paths: ['pyproject.toml'] + branches: [main] + pull_request: + paths: ['pyproject.toml'] + branches: [main] + +jobs: + sync: + runs-on: ubuntu-latest + permissions: + contents: write + steps: + - uses: actions/checkout@v4 + with: + token: ${{ secrets.GITHUB_TOKEN }} + + - name: Setup Python + uses: actions/setup-python@v4 + with: + python-version: '3.x' + + - name: Sync requirements + run: | + # Generate simple requirements.txt with only the 11 main dependencies + python3 -c " +import re + +# Read pyproject.toml +with open('pyproject.toml', 'r') as f: + content = f.read() + +# Find the dependencies section +start = content.find('[tool.poetry.dependencies]') +end = content.find('[', start + 1) +if end == -1: + deps_section = content[start:] +else: + deps_section = content[start:end] + +# Extract dependencies +lines = deps_section.split('\n')[1:] # Skip the section header +deps = [] + +for line in lines: + line = line.strip() + if '=' in line and not line.startswith('python ') and not line.startswith('#') and line: + # Extract package name and version + name = line.split('=')[0].strip() + version = line.split('\"')[1] if '\"' in line else line.split('=')[1].strip() + + # Convert ^1.0.9 to >=1.0.9,<2.0.0 + if version.startswith('^'): + base = version[1:] + major = base.split('.')[0] + next_major = str(int(major) + 1) + pip_version = f'>={base},<{next_major}.0.0' + else: + pip_version = f'>={version}' + + deps.append(f'{name}{pip_version}') + +# Write requirements.txt +with open('requirements.txt', 'w') as f: + f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') + f.write('# This file contains only DIRECT dependencies, not transitive ones\n') + f.write('# Source of truth: pyproject.toml\n\n') + for dep in sorted(deps): + f.write(dep + '\n') + +print(f'✅ Generated requirements.txt with {len(deps)} direct dependencies') +" + + git config --local user.email "action@github.com" + git config --local user.name "GitHub Action" + git add requirements.txt + git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml [11 direct deps]" || exit 0 + git push diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 600ddfd9..00000000 --- a/requirements.txt +++ /dev/null @@ -1,13 +0,0 @@ -# Main Dependencies - Keep in sync with pyproject.toml [tool.poetry.dependencies] -# This file should only contain DIRECT dependencies, not transitive ones -falkordb>=1.0.9,<2.0.0 -typing-extensions>=4.12.1,<5.0.0 -beautifulsoup4>=4.12.3,<5.0.0 -pypdf>=4.2.0,<5.0.0 -backoff>=2.2.1,<3.0.0 -requests>=2.32.3,<3.0.0 -ratelimit>=2.2.1,<3.0.0 -python-dotenv>=1.0.1,<2.0.0 -fix-busted-json>=0.0.18,<0.1.0 -rich>=13.9.4,<14.0.0 -litellm>=1.73.1,<2.0.0 \ No newline at end of file From 7bf1f1b02dcda5d6cb2c9b93f1c1de441ec27bc0 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 14:23:24 +0300 Subject: [PATCH 076/136] update ci --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 5b0dcfcb..c95d44a3 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -62,7 +62,7 @@ jobs: curl -sSL https://install.python-poetry.org | python3 - - name: Install dependencies - run: poetry install --with test --extras "all" + run: poetry install --with test - name: Wait for Ollama to be ready run: | From 09cd39f32d16300ccef82e55f430a8acad26db3e Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 14:44:18 +0300 Subject: [PATCH 077/136] fix tests --- graphrag_sdk/attribute.py | 1 - 1 file changed, 1 deletion(-) diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index b1818a17..d28ec986 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -3,7 +3,6 @@ import logging from enum import Enum from typing import Union, Optional -from graphrag_sdk.fixtures.regex import * logger = logging.getLogger(__name__) From 3bdc6a8a1c283708b6ca3bdc5a5645a5a78be0c0 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 15:40:20 +0300 Subject: [PATCH 078/136] =?UTF-8?q?=F0=9F=94=A7=20Fix=20CI=20workflow:=20i?= =?UTF-8?q?mplement=20robust=20TOML=20parsing=20and=20smart=20commit=20log?= =?UTF-8?q?ic?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Use tomllib/tomli for proper TOML parsing instead of brittle string parsing - Use heredoc to fix YAML lint issues with embedded Python - Only commit when there are actual changes (prevent empty commits) - Guard push by event type to prevent PR failures - Remove hardcoded dependency count from commit message - Support complex dependency specs (git, url, extras) - Add proper Python compatibility layer --- .github/workflows/sync-dependencies.yml | 109 +++++++++++++++--------- 1 file changed, 71 insertions(+), 38 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 474d63a7..4d319244 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -23,59 +23,92 @@ jobs: with: python-version: '3.x' + - name: Install tomli for Python <3.11 + run: | + python3 -c "import sys; exit(0 if sys.version_info >= (3, 11) else 1)" || pip install tomli + - name: Sync requirements run: | - # Generate simple requirements.txt with only the 11 main dependencies - python3 -c " -import re + # Generate simple requirements.txt with only the main (direct) dependencies + python3 - <<'PY' +import sys +try: + import tomllib # Python 3.11+ +except ModuleNotFoundError: + import tomli as tomllib -# Read pyproject.toml -with open('pyproject.toml', 'r') as f: - content = f.read() +def caret_to_range(v: str) -> str: + base = v[1:] + major = base.split('.')[0] + return f'>={base},<{int(major)+1}.0.0' -# Find the dependencies section -start = content.find('[tool.poetry.dependencies]') -end = content.find('[', start + 1) -if end == -1: - deps_section = content[start:] -else: - deps_section = content[start:end] +with open('pyproject.toml', 'rb') as f: + data = tomllib.load(f) -# Extract dependencies -lines = deps_section.split('\n')[1:] # Skip the section header +deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) deps = [] -for line in lines: - line = line.strip() - if '=' in line and not line.startswith('python ') and not line.startswith('#') and line: - # Extract package name and version - name = line.split('=')[0].strip() - version = line.split('\"')[1] if '\"' in line else line.split('=')[1].strip() - - # Convert ^1.0.9 to >=1.0.9,<2.0.0 - if version.startswith('^'): - base = version[1:] - major = base.split('.')[0] - next_major = str(int(major) + 1) - pip_version = f'>={base},<{next_major}.0.0' +for name, spec in deps_table.items(): + if name.lower() == 'python': + continue + + extras = [] + req_line = None + version = None + + if isinstance(spec, str): + version = spec.strip() + elif isinstance(spec, dict): + extras = spec.get('extras') or [] + if 'version' in spec: + version = str(spec['version']).strip() + elif 'git' in spec: + ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' + frag = f'@{ref}' if ref else '' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" + elif 'url' in spec: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ {spec['url']}" else: - pip_version = f'>={version}' - - deps.append(f'{name}{pip_version}') + # Unsupported for requirements (e.g., local path). Skip. + continue + else: + continue + + if req_line is None: + def normalize(ver: str) -> str: + if ver.startswith('^'): + return caret_to_range(ver) + if any(op in ver for op in ('<', '>', '!=', '==', '~=')): + return ver + return f'>={ver}' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part}{normalize(version)}" + + deps.append(req_line) -# Write requirements.txt -with open('requirements.txt', 'w') as f: +deps = sorted(set(deps)) +with open('requirements.txt', 'w', encoding='utf-8') as f: f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') - f.write('# This file contains only DIRECT dependencies, not transitive ones\n') + f.write('# This file contains only DIRECT dependencies, not transitive ones\n') f.write('# Source of truth: pyproject.toml\n\n') - for dep in sorted(deps): + for dep in deps: f.write(dep + '\n') print(f'✅ Generated requirements.txt with {len(deps)} direct dependencies') -" +PY git config --local user.email "action@github.com" git config --local user.name "GitHub Action" git add requirements.txt - git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml [11 direct deps]" || exit 0 - git push + if git diff --staged --quiet; then + echo "No changes to commit" + else + git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" + if [ "${GITHUB_EVENT_NAME}" = "push" ]; then + git push + else + echo "Skipping push on event: ${GITHUB_EVENT_NAME}" + fi + fi From a388b133786bdfb58772d85901ffb3837ebd67f7 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Wed, 13 Aug 2025 18:46:55 +0300 Subject: [PATCH 079/136] Fix YAML indentation in sync-dependencies workflow - Properly indent Python heredoc content in YAML - Fixes YAML parsing error --- .github/workflows/sync-dependencies.yml | 116 ++++++++++++------------ 1 file changed, 58 insertions(+), 58 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 4d319244..4cf8c140 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -3,7 +3,7 @@ name: Sync Dependencies on: push: paths: ['pyproject.toml'] - branches: [main] + branches: [main, fix-poetry-adn-pip-file] # Test on current branch pull_request: paths: ['pyproject.toml'] branches: [main] @@ -31,73 +31,73 @@ jobs: run: | # Generate simple requirements.txt with only the main (direct) dependencies python3 - <<'PY' -import sys -try: - import tomllib # Python 3.11+ -except ModuleNotFoundError: - import tomli as tomllib + import sys + try: + import tomllib # Python 3.11+ + except ModuleNotFoundError: + import tomli as tomllib -def caret_to_range(v: str) -> str: - base = v[1:] - major = base.split('.')[0] - return f'>={base},<{int(major)+1}.0.0' + def caret_to_range(v: str) -> str: + base = v[1:] + major = base.split('.')[0] + return f'>={base},<{int(major)+1}.0.0' -with open('pyproject.toml', 'rb') as f: - data = tomllib.load(f) + with open('pyproject.toml', 'rb') as f: + data = tomllib.load(f) -deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) -deps = [] + deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) + deps = [] -for name, spec in deps_table.items(): - if name.lower() == 'python': - continue + for name, spec in deps_table.items(): + if name.lower() == 'python': + continue - extras = [] - req_line = None - version = None + extras = [] + req_line = None + version = None - if isinstance(spec, str): - version = spec.strip() - elif isinstance(spec, dict): - extras = spec.get('extras') or [] - if 'version' in spec: - version = str(spec['version']).strip() - elif 'git' in spec: - ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' - frag = f'@{ref}' if ref else '' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" - elif 'url' in spec: - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ {spec['url']}" - else: - # Unsupported for requirements (e.g., local path). Skip. - continue - else: - continue + if isinstance(spec, str): + version = spec.strip() + elif isinstance(spec, dict): + extras = spec.get('extras') or [] + if 'version' in spec: + version = str(spec['version']).strip() + elif 'git' in spec: + ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' + frag = f'@{ref}' if ref else '' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" + elif 'url' in spec: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ {spec['url']}" + else: + # Unsupported for requirements (e.g., local path). Skip. + continue + else: + continue - if req_line is None: - def normalize(ver: str) -> str: - if ver.startswith('^'): - return caret_to_range(ver) - if any(op in ver for op in ('<', '>', '!=', '==', '~=')): - return ver - return f'>={ver}' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part}{normalize(version)}" + if req_line is None: + def normalize(ver: str) -> str: + if ver.startswith('^'): + return caret_to_range(ver) + if any(op in ver for op in ('<', '>', '!=', '==', '~=')): + return ver + return f'>={ver}' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part}{normalize(version)}" - deps.append(req_line) + deps.append(req_line) -deps = sorted(set(deps)) -with open('requirements.txt', 'w', encoding='utf-8') as f: - f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') - f.write('# This file contains only DIRECT dependencies, not transitive ones\n') - f.write('# Source of truth: pyproject.toml\n\n') - for dep in deps: - f.write(dep + '\n') + deps = sorted(set(deps)) + with open('requirements.txt', 'w', encoding='utf-8') as f: + f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') + f.write('# This file contains only DIRECT dependencies, not transitive ones\n') + f.write('# Source of truth: pyproject.toml\n\n') + for dep in deps: + f.write(dep + '\n') -print(f'✅ Generated requirements.txt with {len(deps)} direct dependencies') -PY + print(f'✅ Generated requirements.txt with {len(deps)} direct dependencies') + PY git config --local user.email "action@github.com" git config --local user.name "GitHub Action" From c2a2db0165e6d2dca9226b04acc94c39408fbcaf Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Thu, 14 Aug 2025 12:33:16 +0300 Subject: [PATCH 080/136] Update sync-dependencies.yml --- .github/workflows/sync-dependencies.yml | 248 ++++++++++++++++++------ 1 file changed, 193 insertions(+), 55 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 4cf8c140..23f3a17e 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -3,7 +3,7 @@ name: Sync Dependencies on: push: paths: ['pyproject.toml'] - branches: [main, fix-poetry-adn-pip-file] # Test on current branch + branches: [main] pull_request: paths: ['pyproject.toml'] branches: [main] @@ -13,39 +13,69 @@ jobs: runs-on: ubuntu-latest permissions: contents: write + pull-requests: write steps: - uses: actions/checkout@v4 with: token: ${{ secrets.GITHUB_TOKEN }} - + fetch-depth: 0 + - name: Setup Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v5 with: - python-version: '3.x' - + python-version: '3.11' + cache: 'pip' + - name: Install tomli for Python <3.11 run: | - python3 -c "import sys; exit(0 if sys.version_info >= (3, 11) else 1)" || pip install tomli - + python3 -c "import sys; sys.exit(0 if sys.version_info >= (3, 11) else 1)" || python3 -m pip install -q tomli + - name: Sync requirements run: | - # Generate simple requirements.txt with only the main (direct) dependencies + set -euo pipefail python3 - <<'PY' import sys + import re try: - import tomllib # Python 3.11+ + import tomllib except ModuleNotFoundError: import tomli as tomllib def caret_to_range(v: str) -> str: + """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics.""" base = v[1:] - major = base.split('.')[0] - return f'>={base},<{int(major)+1}.0.0' + parts = base.split('.') + + def num(seg): + m = re.match(r'(\d+)', str(seg)) + return int(m.group(1)) if m else 0 + + major = num(parts[0]) if len(parts) > 0 else 0 + minor = num(parts[1]) if len(parts) > 1 else 0 + patch = num(parts[2]) if len(parts) > 2 else 0 + + # Proper caret semantics: ^0.x.y -> <0.(x+1).0, ^x.y.z -> <(x+1).0.0 + if major > 0: + upper = f'{major+1}.0.0' + elif minor > 0: + upper = f'0.{minor+1}.0' + else: + upper = f'0.0.{patch+1}' + + return f'>={base},<{upper}' - with open('pyproject.toml', 'rb') as f: - data = tomllib.load(f) + try: + with open('pyproject.toml', 'rb') as f: + data = tomllib.load(f) + except Exception as e: + print(f"❌ Error reading pyproject.toml: {e}") + sys.exit(1) deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) + if not deps_table: + print("❌ No dependencies found in pyproject.toml") + sys.exit(1) + deps = [] for name, spec in deps_table.items(): @@ -55,60 +85,168 @@ jobs: extras = [] req_line = None version = None + markers = None - if isinstance(spec, str): - version = spec.strip() - elif isinstance(spec, dict): - extras = spec.get('extras') or [] - if 'version' in spec: - version = str(spec['version']).strip() - elif 'git' in spec: - ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' - frag = f'@{ref}' if ref else '' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" - elif 'url' in spec: - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ {spec['url']}" + try: + if isinstance(spec, str): + version = spec.strip() + elif isinstance(spec, dict): + extras = sorted(spec.get('extras') or []) + markers = (spec.get('markers') or '').strip() or None + + if 'version' in spec: + version = str(spec['version']).strip() + elif 'git' in spec: + ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' + frag = f'@{ref}' if ref else '' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" + if markers: + req_line += f"; {markers}" + elif 'url' in spec: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ {spec['url']}" + if markers: + req_line += f"; {markers}" + elif 'path' in spec: + # Skip local path dependencies as they can't be in requirements.txt + print(f"⚠️ Skipping local path dependency: {name}") + continue + else: + print(f"⚠️ Skipping unsupported dependency spec for {name}: {spec}") + continue else: - # Unsupported for requirements (e.g., local path). Skip. + print(f"⚠️ Skipping unsupported dependency type for {name}: {type(spec)}") continue - else: - continue - if req_line is None: - def normalize(ver: str) -> str: - if ver.startswith('^'): - return caret_to_range(ver) - if any(op in ver for op in ('<', '>', '!=', '==', '~=')): - return ver - return f'>={ver}' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part}{normalize(version)}" + if req_line is None and version is not None: + def normalize(ver: str) -> str: + ver = ver.strip() + if not ver: + return '' + if ver.startswith('^'): + return caret_to_range(ver) + # Check for existing constraints/operators + has_constraint = any(op in ver for op in ['<', '>', '!=', '==', '===', '~=', '~', '*']) + has_space = ' ' in ver # Combined constraints like ">=1.0 <2.0" + return ver if (has_constraint or has_space) else f'>={ver}' + + normalized_version = normalize(version) + if normalized_version: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part}{normalized_version}" + if markers: + req_line += f"; {markers}" + + if req_line: + deps.append(req_line) + print(f"✓ Added dependency: {req_line}") + + except Exception as e: + print(f"⚠️ Error processing dependency {name}: {e}") + continue - deps.append(req_line) + if not deps: + print("❌ No valid dependencies found to write to requirements.txt") + sys.exit(1) deps = sorted(set(deps)) - with open('requirements.txt', 'w', encoding='utf-8') as f: - f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') - f.write('# This file contains only DIRECT dependencies, not transitive ones\n') - f.write('# Source of truth: pyproject.toml\n\n') + + try: + with open('requirements.txt', 'w', encoding='utf-8') as f: + f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') + f.write('# This file contains only DIRECT dependencies, not transitive ones\n') + f.write('# Source of truth: pyproject.toml\n') + f.write('# \n') + f.write('# To install:\n') + f.write('# pip install -r requirements.txt\n') + f.write('# \n') + f.write('# Optional extras (install as needed):\n') + f.write('# pip install graphrag-sdk[openai] # OpenAI models\n') + f.write('# pip install graphrag-sdk[vertexai] # Google Vertex AI\n') + f.write('# pip install graphrag-sdk[google-generativeai] # Google AI Studio\n') + f.write('# pip install graphrag-sdk[all] # All optional providers\n') + f.write('\n') + for dep in deps: + f.write(dep + '\n') + + print(f'✅ Successfully generated requirements.txt with {len(deps)} direct dependencies') + + # Print summary + print('\nGenerated dependencies:') for dep in deps: - f.write(dep + '\n') - - print(f'✅ Generated requirements.txt with {len(deps)} direct dependencies') + print(f' - {dep}') + + except Exception as e: + print(f"❌ Error writing requirements.txt: {e}") + sys.exit(1) PY - + + - name: Configure Git + run: | git config --local user.email "action@github.com" git config --local user.name "GitHub Action" + + - name: Check for changes + id: changes + run: | + if git diff --quiet HEAD -- requirements.txt; then + echo "changed=false" >> $GITHUB_OUTPUT + echo "No changes to requirements.txt" + else + echo "changed=true" >> $GITHUB_OUTPUT + echo "Changes detected in requirements.txt" + echo "=== Changes ===" + git diff HEAD -- requirements.txt + echo "===============" + fi + + - name: Commit changes (TESTING - always commit) + run: | git add requirements.txt if git diff --staged --quiet; then - echo "No changes to commit" + echo "No changes to stage, but forcing commit for testing" + git commit --allow-empty -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml + + No actual changes but testing workflow - commit: ${{ github.sha }} + Event: ${{ github.event_name }} + " else - git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" - if [ "${GITHUB_EVENT_NAME}" = "push" ]; then - git push - else - echo "Skipping push on event: ${GITHUB_EVENT_NAME}" - fi + git commit -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml + + Generated from commit: ${{ github.sha }} + Event: ${{ github.event_name }} + " fi + git push + + - name: Add PR comment (TESTING - always comment) + if: github.event_name == 'pull_request' + uses: actions/github-script@v7 + with: + script: | + const commentBody = `🤖 **[TESTING] requirements.txt sync completed** + + The workflow ran and processed \`pyproject.toml\`: + - ✅ Workflow executed successfully + - ✅ Generated/updated requirements.txt + - ✅ Changes committed to PR branch + + **This is a test run** - checking if the sync workflow works properly. + + Event: ${{ github.event_name }} + Commit: \`${{ github.sha }}\``; + + await github.rest.issues.createComment({ + owner: context.repo.owner, + repo: context.repo.repo, + issue_number: context.issue.number, + body: commentBody + }); + + - name: Summary + run: | + echo "✅ [TESTING MODE] Workflow completed" + echo "📁 requirements.txt has been generated/updated and committed" + echo "🔍 Check your PR to see if the requirements.txt file appears" + echo "🗑️ After testing, we can remove the forced commit logic" \ No newline at end of file From b7cc3b538203e1278fcd023cc00860a3f598b3df Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Thu, 14 Aug 2025 12:45:01 +0300 Subject: [PATCH 081/136] Update sync-dependencies.yml --- .github/workflows/sync-dependencies.yml | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 23f3a17e..18998862 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -19,6 +19,7 @@ jobs: with: token: ${{ secrets.GITHUB_TOKEN }} fetch-depth: 0 + ref: ${{ github.head_ref || github.ref }} - name: Setup Python uses: actions/setup-python@v5 @@ -218,7 +219,13 @@ jobs: Event: ${{ github.event_name }} " fi - git push + + # Push to the correct branch + if [ "${{ github.event_name }}" = "pull_request" ]; then + git push origin HEAD:${{ github.head_ref }} + else + git push + fi - name: Add PR comment (TESTING - always comment) if: github.event_name == 'pull_request' From 77cb056e1bff0754f86d4fc708c96a711d1fceb3 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Thu, 14 Aug 2025 09:45:18 +0000 Subject: [PATCH 082/136] =?UTF-8?q?=F0=9F=A4=96=20[TESTING]=20Auto-sync=20?= =?UTF-8?q?requirements.txt=20from=20pyproject.toml?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Generated from commit: d57b4aed4c393d4e47c991674c2d09c0858ee8d7 Event: pull_request --- requirements.txt | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 00000000..eb2d7b63 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,24 @@ +# Auto-generated from pyproject.toml [tool.poetry.dependencies] +# This file contains only DIRECT dependencies, not transitive ones +# Source of truth: pyproject.toml +# +# To install: +# pip install -r requirements.txt +# +# Optional extras (install as needed): +# pip install graphrag-sdk[openai] # OpenAI models +# pip install graphrag-sdk[vertexai] # Google Vertex AI +# pip install graphrag-sdk[google-generativeai] # Google AI Studio +# pip install graphrag-sdk[all] # All optional providers + +backoff>=2.2.1,<3.0.0 +beautifulsoup4>=4.12.3,<5.0.0 +falkordb>=1.0.9,<2.0.0 +fix-busted-json>=0.0.18,<0.0.19 +litellm>=1.73.1,<2.0.0 +pypdf>=4.2.0,<5.0.0 +python-dotenv>=1.0.1,<2.0.0 +ratelimit>=2.2.1,<3.0.0 +requests>=2.32.3,<3.0.0 +rich>=13.9.4,<14.0.0 +typing-extensions>=4.12.1,<5.0.0 From 238720ec12e32dc513e6b9d6bc99b220eb20d25d Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Thu, 14 Aug 2025 13:26:54 +0300 Subject: [PATCH 083/136] using poetry export --- .github/workflows/sync-dependencies.yml | 185 ++---------------------- 1 file changed, 13 insertions(+), 172 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 18998862..5d1fea52 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -27,181 +27,23 @@ jobs: python-version: '3.11' cache: 'pip' - - name: Install tomli for Python <3.11 - run: | - python3 -c "import sys; sys.exit(0 if sys.version_info >= (3, 11) else 1)" || python3 -m pip install -q tomli + - name: Install Poetry + uses: snok/install-poetry@v1 + with: + version: latest + virtualenvs-create: true + virtualenvs-in-project: false - - name: Sync requirements + - name: Generate requirements.txt run: | - set -euo pipefail - python3 - <<'PY' - import sys - import re - try: - import tomllib - except ModuleNotFoundError: - import tomli as tomllib - - def caret_to_range(v: str) -> str: - """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics.""" - base = v[1:] - parts = base.split('.') - - def num(seg): - m = re.match(r'(\d+)', str(seg)) - return int(m.group(1)) if m else 0 - - major = num(parts[0]) if len(parts) > 0 else 0 - minor = num(parts[1]) if len(parts) > 1 else 0 - patch = num(parts[2]) if len(parts) > 2 else 0 - - # Proper caret semantics: ^0.x.y -> <0.(x+1).0, ^x.y.z -> <(x+1).0.0 - if major > 0: - upper = f'{major+1}.0.0' - elif minor > 0: - upper = f'0.{minor+1}.0' - else: - upper = f'0.0.{patch+1}' - - return f'>={base},<{upper}' - - try: - with open('pyproject.toml', 'rb') as f: - data = tomllib.load(f) - except Exception as e: - print(f"❌ Error reading pyproject.toml: {e}") - sys.exit(1) - - deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) - if not deps_table: - print("❌ No dependencies found in pyproject.toml") - sys.exit(1) - - deps = [] - - for name, spec in deps_table.items(): - if name.lower() == 'python': - continue - - extras = [] - req_line = None - version = None - markers = None - - try: - if isinstance(spec, str): - version = spec.strip() - elif isinstance(spec, dict): - extras = sorted(spec.get('extras') or []) - markers = (spec.get('markers') or '').strip() or None - - if 'version' in spec: - version = str(spec['version']).strip() - elif 'git' in spec: - ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' - frag = f'@{ref}' if ref else '' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" - if markers: - req_line += f"; {markers}" - elif 'url' in spec: - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ {spec['url']}" - if markers: - req_line += f"; {markers}" - elif 'path' in spec: - # Skip local path dependencies as they can't be in requirements.txt - print(f"⚠️ Skipping local path dependency: {name}") - continue - else: - print(f"⚠️ Skipping unsupported dependency spec for {name}: {spec}") - continue - else: - print(f"⚠️ Skipping unsupported dependency type for {name}: {type(spec)}") - continue - - if req_line is None and version is not None: - def normalize(ver: str) -> str: - ver = ver.strip() - if not ver: - return '' - if ver.startswith('^'): - return caret_to_range(ver) - # Check for existing constraints/operators - has_constraint = any(op in ver for op in ['<', '>', '!=', '==', '===', '~=', '~', '*']) - has_space = ' ' in ver # Combined constraints like ">=1.0 <2.0" - return ver if (has_constraint or has_space) else f'>={ver}' - - normalized_version = normalize(version) - if normalized_version: - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part}{normalized_version}" - if markers: - req_line += f"; {markers}" - - if req_line: - deps.append(req_line) - print(f"✓ Added dependency: {req_line}") - - except Exception as e: - print(f"⚠️ Error processing dependency {name}: {e}") - continue - - if not deps: - print("❌ No valid dependencies found to write to requirements.txt") - sys.exit(1) - - deps = sorted(set(deps)) - - try: - with open('requirements.txt', 'w', encoding='utf-8') as f: - f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') - f.write('# This file contains only DIRECT dependencies, not transitive ones\n') - f.write('# Source of truth: pyproject.toml\n') - f.write('# \n') - f.write('# To install:\n') - f.write('# pip install -r requirements.txt\n') - f.write('# \n') - f.write('# Optional extras (install as needed):\n') - f.write('# pip install graphrag-sdk[openai] # OpenAI models\n') - f.write('# pip install graphrag-sdk[vertexai] # Google Vertex AI\n') - f.write('# pip install graphrag-sdk[google-generativeai] # Google AI Studio\n') - f.write('# pip install graphrag-sdk[all] # All optional providers\n') - f.write('\n') - for dep in deps: - f.write(dep + '\n') - - print(f'✅ Successfully generated requirements.txt with {len(deps)} direct dependencies') - - # Print summary - print('\nGenerated dependencies:') - for dep in deps: - print(f' - {dep}') - - except Exception as e: - print(f"❌ Error writing requirements.txt: {e}") - sys.exit(1) - PY + poetry export -f requirements.txt --output requirements.txt --without-hashes --only main + echo "✅ Generated requirements.txt using Poetry export" - name: Configure Git run: | git config --local user.email "action@github.com" git config --local user.name "GitHub Action" - - name: Check for changes - id: changes - run: | - if git diff --quiet HEAD -- requirements.txt; then - echo "changed=false" >> $GITHUB_OUTPUT - echo "No changes to requirements.txt" - else - echo "changed=true" >> $GITHUB_OUTPUT - echo "Changes detected in requirements.txt" - echo "=== Changes ===" - git diff HEAD -- requirements.txt - echo "===============" - fi - - name: Commit changes (TESTING - always commit) run: | git add requirements.txt @@ -235,8 +77,8 @@ jobs: const commentBody = `🤖 **[TESTING] requirements.txt sync completed** The workflow ran and processed \`pyproject.toml\`: - - ✅ Workflow executed successfully - - ✅ Generated/updated requirements.txt + - ✅ Used Poetry export command + - ✅ Generated clean requirements.txt - ✅ Changes committed to PR branch **This is a test run** - checking if the sync workflow works properly. @@ -254,6 +96,5 @@ jobs: - name: Summary run: | echo "✅ [TESTING MODE] Workflow completed" - echo "📁 requirements.txt has been generated/updated and committed" - echo "🔍 Check your PR to see if the requirements.txt file appears" - echo "🗑️ After testing, we can remove the forced commit logic" \ No newline at end of file + echo "📁 requirements.txt has been generated using Poetry export" + echo "🔍 Check your PR to see the clean requirements.txt file" \ No newline at end of file From ae81cb2d31934a733ced5300223c598377285687 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Thu, 14 Aug 2025 16:30:08 +0300 Subject: [PATCH 084/136] Update sync-dependencies.yml --- .github/workflows/sync-dependencies.yml | 82 +++++-------------------- 1 file changed, 14 insertions(+), 68 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 5d1fea52..23dce788 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -5,7 +5,7 @@ on: paths: ['pyproject.toml'] branches: [main] pull_request: - paths: ['pyproject.toml'] + # For testing - remove "paths" to run on any PR change branches: [main] jobs: @@ -17,84 +17,30 @@ jobs: steps: - uses: actions/checkout@v4 with: - token: ${{ secrets.GITHUB_TOKEN }} fetch-depth: 0 ref: ${{ github.head_ref || github.ref }} - - name: Setup Python - uses: actions/setup-python@v5 - with: - python-version: '3.11' - cache: 'pip' - - - name: Install Poetry - uses: snok/install-poetry@v1 + - name: Export requirements.txt + uses: divideprojects/poetry-export-requirements-action@v1 with: - version: latest - virtualenvs-create: true - virtualenvs-in-project: false - - - name: Generate requirements.txt - run: | - poetry export -f requirements.txt --output requirements.txt --without-hashes --only main - echo "✅ Generated requirements.txt using Poetry export" + without-hashes: true + outfile-name: requirements.txt - name: Configure Git run: | git config --local user.email "action@github.com" git config --local user.name "GitHub Action" - - name: Commit changes (TESTING - always commit) + - name: Commit changes run: | git add requirements.txt if git diff --staged --quiet; then - echo "No changes to stage, but forcing commit for testing" - git commit --allow-empty -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml - - No actual changes but testing workflow - commit: ${{ github.sha }} - Event: ${{ github.event_name }} - " + echo "No changes to commit" else - git commit -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml - - Generated from commit: ${{ github.sha }} - Event: ${{ github.event_name }} - " - fi - - # Push to the correct branch - if [ "${{ github.event_name }}" = "pull_request" ]; then - git push origin HEAD:${{ github.head_ref }} - else - git push - fi - - - name: Add PR comment (TESTING - always comment) - if: github.event_name == 'pull_request' - uses: actions/github-script@v7 - with: - script: | - const commentBody = `🤖 **[TESTING] requirements.txt sync completed** - - The workflow ran and processed \`pyproject.toml\`: - - ✅ Used Poetry export command - - ✅ Generated clean requirements.txt - - ✅ Changes committed to PR branch - - **This is a test run** - checking if the sync workflow works properly. - - Event: ${{ github.event_name }} - Commit: \`${{ github.sha }}\``; - - await github.rest.issues.createComment({ - owner: context.repo.owner, - repo: context.repo.repo, - issue_number: context.issue.number, - body: commentBody - }); - - - name: Summary - run: | - echo "✅ [TESTING MODE] Workflow completed" - echo "📁 requirements.txt has been generated using Poetry export" - echo "🔍 Check your PR to see the clean requirements.txt file" \ No newline at end of file + git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" + if [ "${{ github.event_name }}" = "pull_request" ]; then + git push origin HEAD:${{ github.head_ref }} + else + git push + fi + fi \ No newline at end of file From 21f5f0ab0aacbfc943904656c05dd0a75b6750b3 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Thu, 14 Aug 2025 16:43:45 +0300 Subject: [PATCH 085/136] using pip-tools --- .github/workflows/sync-dependencies.yml | 42 ++++++++++++++++--------- 1 file changed, 28 insertions(+), 14 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 23dce788..30085d37 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -5,7 +5,6 @@ on: paths: ['pyproject.toml'] branches: [main] pull_request: - # For testing - remove "paths" to run on any PR change branches: [main] jobs: @@ -13,34 +12,49 @@ jobs: runs-on: ubuntu-latest permissions: contents: write - pull-requests: write steps: - uses: actions/checkout@v4 with: fetch-depth: 0 ref: ${{ github.head_ref || github.ref }} - - name: Export requirements.txt - uses: divideprojects/poetry-export-requirements-action@v1 + - name: Setup Python + uses: actions/setup-python@v5 with: - without-hashes: true - outfile-name: requirements.txt + python-version: '3.11' + + - name: Install pip-tools + run: pip install pip-tools + + - name: Generate requirements.txt from pyproject.toml (main deps only) + run: pip-compile pyproject.toml --output-file requirements.txt - name: Configure Git run: | git config --local user.email "action@github.com" git config --local user.name "GitHub Action" - - name: Commit changes + - name: Commit changes (TESTING - always commit) run: | git add requirements.txt if git diff --staged --quiet; then - echo "No changes to commit" + echo "No changes to stage, but forcing commit for testing" + git commit --allow-empty -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml + + No actual changes but testing pip-tools workflow - commit: ${{ github.sha }} + Event: ${{ github.event_name }} + " + else + git commit -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml + + Generated using pip-tools from commit: ${{ github.sha }} + Event: ${{ github.event_name }} + " + fi + + # Push to the correct branch + if [ "${{ github.event_name }}" = "pull_request" ]; then + git push origin HEAD:${{ github.head_ref }} else - git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" - if [ "${{ github.event_name }}" = "pull_request" ]; then - git push origin HEAD:${{ github.head_ref }} - else - git push - fi + git push fi \ No newline at end of file From 604e03702e4a5df29786a007c1fc7dca00044bba Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Thu, 14 Aug 2025 13:49:34 +0000 Subject: [PATCH 086/136] =?UTF-8?q?=F0=9F=A4=96=20[TESTING]=20Auto-sync=20?= =?UTF-8?q?requirements.txt=20from=20pyproject.toml?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Generated using pip-tools from commit: f90b74a88828a56310271ae0d8241eb8fbc87c2f Event: pull_request --- requirements.txt | 199 +++++++++++++++++++++++++++++++++++++++++------ 1 file changed, 175 insertions(+), 24 deletions(-) diff --git a/requirements.txt b/requirements.txt index eb2d7b63..1a8a7c5c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,24 +1,175 @@ -# Auto-generated from pyproject.toml [tool.poetry.dependencies] -# This file contains only DIRECT dependencies, not transitive ones -# Source of truth: pyproject.toml -# -# To install: -# pip install -r requirements.txt -# -# Optional extras (install as needed): -# pip install graphrag-sdk[openai] # OpenAI models -# pip install graphrag-sdk[vertexai] # Google Vertex AI -# pip install graphrag-sdk[google-generativeai] # Google AI Studio -# pip install graphrag-sdk[all] # All optional providers - -backoff>=2.2.1,<3.0.0 -beautifulsoup4>=4.12.3,<5.0.0 -falkordb>=1.0.9,<2.0.0 -fix-busted-json>=0.0.18,<0.0.19 -litellm>=1.73.1,<2.0.0 -pypdf>=4.2.0,<5.0.0 -python-dotenv>=1.0.1,<2.0.0 -ratelimit>=2.2.1,<3.0.0 -requests>=2.32.3,<3.0.0 -rich>=13.9.4,<14.0.0 -typing-extensions>=4.12.1,<5.0.0 +# +# This file is autogenerated by pip-compile with Python 3.11 +# by the following command: +# +# pip-compile --output-file=requirements.txt pyproject.toml +# +aiohappyeyeballs==2.6.1 + # via aiohttp +aiohttp==3.12.15 + # via litellm +aiosignal==1.4.0 + # via aiohttp +annotated-types==0.7.0 + # via pydantic +anyio==4.10.0 + # via + # httpx + # openai +attrs==25.3.0 + # via + # aiohttp + # jsonschema + # referencing +backoff==2.2.1 + # via graphrag_sdk (pyproject.toml) +beautifulsoup4==4.13.4 + # via graphrag_sdk (pyproject.toml) +certifi==2025.8.3 + # via + # httpcore + # httpx + # requests +charset-normalizer==3.4.3 + # via requests +click==8.2.1 + # via litellm +distro==1.9.0 + # via openai +falkordb==1.2.0 + # via graphrag_sdk (pyproject.toml) +filelock==3.18.0 + # via huggingface-hub +fix-busted-json==0.0.18 + # via graphrag_sdk (pyproject.toml) +frozenlist==1.7.0 + # via + # aiohttp + # aiosignal +fsspec==2025.7.0 + # via huggingface-hub +h11==0.16.0 + # via httpcore +hf-xet==1.1.7 + # via huggingface-hub +httpcore==1.0.9 + # via httpx +httpx==0.28.1 + # via + # litellm + # openai +huggingface-hub==0.34.4 + # via tokenizers +idna==3.10 + # via + # anyio + # httpx + # requests + # yarl +importlib-metadata==8.7.0 + # via litellm +jinja2==3.1.6 + # via litellm +jiter==0.10.0 + # via openai +jsonschema==4.25.0 + # via litellm +jsonschema-specifications==2025.4.1 + # via jsonschema +litellm==1.75.5.post1 + # via graphrag_sdk (pyproject.toml) +markdown-it-py==4.0.0 + # via rich +markupsafe==3.0.2 + # via jinja2 +mdurl==0.1.2 + # via markdown-it-py +multidict==6.6.4 + # via + # aiohttp + # yarl +openai==1.99.9 + # via litellm +packaging==25.0 + # via huggingface-hub +propcache==0.3.2 + # via + # aiohttp + # yarl +pydantic==2.11.7 + # via + # litellm + # openai +pydantic-core==2.33.2 + # via pydantic +pygments==2.19.2 + # via rich +pyjwt==2.10.1 + # via redis +pypdf==4.3.1 + # via graphrag_sdk (pyproject.toml) +python-dateutil==2.9.0.post0 + # via falkordb +python-dotenv==1.1.1 + # via + # graphrag_sdk (pyproject.toml) + # litellm +pyyaml==6.0.2 + # via huggingface-hub +ratelimit==2.2.1 + # via graphrag_sdk (pyproject.toml) +redis==5.3.1 + # via falkordb +referencing==0.36.2 + # via + # jsonschema + # jsonschema-specifications +regex==2025.7.34 + # via tiktoken +requests==2.32.4 + # via + # graphrag_sdk (pyproject.toml) + # huggingface-hub + # tiktoken +rich==13.9.4 + # via graphrag_sdk (pyproject.toml) +rpds-py==0.27.0 + # via + # jsonschema + # referencing +six==1.17.0 + # via python-dateutil +sniffio==1.3.1 + # via + # anyio + # openai +soupsieve==2.7 + # via beautifulsoup4 +tiktoken==0.11.0 + # via litellm +tokenizers==0.21.4 + # via litellm +tqdm==4.67.1 + # via + # huggingface-hub + # openai +typing-extensions==4.14.1 + # via + # aiosignal + # anyio + # beautifulsoup4 + # graphrag_sdk (pyproject.toml) + # huggingface-hub + # openai + # pydantic + # pydantic-core + # referencing + # typing-inspection +typing-inspection==0.4.1 + # via pydantic +urllib3==2.5.0 + # via requests +yarl==1.20.1 + # via aiohttp +zipp==3.23.0 + # via importlib-metadata From 4afee1ab9546914c15e28a08f42203048b9833ae Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Sun, 17 Aug 2025 13:15:52 +0300 Subject: [PATCH 087/136] back to tomllib --- .github/workflows/sync-dependencies.yml | 219 ++++++++++++++++++++++-- 1 file changed, 202 insertions(+), 17 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 30085d37..4d2b0ed6 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -5,6 +5,7 @@ on: paths: ['pyproject.toml'] branches: [main] pull_request: + paths: ['pyproject.toml'] branches: [main] jobs: @@ -12,6 +13,7 @@ jobs: runs-on: ubuntu-latest permissions: contents: write + pull-requests: write steps: - uses: actions/checkout@v4 with: @@ -22,39 +24,222 @@ jobs: uses: actions/setup-python@v5 with: python-version: '3.11' + cache: 'pip' + + - name: Install tomli for Python <3.11 + run: | + python3 -c "import sys; sys.exit(0 if sys.version_info >= (3, 11) else 1)" || python3 -m pip install -q tomli + + - name: Sync requirements + run: | + set -euo pipefail + python3 - <<'PY' + import sys + import re + try: + import tomllib + except ImportError: + import tomli as tomllib + + def caret_to_range(v: str) -> str: + """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics.""" + base = v[1:] + parts = base.split('.') + + def num(seg): + m = re.match(r'(\d+)', str(seg)) + return int(m.group(1)) if m else 0 + + major = num(parts[0]) if len(parts) > 0 else 0 + minor = num(parts[1]) if len(parts) > 1 else 0 + patch = num(parts[2]) if len(parts) > 2 else 0 + + # Proper caret semantics: ^0.x.y -> <0.(x+1).0, ^x.y.z -> <(x+1).0.0 + if major > 0: + upper = f'{major+1}.0.0' + elif minor > 0: + upper = f'0.{minor+1}.0' + else: + upper = f'0.0.{patch+1}' + + return f'>={base},<{upper}' + + try: + with open('pyproject.toml', 'rb') as f: + data = tomllib.load(f) + except Exception as e: + print(f"Error reading pyproject.toml: {e}") + sys.exit(1) + + deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) + if not deps_table: + print("No dependencies found in pyproject.toml") + sys.exit(1) - - name: Install pip-tools - run: pip install pip-tools + deps = [] - - name: Generate requirements.txt from pyproject.toml (main deps only) - run: pip-compile pyproject.toml --output-file requirements.txt + for name, spec in deps_table.items(): + if name.lower() == 'python': + continue + + extras = [] + req_line = None + version = None + markers = None + + try: + if isinstance(spec, str): + version = spec.strip() + elif isinstance(spec, dict): + extras = sorted(spec.get('extras') or []) + markers = (spec.get('markers') or '').strip() or None + + if 'version' in spec: + version = str(spec['version']).strip() + elif 'git' in spec: + ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' + frag = f'@{ref}' if ref else '' + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" + if markers: + req_line += f"; {markers}" + elif 'url' in spec: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part} @ {spec['url']}" + if markers: + req_line += f"; {markers}" + elif 'path' in spec: + # Skip local path dependencies as they can't be in requirements.txt + print(f"Skipping local path dependency: {name}") + continue + else: + print(f"Skipping unsupported dependency spec for {name}: {spec}") + continue + else: + print(f"Skipping unsupported dependency type for {name}: {type(spec)}") + continue + + if req_line is None and version is not None: + def normalize(ver: str) -> str: + ver = ver.strip() + if not ver: + return '' + if ver.startswith('^'): + return caret_to_range(ver) + # Check for existing constraints/operators + has_constraint = any(op in ver for op in ['<', '>', '!=', '==', '===', '~=', '~', '*']) + has_space = ' ' in ver # Combined constraints like ">=1.0 <2.0" + return ver if (has_constraint or has_space) else f'>={ver}' + + normalized_version = normalize(version) + if normalized_version: + extras_part = f"[{','.join(extras)}]" if extras else '' + req_line = f"{name}{extras_part}{normalized_version}" + if markers: + req_line += f"; {markers}" + + if req_line: + deps.append(req_line) + print(f"✓ Added dependency: {req_line}") + + except Exception as e: + print(f"Error processing dependency {name}: {e}") + continue + + if not deps: + print("No valid dependencies found to write to requirements.txt") + sys.exit(1) + + deps = sorted(set(deps)) + + try: + with open('requirements.txt', 'w', encoding='utf-8') as f: + f.write('# Auto-generated from pyproject.toml [tool.poetry.dependencies]\n') + f.write('# This file contains only DIRECT dependencies, not transitive ones\n') + f.write('# Source of truth: pyproject.toml\n') + f.write('#\n') + f.write('# To install:\n') + f.write('# pip install -r requirements.txt\n') + f.write('\n') + for dep in deps: + f.write(dep + '\n') + + print(f'Successfully generated requirements.txt with {len(deps)} direct dependencies') + + # Print summary + print('\nGenerated dependencies:') + for dep in deps: + print(f' - {dep}') + + except Exception as e: + print(f"Error writing requirements.txt: {e}") + sys.exit(1) + PY - name: Configure Git run: | git config --local user.email "action@github.com" git config --local user.name "GitHub Action" - - name: Commit changes (TESTING - always commit) + - name: Check for changes + id: changes run: | - git add requirements.txt - if git diff --staged --quiet; then - echo "No changes to stage, but forcing commit for testing" - git commit --allow-empty -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml - - No actual changes but testing pip-tools workflow - commit: ${{ github.sha }} - Event: ${{ github.event_name }} - " + if git diff --quiet HEAD -- requirements.txt; then + echo "changed=false" >> $GITHUB_OUTPUT + echo "No changes to requirements.txt" else - git commit -m "🤖 [TESTING] Auto-sync requirements.txt from pyproject.toml + echo "changed=true" >> $GITHUB_OUTPUT + echo "Changes detected in requirements.txt" + echo "=== Changes ===" + git diff HEAD -- requirements.txt + echo "===============" + fi + + - name: Commit changes + if: steps.changes.outputs.changed == 'true' + run: | + git add requirements.txt + git commit -m "Auto-sync requirements.txt from pyproject.toml - Generated using pip-tools from commit: ${{ github.sha }} + Generated from commit: ${{ github.sha }} Event: ${{ github.event_name }} " - fi # Push to the correct branch if [ "${{ github.event_name }}" = "pull_request" ]; then git push origin HEAD:${{ github.head_ref }} else git push - fi \ No newline at end of file + fi + + - name: Add PR comment + if: steps.changes.outputs.changed == 'true' && github.event_name == 'pull_request' + uses: actions/github-script@v7 + with: + script: | + const commentBody = `**requirements.txt updated automatically** + + The \`requirements.txt\` file has been updated based on changes to \`pyproject.toml\`. + + **Changes made:** + - Synchronized direct dependencies from Poetry configuration + - Maintained proper version constraints and markers + - Updated package count and dependency specifications + + This is an automated update to keep requirements.txt in sync with pyproject.toml.`; + + await github.rest.issues.createComment({ + owner: context.repo.owner, + repo: context.repo.repo, + issue_number: context.issue.number, + body: commentBody + }); + + - name: Summary + run: | + if [[ "${{ steps.changes.outputs.changed }}" == "true" ]]; then + echo "requirements.txt has been updated and committed" + else + echo "requirements.txt is already up to date" + fi + echo "Workflow completed successfully" \ No newline at end of file From 2551eaba5552008fad451ffd01fe3027a3a2d3e2 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Sun, 17 Aug 2025 10:16:06 +0000 Subject: [PATCH 088/136] Auto-sync requirements.txt from pyproject.toml Generated from commit: 37dcc3aa0364e217531dc1a418e1cfa1cb4fa6ac Event: pull_request --- requirements.txt | 191 +++++------------------------------------------ 1 file changed, 17 insertions(+), 174 deletions(-) diff --git a/requirements.txt b/requirements.txt index 1a8a7c5c..5c87e584 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,175 +1,18 @@ +# Auto-generated from pyproject.toml [tool.poetry.dependencies] +# This file contains only DIRECT dependencies, not transitive ones +# Source of truth: pyproject.toml # -# This file is autogenerated by pip-compile with Python 3.11 -# by the following command: -# -# pip-compile --output-file=requirements.txt pyproject.toml -# -aiohappyeyeballs==2.6.1 - # via aiohttp -aiohttp==3.12.15 - # via litellm -aiosignal==1.4.0 - # via aiohttp -annotated-types==0.7.0 - # via pydantic -anyio==4.10.0 - # via - # httpx - # openai -attrs==25.3.0 - # via - # aiohttp - # jsonschema - # referencing -backoff==2.2.1 - # via graphrag_sdk (pyproject.toml) -beautifulsoup4==4.13.4 - # via graphrag_sdk (pyproject.toml) -certifi==2025.8.3 - # via - # httpcore - # httpx - # requests -charset-normalizer==3.4.3 - # via requests -click==8.2.1 - # via litellm -distro==1.9.0 - # via openai -falkordb==1.2.0 - # via graphrag_sdk (pyproject.toml) -filelock==3.18.0 - # via huggingface-hub -fix-busted-json==0.0.18 - # via graphrag_sdk (pyproject.toml) -frozenlist==1.7.0 - # via - # aiohttp - # aiosignal -fsspec==2025.7.0 - # via huggingface-hub -h11==0.16.0 - # via httpcore -hf-xet==1.1.7 - # via huggingface-hub -httpcore==1.0.9 - # via httpx -httpx==0.28.1 - # via - # litellm - # openai -huggingface-hub==0.34.4 - # via tokenizers -idna==3.10 - # via - # anyio - # httpx - # requests - # yarl -importlib-metadata==8.7.0 - # via litellm -jinja2==3.1.6 - # via litellm -jiter==0.10.0 - # via openai -jsonschema==4.25.0 - # via litellm -jsonschema-specifications==2025.4.1 - # via jsonschema -litellm==1.75.5.post1 - # via graphrag_sdk (pyproject.toml) -markdown-it-py==4.0.0 - # via rich -markupsafe==3.0.2 - # via jinja2 -mdurl==0.1.2 - # via markdown-it-py -multidict==6.6.4 - # via - # aiohttp - # yarl -openai==1.99.9 - # via litellm -packaging==25.0 - # via huggingface-hub -propcache==0.3.2 - # via - # aiohttp - # yarl -pydantic==2.11.7 - # via - # litellm - # openai -pydantic-core==2.33.2 - # via pydantic -pygments==2.19.2 - # via rich -pyjwt==2.10.1 - # via redis -pypdf==4.3.1 - # via graphrag_sdk (pyproject.toml) -python-dateutil==2.9.0.post0 - # via falkordb -python-dotenv==1.1.1 - # via - # graphrag_sdk (pyproject.toml) - # litellm -pyyaml==6.0.2 - # via huggingface-hub -ratelimit==2.2.1 - # via graphrag_sdk (pyproject.toml) -redis==5.3.1 - # via falkordb -referencing==0.36.2 - # via - # jsonschema - # jsonschema-specifications -regex==2025.7.34 - # via tiktoken -requests==2.32.4 - # via - # graphrag_sdk (pyproject.toml) - # huggingface-hub - # tiktoken -rich==13.9.4 - # via graphrag_sdk (pyproject.toml) -rpds-py==0.27.0 - # via - # jsonschema - # referencing -six==1.17.0 - # via python-dateutil -sniffio==1.3.1 - # via - # anyio - # openai -soupsieve==2.7 - # via beautifulsoup4 -tiktoken==0.11.0 - # via litellm -tokenizers==0.21.4 - # via litellm -tqdm==4.67.1 - # via - # huggingface-hub - # openai -typing-extensions==4.14.1 - # via - # aiosignal - # anyio - # beautifulsoup4 - # graphrag_sdk (pyproject.toml) - # huggingface-hub - # openai - # pydantic - # pydantic-core - # referencing - # typing-inspection -typing-inspection==0.4.1 - # via pydantic -urllib3==2.5.0 - # via requests -yarl==1.20.1 - # via aiohttp -zipp==3.23.0 - # via importlib-metadata +# To install: +# pip install -r requirements.txt + +backoff>=2.2.1,<3.0.0 +beautifulsoup4>=4.12.3,<5.0.0 +falkordb>=1.0.9,<2.0.0 +fix-busted-json>=0.0.18,<0.0.19 +litellm>=1.73.1,<2.0.0 +pypdf>=4.2.0,<5.0.0 +python-dotenv>=1.0.1,<2.0.0 +ratelimit>=2.2.1,<3.0.0 +requests>=2.32.3,<3.0.0 +rich>=13.9.4,<14.0.0 +typing-extensions>=4.12.1,<5.0.0 From 2c7312edcbb0e7a53c5833e214dce041b41cb756 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Sun, 17 Aug 2025 14:53:43 +0300 Subject: [PATCH 089/136] update sync dep CI --- .github/workflows/sync-dependencies.yml | 56 +++++++------------------ 1 file changed, 15 insertions(+), 41 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 4d2b0ed6..11ed3a54 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -13,7 +13,6 @@ jobs: runs-on: ubuntu-latest permissions: contents: write - pull-requests: write steps: - uses: actions/checkout@v4 with: @@ -140,7 +139,7 @@ jobs: if req_line: deps.append(req_line) - print(f"✓ Added dependency: {req_line}") + print(f"Added dependency: {req_line}") except Exception as e: print(f"Error processing dependency {name}: {e}") @@ -190,56 +189,31 @@ jobs: else echo "changed=true" >> $GITHUB_OUTPUT echo "Changes detected in requirements.txt" - echo "=== Changes ===" - git diff HEAD -- requirements.txt - echo "===============" fi - name: Commit changes - if: steps.changes.outputs.changed == 'true' + env: + PR_REF: ${{ github.head_ref }} run: | git add requirements.txt - git commit -m "Auto-sync requirements.txt from pyproject.toml - - Generated from commit: ${{ github.sha }} - Event: ${{ github.event_name }} - " - - # Push to the correct branch - if [ "${{ github.event_name }}" = "pull_request" ]; then - git push origin HEAD:${{ github.head_ref }} + if git diff --staged --quiet; then + echo "No changes to commit" else - git push + git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" + if [ "${{ github.event_name }}" = "pull_request" ]; then + case "${PR_REF}" in + *[!A-Za-z0-9._/-]*|'') echo "Unsafe PR ref; skipping push"; exit 0;; + esac + git push origin "HEAD:${PR_REF}" + else + git push + fi fi - - name: Add PR comment - if: steps.changes.outputs.changed == 'true' && github.event_name == 'pull_request' - uses: actions/github-script@v7 - with: - script: | - const commentBody = `**requirements.txt updated automatically** - - The \`requirements.txt\` file has been updated based on changes to \`pyproject.toml\`. - - **Changes made:** - - Synchronized direct dependencies from Poetry configuration - - Maintained proper version constraints and markers - - Updated package count and dependency specifications - - This is an automated update to keep requirements.txt in sync with pyproject.toml.`; - - await github.rest.issues.createComment({ - owner: context.repo.owner, - repo: context.repo.repo, - issue_number: context.issue.number, - body: commentBody - }); - - name: Summary run: | if [[ "${{ steps.changes.outputs.changed }}" == "true" ]]; then echo "requirements.txt has been updated and committed" else echo "requirements.txt is already up to date" - fi - echo "Workflow completed successfully" \ No newline at end of file + fi \ No newline at end of file From 5695010ee3a775a0a83f91a5d6218919d01117ec Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Sun, 17 Aug 2025 14:55:09 +0300 Subject: [PATCH 090/136] fix sync-dep CI --- .github/workflows/sync-dependencies.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 11ed3a54..820fd338 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -23,7 +23,6 @@ jobs: uses: actions/setup-python@v5 with: python-version: '3.11' - cache: 'pip' - name: Install tomli for Python <3.11 run: | From ba3e93088356502f6584e536a8f637ea23ac14ff Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Sun, 17 Aug 2025 15:21:58 +0300 Subject: [PATCH 091/136] fix comments --- .github/workflows/sync-dependencies.yml | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 820fd338..7cd5bce8 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -40,26 +40,31 @@ jobs: import tomli as tomllib def caret_to_range(v: str) -> str: - """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics.""" + """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics, incl. ^0 and ^0.0.""" base = v[1:] parts = base.split('.') - def num(seg): m = re.match(r'(\d+)', str(seg)) return int(m.group(1)) if m else 0 - major = num(parts[0]) if len(parts) > 0 else 0 minor = num(parts[1]) if len(parts) > 1 else 0 patch = num(parts[2]) if len(parts) > 2 else 0 - - # Proper caret semantics: ^0.x.y -> <0.(x+1).0, ^x.y.z -> <(x+1).0.0 + # Proper caret semantics: + # - ^X[.Y[.Z]] with X>0 -> <(X+1).0.0 + # - ^0.Y[.Z] with Y>0 -> <0.(Y+1).0 + # - ^0.0.Z -> <0.0.(Z+1) + # - ^0 -> <1.0.0 + # - ^0.0 -> <0.1.0 if major > 0: upper = f'{major+1}.0.0' + elif len(parts) == 1: # ^0 + upper = '1.0.0' + elif len(parts) == 2 and minor == 0: # ^0.0 + upper = '0.1.0' elif minor > 0: upper = f'0.{minor+1}.0' else: upper = f'0.0.{patch+1}' - return f'>={base},<{upper}' try: @@ -198,7 +203,7 @@ jobs: if git diff --staged --quiet; then echo "No changes to commit" else - git commit -m "🤖 Auto-sync requirements.txt from pyproject.toml" + git commit -m "Auto-sync requirements.txt from pyproject.toml" if [ "${{ github.event_name }}" = "pull_request" ]; then case "${PR_REF}" in *[!A-Za-z0-9._/-]*|'') echo "Unsafe PR ref; skipping push"; exit 0;; From 4160e7e3e7759214fc487602746a948aec03a598 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Sun, 17 Aug 2025 15:46:09 +0300 Subject: [PATCH 092/136] Update sync-dependencies.yml --- .github/workflows/sync-dependencies.yml | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 7cd5bce8..b721abe3 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -127,6 +127,8 @@ jobs: ver = ver.strip() if not ver: return '' + if ver == '*' or ver.lower() == 'any': + return '' if ver.startswith('^'): return caret_to_range(ver) # Check for existing constraints/operators @@ -135,11 +137,14 @@ jobs: return ver if (has_constraint or has_space) else f'>={ver}' normalized_version = normalize(version) + extras_part = f"[{','.join(extras)}]" if extras else '' if normalized_version: - extras_part = f"[{','.join(extras)}]" if extras else '' req_line = f"{name}{extras_part}{normalized_version}" - if markers: - req_line += f"; {markers}" + else: + # Unpinned dependency (e.g., "*"): emit just the name (+ extras) + req_line = f"{name}{extras_part}" + if markers: + req_line += f"; {markers}" if req_line: deps.append(req_line) @@ -181,8 +186,9 @@ jobs: - name: Configure Git run: | - git config --local user.email "action@github.com" - git config --local user.name "GitHub Action" + set -e + git config --local user.email "github-actions[bot]@users.noreply.github.com" + git config --local user.name "github-actions[bot]" - name: Check for changes id: changes @@ -199,6 +205,7 @@ jobs: env: PR_REF: ${{ github.head_ref }} run: | + set -e git add requirements.txt if git diff --staged --quiet; then echo "No changes to commit" @@ -206,7 +213,7 @@ jobs: git commit -m "Auto-sync requirements.txt from pyproject.toml" if [ "${{ github.event_name }}" = "pull_request" ]; then case "${PR_REF}" in - *[!A-Za-z0-9._/-]*|'') echo "Unsafe PR ref; skipping push"; exit 0;; + *[!A-Za-z0-9_-]*|'') echo "Unsafe PR ref; skipping push"; exit 0;; esac git push origin "HEAD:${PR_REF}" else From fd49d0278ae629baa52e2907fba3fc4842eb3cc1 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Mon, 25 Aug 2025 16:23:29 +0300 Subject: [PATCH 093/136] update README Add quick start example for existing knowledge graphs --- README.md | 72 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 72 insertions(+) diff --git a/README.md b/README.md index 9c9b2ff5..8620b139 100644 --- a/README.md +++ b/README.md @@ -42,6 +42,78 @@ pip install graphrag_sdk [![Get started](https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/get-started-badge.svg)](https://lightning.ai/muhammadqadora/studios/build-fast-accurate-genai-apps-advanced-rag-with-falkordb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/FalkorDB/GraphRAG-SDK/blob/main/examples/movies/demo-movies.ipynb) +### Environment Configuration + +Before using the SDK, configure your environment variables: + +```bash +# FalkorDB Connection (defaults are for on-premises) +export FALKORDB_HOST="localhost" +export FALKORDB_PORT=6379 +export FALKORDB_USERNAME="your-username" # optional for on-premises +export FALKORDB_PASSWORD="your-password" # optional for on-premises + +# LLM Provider (choose one) +export OPENAI_API_KEY="your-key" # or GOOGLE_API_KEY, GROQ_API_KEY, etc. +``` + +## Quick Start with Existing Knowledge Graph + +If you already have a knowledge graph in FalkorDB, you can quickly set up GraphRAG by extracting the ontology from your existing graph: + +```python +import os +from falkordb import FalkorDB +from graphrag_sdk import KnowledgeGraph +from graphrag_sdk.ontology import Ontology +from graphrag_sdk.models.litellm import LiteModel +from graphrag_sdk.model_config import KnowledgeGraphModelConfig + +graph_name = "my_existing_graph" + +# Connect to FalkorDB using environment variables +db = FalkorDB( + host=os.getenv("FALKORDB_HOST", "localhost"), + port=os.getenv("FALKORDB_PORT", 6379), + username=os.getenv("FALKORDB_USERNAME"), # optional for on-premises + password=os.getenv("FALKORDB_PASSWORD") # optional for on-premises +) + +# Select graph +graph = db.select_graph(graph_name) + +# Extract ontology from existing knowledge graph +ontology = Ontology.from_kg_graph(graph) + +# Configure model and create GraphRAG instance +model = LiteModel() # Default is OpenAI GPT-4.1, can specify different model +model_config = KnowledgeGraphModelConfig.with_model(model) + +# Create KnowledgeGraph instance +kg = KnowledgeGraph( + name=graph_name, + model_config=model_config, + ontology=ontology, + host=os.getenv("FALKORDB_HOST", "localhost"), + port=os.getenv("FALKORDB_PORT", 6379), + username=os.getenv("FALKORDB_USERNAME"), + password=os.getenv("FALKORDB_PASSWORD") +) + +# Start chat session +chat = kg.chat_session() + +# Ask questions +response = chat.send_message("What products are available?") +print(response["response"]) + +# Ask follow-up questions +response = chat.send_message("Tell me which one of them is the most expensive") +print(response["response"]) +``` + +## Creating Knowledge Graphs from Scratch + ### Step 1: Creating Ontologies Automate ontology creation from unstructured data or define it manually - See [example](https://github.com/falkordb/GraphRAG-SDK/blob/main/examples/trip/demo_orchestrator_trip.ipynb) From e53f6c560da168d3ce2d54a2a05ad6673356ca70 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Tue, 26 Aug 2025 11:20:57 +0300 Subject: [PATCH 094/136] Add refresh_ontology() method to kg --- graphrag_sdk/kg.py | 22 +++++++++++++++++++--- 1 file changed, 19 insertions(+), 3 deletions(-) diff --git a/graphrag_sdk/kg.py b/graphrag_sdk/kg.py index 752bbeb6..a0a4e74b 100644 --- a/graphrag_sdk/kg.py +++ b/graphrag_sdk/kg.py @@ -61,18 +61,18 @@ def __init__( # Connect to database self.db = FalkorDB(host=host, port=port, username=username, password=password) self.graph = self.db.select_graph(name) - ontology_graph = self.db.select_graph("{" + name + "}" + "_schema") + self.ontology_graph = self.db.select_graph("{" + name + "}" + "_schema") # Load / Save ontology to database if ontology is None: # Load ontology from DB - ontology = Ontology.from_schema_graph(ontology_graph) + ontology = Ontology.from_schema_graph(self.ontology_graph) if len(ontology.entities) == 0: raise Exception("The ontology is empty. Load a valid ontology or create one using the ontology module.") else: # Save ontology to DB - ontology.save_to_graph(ontology_graph) + ontology.save_to_graph(self.ontology_graph) self._ontology = ontology self._name = name @@ -210,6 +210,22 @@ def chat_session(self) -> ChatSession: chat_session = ChatSession(self._model_config, self.ontology, self.graph, self.cypher_system_instruction, self.qa_system_instruction, self.cypher_gen_prompt, self.qa_prompt, self.cypher_gen_prompt_history) return chat_session + + def refresh_ontology(self) -> None: + """ + Refresh the ontology by reloading it from the database. + This is useful when the schema has been updated. + + Raises: + Exception: If the refreshed ontology is empty and no fallback is available. + """ + # Reload ontology from database + refreshed_ontology = Ontology.from_schema_graph(self.ontology_graph) + + # Always update the ontology, even if it's empty + # This allows users to intentionally clear the ontology if needed + self._ontology = refreshed_ontology + def add_node(self, entity: str, attributes: dict) -> None: """ Add a node to the knowledge graph, checking if it matches the ontology From 81bd7a76ba9e1fc5c3bb4c539c9055e63589dac2 Mon Sep 17 00:00:00 2001 From: Naseem Ali <34807727+Naseem77@users.noreply.github.com> Date: Tue, 26 Aug 2025 11:24:30 +0300 Subject: [PATCH 095/136] fix ai comments --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8620b139..39078856 100644 --- a/README.md +++ b/README.md @@ -74,7 +74,7 @@ graph_name = "my_existing_graph" # Connect to FalkorDB using environment variables db = FalkorDB( host=os.getenv("FALKORDB_HOST", "localhost"), - port=os.getenv("FALKORDB_PORT", 6379), + port=int(os.getenv("FALKORDB_PORT", 6379)), username=os.getenv("FALKORDB_USERNAME"), # optional for on-premises password=os.getenv("FALKORDB_PASSWORD") # optional for on-premises ) @@ -95,7 +95,7 @@ kg = KnowledgeGraph( model_config=model_config, ontology=ontology, host=os.getenv("FALKORDB_HOST", "localhost"), - port=os.getenv("FALKORDB_PORT", 6379), + port=int(os.getenv("FALKORDB_PORT", 6379)), username=os.getenv("FALKORDB_USERNAME"), password=os.getenv("FALKORDB_PASSWORD") ) From f951c97908e6d65a14b1e927f6ca829fec6419cf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=8E=96=E4=BA=96=E4=BC=8D?= Date: Wed, 17 Sep 2025 15:09:03 +0800 Subject: [PATCH 096/136] avoid deepcopy exception with OllamaGenerativeModel --- graphrag_sdk/model_config.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index c806c0e0..e92c08b5 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -49,7 +49,14 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ # Ensure the extract_data model is configured for structured data extraction - extract_data_model = copy.deepcopy(model) + try: + extract_data_model = copy.deepcopy(model) + except TypeError as te: + if getattr(model, "ollama_client", None) is not None: + from .models.ollama import OllamaGenerativeModel + extract_data_model = OllamaGenerativeModel.from_json(model.to_json()) + else: + raise te extract_data_model.generation_config.response_format = {"type": "json_object"} From 043708efc78efdde8ed9702a7dbb448940f9e43d Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Wed, 17 Sep 2025 07:46:50 +0000 Subject: [PATCH 097/136] Auto-sync requirements.txt from pyproject.toml --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 5c87e584..90c5a221 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,7 +10,7 @@ beautifulsoup4>=4.12.3,<5.0.0 falkordb>=1.0.9,<2.0.0 fix-busted-json>=0.0.18,<0.0.19 litellm>=1.73.1,<2.0.0 -pypdf>=4.2.0,<5.0.0 +pypdf>=5.9.0,<6.0.0 python-dotenv>=1.0.1,<2.0.0 ratelimit>=2.2.1,<3.0.0 requests>=2.32.3,<3.0.0 From 7b033041a24b538e8c30027fc561102aa0e869a1 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 17 Sep 2025 13:47:55 +0300 Subject: [PATCH 098/136] update-ollama-usage --- .env.template | 2 ++ README.md | 21 +++++++++++++++++++++ graphrag_sdk/model_config.py | 11 ++++++++++- graphrag_sdk/models/litellm.py | 5 +++-- graphrag_sdk/models/ollama.py | 23 +++++++++++++++++++---- 5 files changed, 55 insertions(+), 7 deletions(-) diff --git a/.env.template b/.env.template index a884f3fc..5d8de984 100644 --- a/.env.template +++ b/.env.template @@ -9,6 +9,8 @@ # For LiteLLM usage GEMINI_API_KEY = "GEMINI_API_KEY" + + # For Ollama OLLAMA_API_BASE = "OLLAMA_API_BASE" # "http://localhost:11434" AZURE_API_KEY = "AZURE_API_KEY" # "my-azure-api-key" diff --git a/README.md b/README.md index 39078856..9a2c93d7 100644 --- a/README.md +++ b/README.md @@ -195,6 +195,27 @@ With these 3 steps now completed, you're ready to interact and query your knowle
+# Using Ollama + +Ollama models are suitable for the Q&A step only (after the knowledge graph has been created). + +## Setup + +```python +from graphrag_sdk.models.ollama import OllamaGenerativeModel + +# Local Ollama (default: http://localhost:11434) +qa_model = OllamaGenerativeModel(model_name="llama3:8b") + +# Remote Ollama +qa_model = OllamaGenerativeModel( + model_name="llama3:8b", + api_base="http://remote-host:11434" +) +``` + +
+ # AI Agents with GraphRAG ### Orchestrator diff --git a/graphrag_sdk/model_config.py b/graphrag_sdk/model_config.py index c806c0e0..859bbd5e 100644 --- a/graphrag_sdk/model_config.py +++ b/graphrag_sdk/model_config.py @@ -49,7 +49,16 @@ def with_model(model: GenerativeModel) -> "KnowledgeGraphModelConfig": """ # Ensure the extract_data model is configured for structured data extraction - extract_data_model = copy.deepcopy(model) + try: + extract_data_model = copy.deepcopy(model) + except TypeError as te: + # Handle models that cannot be deep-copied (e.g., Ollama models with threading locks) + # Check if this is an Ollama model by checking its type + from .models.ollama import OllamaGenerativeModel + if isinstance(model, OllamaGenerativeModel): + extract_data_model = OllamaGenerativeModel.from_json(model.to_json()) + else: + raise te extract_data_model.generation_config.response_format = {"type": "json_object"} diff --git a/graphrag_sdk/models/litellm.py b/graphrag_sdk/models/litellm.py index 1e64568e..78f0d0f6 100644 --- a/graphrag_sdk/models/litellm.py +++ b/graphrag_sdk/models/litellm.py @@ -41,8 +41,9 @@ def __init__( system_instruction (Optional[str]): Instruction to guide the model. additional_params (Optional[dict]): Additional provider-specific parameters. """ - - env_val = validate_environment(model_name) + api_base = additional_params.get('api_base') if additional_params else None + env_val = validate_environment(model_name, api_base=api_base) + if not env_val['keys_in_environment']: raise ValueError(f"Missing {env_val['missing_keys']} in the environment.") self._internal_model_name, provider, _, _ = litellm_utils.get_llm_provider(model_name) diff --git a/graphrag_sdk/models/ollama.py b/graphrag_sdk/models/ollama.py index ef28a22b..3b3e23e6 100644 --- a/graphrag_sdk/models/ollama.py +++ b/graphrag_sdk/models/ollama.py @@ -1,4 +1,5 @@ import logging +import os from typing import Optional from .litellm import LiteModel, LiteModelChatSession from .model import ( @@ -24,6 +25,7 @@ def __init__( model_name: str, generation_config: Optional[GenerativeModelConfig] = None, system_instruction: Optional[str] = None, + api_base: Optional[str] = None, host: Optional[str] = None, ): """ @@ -33,15 +35,28 @@ def __init__( model_name (str): The name of the Ollama model. generation_config (Optional[GenerativeModelConfig]): Configuration settings for generation. system_instruction (Optional[str]): System-level instruction for the model. - host (Optional[str]): Host for connecting to the Ollama API. + api_base (Optional[str]): Base URL for the Ollama API (e.g., "http://localhost:11434"). + If not provided, will use OLLAMA_API_BASE environment variable. + host (Optional[str]): DEPRECATED: Use api_base instead. Base URL for the Ollama API. """ # Convert to LiteLLM format lite_model_name = f"ollama/{model_name}" - # Handle host parameter for Ollama + # Handle backward compatibility for host parameter + if host is not None and api_base is not None: + logger.warning("Both 'host' and 'api_base' parameters provided. Using 'api_base' and ignoring 'host'.") + elif host is not None and api_base is None: + logger.warning("Parameter 'host' is deprecated. Please use 'api_base' instead.") + api_base = host + + # Use environment variable if no api_base is provided + if api_base is None: + api_base = os.getenv('OLLAMA_API_BASE') + + # Handle api_base parameter for Ollama additional_params = {} - if host is not None: - additional_params['api_base'] = host # LiteLLM uses api_base for custom endpoints + if api_base is not None: + additional_params['api_base'] = api_base # Call parent constructor super().__init__( From 8600b067a9a39fc3d43d8fcb4e2e1b5af06b27c0 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Wed, 17 Sep 2025 13:59:01 +0300 Subject: [PATCH 099/136] update-lock-file --- poetry.lock | 2654 ++++++++++++++++++++++++--------------------------- 1 file changed, 1227 insertions(+), 1427 deletions(-) diff --git a/poetry.lock b/poetry.lock index 4c5f1462..15a08b5f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -6,7 +6,6 @@ version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.9" -groups = ["main", "test"] files = [ {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, @@ -18,7 +17,6 @@ version = "3.12.15" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" -groups = ["main", "test"] files = [ {file = "aiohttp-3.12.15-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b6fc902bff74d9b1879ad55f5404153e2b33a82e72a95c89cec5eb6cc9e92fbc"}, {file = "aiohttp-3.12.15-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:098e92835b8119b54c693f2f88a1dec690e20798ca5f5fe5f0520245253ee0af"}, @@ -119,7 +117,7 @@ propcache = ">=0.2.0" yarl = ">=1.17.0,<2.0" [package.extras] -speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "brotlicffi ; platform_python_implementation != \"CPython\""] +speedups = ["Brotli", "aiodns (>=3.3.0)", "brotlicffi"] [[package]] name = "aiosignal" @@ -127,7 +125,6 @@ version = "1.4.0" description = "aiosignal: a list of registered asynchronous callbacks" optional = false python-versions = ">=3.9" -groups = ["main", "test"] files = [ {file = "aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e"}, {file = "aiosignal-1.4.0.tar.gz", hash = "sha256:f47eecd9468083c2029cc99945502cb7708b082c232f9aca65da147157b251c7"}, @@ -143,7 +140,6 @@ version = "0.7.16" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.9" -groups = ["dev"] files = [ {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"}, {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"}, @@ -155,7 +151,6 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" -groups = ["main", "test"] files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -167,7 +162,6 @@ version = "0.49.0" description = "The official Python library for the anthropic API" optional = false python-versions = ">=3.8" -groups = ["test"] files = [ {file = "anthropic-0.49.0-py3-none-any.whl", hash = "sha256:bbc17ad4e7094988d2fa86b87753ded8dce12498f4b85fe5810f208f454a8375"}, {file = "anthropic-0.49.0.tar.gz", hash = "sha256:c09e885b0f674b9119b4f296d8508907f6cff0009bc20d5cf6b35936c40b4398"}, @@ -188,14 +182,13 @@ vertex = ["google-auth (>=2,<3)"] [[package]] name = "anyio" -version = "4.9.0" -description = "High level compatibility layer for multiple asynchronous event loop implementations" +version = "4.10.0" +description = "High-level concurrency and networking framework on top of asyncio or Trio" optional = false python-versions = ">=3.9" -groups = ["main", "dev", "test"] files = [ - {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"}, - {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"}, + {file = "anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1"}, + {file = "anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6"}, ] [package.dependencies] @@ -205,8 +198,6 @@ sniffio = ">=1.1" typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] -doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] -test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1) ; python_version >= \"3.10\"", "uvloop (>=0.21) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\" and python_version < \"3.14\""] trio = ["trio (>=0.26.1)"] [[package]] @@ -215,8 +206,6 @@ version = "0.1.4" description = "Disable App Nap on macOS >= 10.9" optional = false python-versions = ">=3.6" -groups = ["dev"] -markers = "platform_system == \"Darwin\"" files = [ {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"}, @@ -228,7 +217,6 @@ version = "25.1.0" description = "Argon2 for Python" optional = false python-versions = ">=3.8" -groups = ["dev"] files = [ {file = "argon2_cffi-25.1.0-py3-none-any.whl", hash = "sha256:fdc8b074db390fccb6eb4a3604ae7231f219aa669a2652e0f20e16ba513d5741"}, {file = "argon2_cffi-25.1.0.tar.gz", hash = "sha256:694ae5cc8a42f4c4e2bf2ca0e64e51e23a040c6a517a85074683d3959e1346c1"}, @@ -243,7 +231,6 @@ version = "25.1.0" description = "Low-level CFFI bindings for Argon2" optional = false python-versions = ">=3.9" -groups = ["dev"] files = [ {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:3d3f05610594151994ca9ccb3c771115bdb4daef161976a266f0dd8aa9996b8f"}, {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:8b8efee945193e667a396cbc7b4fb7d357297d6234d30a489905d96caabde56b"}, @@ -282,7 +269,6 @@ version = "1.3.0" description = "Better dates & times for Python" optional = false python-versions = ">=3.8" -groups = ["dev"] files = [ {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"}, {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"}, @@ -302,7 +288,6 @@ version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false python-versions = ">=3.8" -groups = ["dev"] files = [ {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, @@ -318,7 +303,6 @@ version = "2.0.5" description = "Simple LRU cache for asyncio" optional = false python-versions = ">=3.9" -groups = ["dev"] files = [ {file = "async_lru-2.0.5-py3-none-any.whl", hash = "sha256:ab95404d8d2605310d345932697371a5f40def0487c03d6d0ad9138de52c9943"}, {file = "async_lru-2.0.5.tar.gz", hash = "sha256:481d52ccdd27275f42c43a928b4a50c3bfb2d67af4e78b170e3e0bb39c66e5bb"}, @@ -333,12 +317,10 @@ version = "5.0.1" description = "Timeout context manager for asyncio programs" optional = false python-versions = ">=3.8" -groups = ["main", "test"] files = [ {file = "async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c"}, {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"}, ] -markers = {main = "python_full_version < \"3.11.3\"", test = "python_version < \"3.11\""} [[package]] name = "attrs" @@ -346,19 +328,18 @@ version = "25.3.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.8" -groups = ["main", "dev", "test"] files = [ {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, ] [package.extras] -benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] -cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] -dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= 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platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""] +brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"] h2 = ["h2 (>=4,<5)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] zstd = ["zstandard (>=0.18.0)"] @@ -4939,7 +4748,6 @@ version = "0.2.13" description = "Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" -groups = ["dev"] files = [ {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, @@ -4951,7 +4759,6 @@ version = "24.11.1" description = "A library for working with the color formats defined by HTML and CSS." optional = false python-versions = ">=3.9" -groups = ["dev"] files = [ {file = "webcolors-24.11.1-py3-none-any.whl", hash = "sha256:515291393b4cdf0eb19c155749a096f779f7d909f7cceea072791cb9095b92e9"}, {file = "webcolors-24.11.1.tar.gz", hash = "sha256:ecb3d768f32202af770477b8b65f318fa4f566c22948673a977b00d589dd80f6"}, @@ -4963,7 +4770,6 @@ version = "0.5.1" description = "Character encoding aliases for legacy web content" optional = false python-versions = "*" -groups = ["dev"] files = [ {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"}, {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"}, @@ -4975,7 +4781,6 @@ version = "1.8.0" description = "WebSocket client for Python with low level API options" optional = false python-versions = ">=3.8" -groups = ["dev"] files = [ {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"}, {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"}, @@ -4992,7 +4797,6 @@ version = "15.0.1" description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)" optional = false python-versions = ">=3.9" -groups = ["test"] files = [ {file = "websockets-15.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d63efaa0cd96cf0c5fe4d581521d9fa87744540d4bc999ae6e08595a1014b45b"}, {file = "websockets-15.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ac60e3b188ec7574cb761b08d50fcedf9d77f1530352db4eef1707fe9dee7205"}, @@ -5071,7 +4875,6 @@ version = "0.45.1" description = "A built-package format for Python" optional = false python-versions = ">=3.8" -groups = ["test"] files = [ {file = "wheel-0.45.1-py3-none-any.whl", hash = "sha256:708e7481cc80179af0e556bbf0cc00b8444c7321e2700b8d8580231d13017248"}, {file = "wheel-0.45.1.tar.gz", hash = "sha256:661e1abd9198507b1409a20c02106d9670b2576e916d58f520316666abca6729"}, @@ -5086,7 +4889,6 @@ version = "4.0.14" description = "Jupyter interactive widgets for Jupyter Notebook" optional = false python-versions = ">=3.7" -groups = ["dev"] files = [ {file = "widgetsnbextension-4.0.14-py3-none-any.whl", hash = "sha256:4875a9eaf72fbf5079dc372a51a9f268fc38d46f767cbf85c43a36da5cb9b575"}, {file = "widgetsnbextension-4.0.14.tar.gz", hash = "sha256:a3629b04e3edb893212df862038c7232f62973373869db5084aed739b437b5af"}, @@ -5098,7 +4900,6 @@ version = "1.20.1" description = "Yet another URL library" optional = false python-versions = ">=3.9" -groups = ["main", "test"] files = [ {file = "yarl-1.20.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6032e6da6abd41e4acda34d75a816012717000fa6839f37124a47fcefc49bec4"}, {file = "yarl-1.20.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2c7b34d804b8cf9b214f05015c4fee2ebe7ed05cf581e7192c06555c71f4446a"}, @@ -5217,14 +5018,13 @@ version = "3.23.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" -groups = ["main", "test"] files = [ {file = "zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e"}, {file = "zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] @@ -5232,6 +5032,6 @@ test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_it type = ["pytest-mypy"] [metadata] -lock-version = "2.1" +lock-version = "2.0" python-versions = "^3.10.0, <3.14" -content-hash = "88d705e9f71cb9a5dde3ab2c84e4326b5b52327283590cc8d8bf06d0039c81aa" \ No newline at end of file +content-hash = "b2e17ad632017816fa8be30d8a4116ad3078868130dfc04b77862aab3cfb198e" From c72afa96efee09a43d39c78f849366ecf0072eed Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=8E=96=E4=BA=96=E4=BC=8D?= Date: Thu, 18 Sep 2025 19:18:10 +0800 Subject: [PATCH 100/136] Remove the 'AttributeType.' prefix to avoid 'Invalid attribute type' error. --- graphrag_sdk/attribute.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/attribute.py b/graphrag_sdk/attribute.py index d28ec986..9858324d 100644 --- a/graphrag_sdk/attribute.py +++ b/graphrag_sdk/attribute.py @@ -35,7 +35,7 @@ def from_string(txt: str) -> "AttributeType": ValueError: If the provided attribute type is invalid. """ # Graph representation of the attribute type - normalized_txt = txt.lower() + normalized_txt = txt.lstrip('AttributeType.').lower() # Find the matching attribute type if normalized_txt in _SYNONYMS: From 9421b844683ef5504d7cc37108fe10ca5b9f220f Mon Sep 17 00:00:00 2001 From: Filip Ratajczak <90644163+Tesla2000@users.noreply.github.com> Date: Mon, 29 Sep 2025 11:25:32 +0200 Subject: [PATCH 101/136] Fixed typo in prompts --- graphrag_sdk/fixtures/prompts.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/fixtures/prompts.py b/graphrag_sdk/fixtures/prompts.py index 1f79c5d8..78c0444c 100644 --- a/graphrag_sdk/fixtures/prompts.py +++ b/graphrag_sdk/fixtures/prompts.py @@ -171,7 +171,7 @@ CREATE_ONTOLOGY_PROMPT = """ Given the following text, create the ontology that represents the entities and relationships in the data. Extract as many entities and relations as possible to fully describe the data. -Extract as attributes as possible to fully describe the entities and relationships in the text. +Extract as many attributes as possible to fully describe the entities and relationships in the text. Attributes should be extracted as entities or relations whenever possible. For example, when describing a Movie entity, the "director" attribute can be extracted as a entity "Person" and connected to the "Movie" entity with an relation labeled "DIRECTED". For example, when describing a Movie entity, you can extract attributes like title, release year, genre, and more. Make sure to connect all related entities in the ontology. For example, if a Person PLAYED a Character in a Movie, make sure to connect the Character back to the Movie, otherwise we won't be able to say which Movie the Character is from. From f349e9b8ab97ab9c8ca5e41ce7ed9c41ecbe2b29 Mon Sep 17 00:00:00 2001 From: Filip Ratajczak <90644163+Tesla2000@users.noreply.github.com> Date: Mon, 29 Sep 2025 15:53:28 +0200 Subject: [PATCH 102/136] Fixed issue with JSONL loader In previous implementation last rows were skipped --- graphrag_sdk/document_loaders/jsonl.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/document_loaders/jsonl.py b/graphrag_sdk/document_loaders/jsonl.py index 1742b7c0..9ba615f8 100644 --- a/graphrag_sdk/document_loaders/jsonl.py +++ b/graphrag_sdk/document_loaders/jsonl.py @@ -1,3 +1,4 @@ +from math import ceil from typing import Iterator from graphrag_sdk.document import Document @@ -15,7 +16,7 @@ def load(self) -> Iterator[Document]: with open(self.path, "r") as f: rows = f.readlines() num_rows = len(rows) - num_documents = num_rows // self.rows_per_document + num_documents = ceil(num_rows / self.rows_per_document) for i in range(num_documents): content = "\n".join( rows[ From 8076946fc20a842a95259f2dee5f6dbbe9f49692 Mon Sep 17 00:00:00 2001 From: Filip Ratajczak <90644163+Tesla2000@users.noreply.github.com> Date: Mon, 29 Sep 2025 15:56:25 +0200 Subject: [PATCH 103/136] Fixed the same issue in CSVLoader --- graphrag_sdk/document_loaders/csv.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/document_loaders/csv.py b/graphrag_sdk/document_loaders/csv.py index d8e37057..36a2d6fd 100644 --- a/graphrag_sdk/document_loaders/csv.py +++ b/graphrag_sdk/document_loaders/csv.py @@ -1,4 +1,5 @@ import csv +from math import ceil from typing import Iterator from graphrag_sdk.document import Document @@ -17,7 +18,7 @@ def load(self) -> Iterator[Document]: reader = csv.reader(f) rows = [row for row in reader] num_rows = len(rows) - num_documents = num_rows // self.rows_per_document + num_documents = ceil(num_rows / self.rows_per_document) for i in range(num_documents): content = "\n".join( [ From ded68fe531665460fdf345575fb560014a688e52 Mon Sep 17 00:00:00 2001 From: Michael Yuen Date: Thu, 2 Oct 2025 15:46:10 +0800 Subject: [PATCH 104/136] Support UTF8 csv --- graphrag_sdk/document_loaders/csv.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/graphrag_sdk/document_loaders/csv.py b/graphrag_sdk/document_loaders/csv.py index 36a2d6fd..96eb7b5d 100644 --- a/graphrag_sdk/document_loaders/csv.py +++ b/graphrag_sdk/document_loaders/csv.py @@ -14,7 +14,7 @@ def __init__(self, path: str, rows_per_document: int = 500): self.rows_per_document = rows_per_document def load(self) -> Iterator[Document]: - with open(self.path, "r") as f: + with open(self.path, "r", encoding='utf-8') as f: reader = csv.reader(f) rows = [row for row in reader] num_rows = len(rows) From 97ec7a61ed2c4bc51dc1d7409cadd5001d34794c Mon Sep 17 00:00:00 2001 From: Abhinv Singh Parmar Date: Mon, 17 Nov 2025 19:36:48 +0530 Subject: [PATCH 105/136] fix: escape special characters in entity descriptions for Cypher queries Prevents syntax errors when descriptions contain quotes or backslashes. The escaping only affects query generation stored data remains unchanged --- graphrag_sdk/entity.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/graphrag_sdk/entity.py b/graphrag_sdk/entity.py index 291ed063..a82c9cec 100644 --- a/graphrag_sdk/entity.py +++ b/graphrag_sdk/entity.py @@ -144,7 +144,9 @@ def to_graph_query(self) -> str: [str(attr) for attr in self.attributes if not attr.unique] ) if self.description: - non_unique_attributes += f"{', ' if len(non_unique_attributes) > 0 else ''} {descriptionKey}: '{self.description}'" + # Escape special characters to prevent Cypher syntax errors + escaped_description = self.description.replace("\\", "\\\\").replace("'", "\\'").replace('"', '\\"') + non_unique_attributes += f"{', ' if len(non_unique_attributes) > 0 else ''} {descriptionKey}: '{escaped_description}'" return f"MERGE (n:{self.label} {{{unique_attributes}}}) SET n += {{{non_unique_attributes}}} RETURN n" def __str__(self) -> str: From d2b3ff84d75c8ff1820a92168612c9b638519be7 Mon Sep 17 00:00:00 2001 From: Dianjan Date: Sun, 14 Dec 2025 14:20:06 +0530 Subject: [PATCH 106/136] Add TTLLoader to import TTL files to improve GraphRAG-SDK --- .gitignore | 2 + examples/data/ttl/sports.ttl | 147 +++++ examples/sports/demo-sports.ipynb | 689 ++++++++++++++++++++++ graphrag_sdk/document_loaders/__init__.py | 2 + graphrag_sdk/document_loaders/ttl.py | 91 +++ graphrag_sdk/helpers.py | 33 +- graphrag_sdk/ontology.py | 42 ++ graphrag_sdk/rdf_extractor.py | 301 ++++++++++ graphrag_sdk/source.py | 13 + poetry.lock | 346 +++++++++-- pyproject.toml | 1 + 11 files changed, 1621 insertions(+), 46 deletions(-) create mode 100644 examples/data/ttl/sports.ttl create mode 100644 examples/sports/demo-sports.ipynb create mode 100644 graphrag_sdk/document_loaders/ttl.py create mode 100644 graphrag_sdk/rdf_extractor.py diff --git a/.gitignore b/.gitignore index c3418c0c..adcdef9f 100644 --- a/.gitignore +++ b/.gitignore @@ -9,3 +9,5 @@ logs falkordb-data weaviate-data .deepeval_telemtry.txt + +.claude \ No newline at end of file diff --git a/examples/data/ttl/sports.ttl b/examples/data/ttl/sports.ttl new file mode 100644 index 00000000..e5947f21 --- /dev/null +++ b/examples/data/ttl/sports.ttl @@ -0,0 +1,147 @@ +@prefix : . +@prefix owl: . +@prefix rdf: . +@prefix xml: . +@prefix xsd: . +@prefix rdfs: . + +# ======================================== +# ONTOLOGY DECLARATION +# ======================================== + + + rdf:type owl:Ontology . + + +# ======================================== +# OBJECT PROPERTIES +# ======================================== + +:associatedTo rdf:type owl:ObjectProperty ; + rdfs:domain :SportsPerson ; + rdfs:range :Sport ; + rdfs:comment "Links a sports person to the sport they play" . + +:partOf rdf:type owl:ObjectProperty ; + rdfs:domain :Workouts ; + rdfs:range :FocusedAreas ; + rdfs:comment "Relates workouts to their focused training areas" . + + +# ======================================== +# DATATYPE PROPERTIES (Person Attributes) +# ======================================== + +:personDatatypes rdf:type owl:DatatypeProperty ; + rdfs:comment "Parent property for all person-related datatype properties" . + +:Age rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf :personDatatypes ; + rdfs:comment "Age of the sports person" . + +:Gender rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf :personDatatypes ; + rdfs:comment "Gender of the sports person" . + +:Height rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf :personDatatypes ; + rdfs:comment "Height of the sports person" . + +:Weight rdf:type owl:DatatypeProperty ; + rdfs:subPropertyOf :personDatatypes ; + rdfs:comment "Weight of the sports person" . + + +# ======================================== +# MAIN CLASSES +# ======================================== + +:SportsPerson rdf:type owl:Class ; + rdfs:comment "An individual who participates in sports" . + +:Sport rdf:type owl:Class ; + rdfs:comment "A physical activity or game with competitive elements" . + +:Equipments rdf:type owl:Class ; + rdfs:comment "Tools and gear used in sports activities" . + +:Workouts rdf:type owl:Class ; + rdfs:comment "Training exercises and routines for athletic development" . + +:FocusedAreas rdf:type owl:Class ; + rdfs:subClassOf [ rdf:type owl:Restriction ; + owl:onProperty :personDatatypes ; + owl:someValuesFrom xsd:string + ] ; + rdfs:comment "Specific physical attributes targeted by training" . + + +# ======================================== +# SPORT TYPES (Subclasses of Sport) +# ======================================== + +:Cricket rdf:type owl:Class ; + rdfs:subClassOf :Sport ; + rdfs:comment "Bat-and-ball game played between two teams" . + +:Football rdf:type owl:Class ; + rdfs:subClassOf :Sport ; + rdfs:comment "Team sport played with a spherical ball" . + +:Tennis rdf:type owl:Class ; + rdfs:subClassOf :Sport ; + rdfs:comment "Racket sport played individually or in pairs" . + +:Badmintion rdf:type owl:Class ; + rdfs:subClassOf :Sport ; + rdfs:comment "Racket sport using a shuttlecock" . + + +# ======================================== +# WORKOUT TYPES (Subclasses of Workouts) +# ======================================== + +:UpperBody rdf:type owl:Class ; + rdfs:subClassOf :Workouts ; + rdfs:comment "Exercises targeting chest, shoulders, arms, and back" . + +:LowerBody rdf:type owl:Class ; + rdfs:subClassOf :Workouts ; + rdfs:comment "Exercises targeting legs, glutes, and hips" . + +:Core rdf:type owl:Class ; + rdfs:subClassOf :Workouts ; + rdfs:comment "Exercises targeting abdominal and back muscles" . + +:Functional rdf:type owl:Class ; + rdfs:subClassOf :Workouts ; + rdfs:comment "Multi-joint exercises that mimic everyday movements" . + + +# ======================================== +# FOCUSED AREAS (Subclasses of FocusedAreas) +# ======================================== + +:Agility rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Ability to move quickly and change direction effectively" . + +:Balance rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Ability to maintain body equilibrium" . + +:Endurance rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Ability to sustain prolonged physical effort" . + +:Flexibility rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Range of motion in joints and muscles" . + +:MusclePower rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Combination of strength and speed in muscle contraction" . + +:Speed rdf:type owl:Class ; + rdfs:subClassOf :FocusedAreas ; + rdfs:comment "Rate of movement or action" . \ No newline at end of file diff --git a/examples/sports/demo-sports.ipynb b/examples/sports/demo-sports.ipynb new file mode 100644 index 00000000..9894600f --- /dev/null +++ b/examples/sports/demo-sports.ipynb @@ -0,0 +1,689 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "34e270a4", + "metadata": {}, + "source": [ + "# Sports Ontology Extraction from TTL File\n", + "\n", + "This notebook demonstrates how to:\n", + "1. Extract an ontology from a TTL (Turtle) RDF schema file\n", + "2. Inspect the entities, relations, and attributes\n", + "3. Export the ontology to JSON format\n", + "\n", + "The sports.ttl file contains an OWL ontology defining sports-related concepts including SportsPerson, Sport, Workouts, and their relationships." + ] + }, + { + "cell_type": "markdown", + "id": "d6218be8", + "metadata": {}, + "source": [ + "## Step 1: Import Required Modules" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "d4264f31", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TTL file path: /Users/dipanjanchowdhury/Labs/OpenScience/GraphRAG-SDK/examples/data/ttl/sports.ttl\n", + "File exists: True\n" + ] + } + ], + "source": [ + "import os\n", + "from pathlib import Path\n", + "from graphrag_sdk import Ontology\n", + "import json\n", + "\n", + "# Get the path to the sports.ttl file\n", + "ttl_file_path = os.path.join(Path(os.getcwd()).parent.parent, \"examples\", \"data/ttl\", \"sports.ttl\")\n", + "print(f\"TTL file path: {ttl_file_path}\")\n", + "print(f\"File exists: {os.path.exists(ttl_file_path)}\")" + ] + }, + { + "cell_type": "markdown", + "id": "e32d0b3c", + "metadata": {}, + "source": [ + "## Step 2: Extract Ontology from TTL File\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a6fd10f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Extracting ontology from sports.ttl...\n", + "✓ Successfully extracted ontology!\n", + " - Entities: 19\n", + " - Relations: 2\n" + ] + } + ], + "source": [ + "# Extract ontology from TTL file\n", + "print(\"Extracting ontology from sports.ttl...\")\n", + "ontology = Ontology.from_ttl(ttl_file_path)\n", + "\n", + "print(f\" Successfully extracted ontology!\")\n", + "print(f\" - Entities: {len(ontology.entities)}\")\n", + "print(f\" - Relations: {len(ontology.relations)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "078f3221", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entities:\n", + "\f- (:Equipments {})\n", + "- (:SportsPerson {})\n", + "- (:MusclePower {})\n", + "- (:Football {})\n", + "- (:Agility {})\n", + "- (:Flexibility {})\n", + "- (:Endurance {})\n", + "- (:Core {})\n", + "- (:Functional {})\n", + "- (:FocusedAreas {})\n", + "- (:Workouts {})\n", + "- (:Cricket {})\n", + "- (:Badmintion {})\n", + "- (:Balance {})\n", + "- (:UpperBody {})\n", + "- (:LowerBody {})\n", + "- (:Speed {})\n", + "- (:Sport {})\n", + "- (:Tennis {})\n", + "\n", + "Edges:\n", + "\f- (:Workouts)-[:PARTOF {}]->(:FocusedAreas)\n", + "- (:SportsPerson)-[:ASSOCIATEDTO {}]->(:Sport)\n" + ] + } + ], + "source": [ + "print(ontology)" + ] + }, + { + "cell_type": "markdown", + "id": "bd7d3e3e", + "metadata": {}, + "source": [ + "## Step 3: Inspect Extracted Entities\n", + "\n", + "Display all entities (classes) extracted from the TTL file with their attributes and descriptions." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3d308940", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================================================================\n", + "ENTITIES (Classes)\n", + "================================================================================\n", + "\n", + " Equipments\n", + " Description: Tools and gear used in sports activities\n", + " No attributes defined\n", + "\n", + " SportsPerson\n", + " Description: An individual who participates in sports\n", + " No attributes defined\n", + "\n", + " MusclePower\n", + " Description: Combination of strength and speed in muscle contraction\n", + " No attributes defined\n", + "\n", + " Football\n", + " Description: Team sport played with a spherical ball\n", + " No attributes defined\n", + "\n", + " Agility\n", + " Description: Ability to move quickly and change direction effectively\n", + " No attributes defined\n", + "\n", + " Flexibility\n", + " Description: Range of motion in joints and muscles\n", + " No attributes defined\n", + "\n", + " Endurance\n", + " Description: Ability to sustain prolonged physical effort\n", + " No attributes defined\n", + "\n", + " Core\n", + " Description: Exercises targeting abdominal and back muscles\n", + " No attributes defined\n", + "\n", + " Functional\n", + " Description: Multi-joint exercises that mimic everyday movements\n", + " No attributes defined\n", + "\n", + " FocusedAreas\n", + " Description: Specific physical attributes targeted by training\n", + " No attributes defined\n", + "\n", + " Workouts\n", + " Description: Training exercises and routines for athletic development\n", + " No attributes defined\n", + "\n", + " Cricket\n", + " Description: Bat-and-ball game played between two teams\n", + " No attributes defined\n", + "\n", + " Badmintion\n", + " Description: Racket sport using a shuttlecock\n", + " No attributes defined\n", + "\n", + " Balance\n", + " Description: Ability to maintain body equilibrium\n", + " No attributes defined\n", + "\n", + " UpperBody\n", + " Description: Exercises targeting chest, shoulders, arms, and back\n", + " No attributes defined\n", + "\n", + " LowerBody\n", + " Description: Exercises targeting legs, glutes, and hips\n", + " No attributes defined\n", + "\n", + " Speed\n", + " Description: Rate of movement or action\n", + " No attributes defined\n", + "\n", + " Sport\n", + " Description: A physical activity or game with competitive elements\n", + " No attributes defined\n", + "\n", + " Tennis\n", + " Description: Racket sport played individually or in pairs\n", + " No attributes defined\n" + ] + } + ], + "source": [ + "print(\"=\" * 80)\n", + "print(\"ENTITIES (Classes)\")\n", + "print(\"=\" * 80)\n", + "\n", + "for entity in ontology.entities:\n", + " print(f\"\\n {entity.label}\")\n", + " if entity.description:\n", + " print(f\" Description: {entity.description}\")\n", + " if entity.attributes:\n", + " print(f\" Attributes ({len(entity.attributes)}):\")\n", + " for attr in entity.attributes:\n", + " print(f\" - {attr.name}: {attr.type.value}\")\n", + " else:\n", + " print(\" No attributes defined\")" + ] + }, + { + "cell_type": "markdown", + "id": "861f893e", + "metadata": {}, + "source": [ + "## Step 4: Inspect Extracted Relations\n", + "\n", + "Display all relations (object properties) extracted from the TTL file." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ead7c3a1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "================================================================================\n", + "RELATIONS (Object Properties)\n", + "================================================================================\n", + "\n", + "PARTOF\n", + " (:Workouts) --[PARTOF]--> (:FocusedAreas)\n", + "\n", + "ASSOCIATEDTO\n", + " (:SportsPerson) --[ASSOCIATEDTO]--> (:Sport)\n" + ] + } + ], + "source": [ + "print(\"\\n\" + \"=\" * 80)\n", + "print(\"RELATIONS (Object Properties)\")\n", + "print(\"=\" * 80)\n", + "\n", + "for relation in ontology.relations:\n", + " print(f\"\\n{relation.label}\")\n", + " print(f\" {relation.source} --[{relation.label}]--> {relation.target}\")\n", + " if hasattr(relation, 'attributes') and relation.attributes:\n", + " print(f\" Relation attributes: {[a.name for a in relation.attributes]}\")" + ] + }, + { + "cell_type": "markdown", + "id": "994db559", + "metadata": {}, + "source": [ + "## Step 5: Export Ontology to JSON\n", + "\n", + "Export the extracted ontology to JSON format for storage or further processing." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "64d8ee34", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "================================================================================\n", + "ONTOLOGY JSON EXPORT\n", + "================================================================================\n", + "{\n", + " \"entities\": [\n", + " {\n", + " \"label\": \"Endurance\",\n", + " \"attributes\": [],\n", + " \"description\": \"Ability to sustain prolonged physical effort\"\n", + " },\n", + " {\n", + " \"label\": \"Core\",\n", + " \"attributes\": [],\n", + " \"description\": \"Exercises targeting abdominal and back muscles\"\n", + " },\n", + " {\n", + " \"label\": \"Balance\",\n", + " \"attributes\": [],\n", + " \"description\": \"Ability to maintain body equilibrium\"\n", + " },\n", + " {\n", + " \"label\": \"FocusedAreas\",\n", + " \"attributes\": [],\n", + " \"description\": \"Specific physical attributes targeted by training\"\n", + " },\n", + " {\n", + " \"label\": \"Tennis\",\n", + " \"attributes\": [],\n", + " \"description\": \"Racket sport played individually or in pairs\"\n", + " },\n", + " {\n", + " \"label\": \"Sport\",\n", + " \"attributes\": [],\n", + " \"description\": \"A physical activity or game with competitive elements\"\n", + " },\n", + " {\n", + " \"label\": \"Flexibility\",\n", + " \"attributes\": [],\n", + " \"description\": \"Range of motion in joints and muscles\"\n", + " },\n", + " {\n", + " \"label\": \"Equipments\",\n", + " \"attributes\": [],\n", + " \"description\": \"Tools and gear used in sports activities\"\n", + " },\n", + " {\n", + " \"label\": \"Badmintion\",\n", + " \"attributes\": [],\n", + " \"description\": \"Racket sport using a shuttlecock\"\n", + " },\n", + " {\n", + " \"label\": \"Speed\",\n", + " \"attributes\": [],\n", + " \"description\": \"Rate of movement or action\"\n", + " },\n", + " {\n", + " \"label\": \"SportsPerson\",\n", + " \"attributes\": [],\n", + " \"description\": \"An individual who participates in sports\"\n", + " },\n", + " {\n", + " \"label\": \"UpperBody\",\n", + " \"attributes\": [],\n", + " \"description\": \"Exercises targeting chest, shoulders, arms, and back\"\n", + " },\n", + " {\n", + " \"label\": \"Cricket\",\n", + " \"attributes\": [],\n", + " \"description\": \"Bat-and-ball game played between two teams\"\n", + " },\n", + " {\n", + " \"label\": \"Football\",\n", + " \"attributes\": [],\n", + " \"description\": \"Team sport played with a spherical ball\"\n", + " },\n", + " {\n", + " \"label\": \"MusclePower\",\n", + " \"attributes\": [],\n", + " \"description\": \"Combination of strength and speed in muscle contraction\"\n", + " },\n", + " {\n", + " \"label\": \"LowerBody\",\n", + " \"attributes\": [],\n", + " \"description\": \"Exercises targeting legs, glutes, and hips\"\n", + " },\n", + " {\n", + " \"label\": \"Workouts\",\n", + " \"attributes\": [],\n", + " \"description\": \"Training exercises and routines for athletic development\"\n", + " },\n", + " {\n", + " \"label\": \"Agility\",\n", + " \"attributes\": [],\n", + " \"description\": \"Ability to move quickly and change direction effectively\"\n", + " },\n", + " {\n", + " \"label\": \"Functional\",\n", + " \"attributes\": [],\n", + " \"description\": \"Multi-joint exercises that mimic everyday movements\"\n", + " }\n", + " ],\n", + " \"relations\": [\n", + " {\n", + " \"label\": \"ASSOCIATEDTO\",\n", + " \"source\": {\n", + " \"label\": \"SportsPerson\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"Sport\"\n", + " },\n", + " \"attributes\": []\n", + " },\n", + " {\n", + " \"label\": \"PARTOF\",\n", + " \"source\": {\n", + " \"label\": \"Workouts\"\n", + " },\n", + " \"target\": {\n", + " \"label\": \"FocusedAreas\"\n", + " },\n", + " \"attributes\": []\n", + " }\n", + " ]\n", + "}\n", + "\n", + "✓ Ontology saved to sports_ontology.json\n" + ] + } + ], + "source": [ + "# Export to JSON\n", + "ontology_json = ontology.to_json()\n", + "print(\"\\n\" + \"=\" * 80)\n", + "print(\"ONTOLOGY JSON EXPORT\")\n", + "print(\"=\" * 80)\n", + "print(json.dumps(ontology_json, indent=2))\n", + "\n", + "# Optionally save to file (not executed by default)\n", + "# output_file = \"sports_ontology.json\"\n", + "# with open(output_file, 'w') as f:\n", + "# json.dump(ontology_json, f, indent=2)\n", + "# print(f\"\\n Ontology saved to {output_file}\")" + ] + }, + { + "cell_type": "markdown", + "id": "f6e6f511", + "metadata": {}, + "source": [ + "## Step 6: Summary Statistics\n", + "\n", + "Get a quick overview of the extracted ontology." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "fa7c5ba4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "================================================================================\n", + "ONTOLOGY SUMMARY\n", + "================================================================================\n", + "\n", + " Statistics:\n", + " Total Entities: 19\n", + " Total Relations: 2\n", + " Entities with Attributes: 0\n", + " Total Attributes: 0\n", + "\n", + " Entity List:\n", + " - Equipments (0 attributes)\n", + " - SportsPerson (0 attributes)\n", + " - MusclePower (0 attributes)\n", + " - Football (0 attributes)\n", + " - Agility (0 attributes)\n", + " - Flexibility (0 attributes)\n", + " - Endurance (0 attributes)\n", + " - Core (0 attributes)\n", + " - Functional (0 attributes)\n", + " - FocusedAreas (0 attributes)\n", + " - Workouts (0 attributes)\n", + " - Cricket (0 attributes)\n", + " - Badmintion (0 attributes)\n", + " - Balance (0 attributes)\n", + " - UpperBody (0 attributes)\n", + " - LowerBody (0 attributes)\n", + " - Speed (0 attributes)\n", + " - Sport (0 attributes)\n", + " - Tennis (0 attributes)\n", + "\n", + " Relation List:\n", + " - (:Workouts) → PARTOF → (:FocusedAreas)\n", + " - (:SportsPerson) → ASSOCIATEDTO → (:Sport)\n", + "\n", + " Ontology extraction complete!\n" + ] + } + ], + "source": [ + "print(\"\\n\" + \"=\" * 80)\n", + "print(\"ONTOLOGY SUMMARY\")\n", + "print(\"=\" * 80)\n", + "\n", + "def summarize_ontology_stats(ontology):\n", + "\n", + " total_entities = len(ontology.entities)\n", + " total_relations = len(ontology.relations)\n", + " entities_with_attrs = sum(1 for e in ontology.entities if e.attributes)\n", + " total_attributes = sum(len(e.attributes) for e in ontology.entities)\n", + "\n", + " print(f\"\\n Statistics:\")\n", + " print(f\" Total Entities: {total_entities}\")\n", + " print(f\" Total Relations: {total_relations}\")\n", + " print(f\" Entities with Attributes: {entities_with_attrs}\")\n", + " print(f\" Total Attributes: {total_attributes}\")\n", + "\n", + " print(f\"\\n Entity List:\")\n", + " for entity in ontology.entities:\n", + " attr_count = len(entity.attributes) if entity.attributes else 0\n", + " print(f\" - {entity.label} ({attr_count} attributes)\")\n", + "\n", + " print(f\"\\n Relation List:\")\n", + " for relation in ontology.relations:\n", + " print(f\" - {relation.source} → {relation.label} → {relation.target}\")\n", + "\n", + " print(\"\\n Ontology extraction complete!\")\n", + "\n", + "summarize_ontology_stats(ontology)" + ] + }, + { + "cell_type": "markdown", + "id": "b8b36772", + "metadata": {}, + "source": [ + "## Step 7: Configure FalkorDB Connection\n", + "\n", + "Set your FalkorDB credentials. You can use a local instance or get credentials from [FalkorDB Cloud](https://app.falkordb.cloud)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aed7c0a5", + "metadata": {}, + "outputs": [], + "source": [ + "# Set your OpenAI credential in .env file\n", + "# OPENAI_API_KEY=your_api_key\n", + "\n", + "# Get your Credentials from Falkor website, see https://app.falkordb.cloud\n", + "falkor_host = \"\"\n", + "falkor_port = None\n", + "falkor_username = \"\"\n", + "falkor_password = \"\"" + ] + }, + { + "cell_type": "markdown", + "id": "beddd528", + "metadata": {}, + "source": [ + "## Step 8: Create Knowledge Graph and Upload Ontology\n", + "\n", + "Create a Knowledge Graph instance and upload the extracted ontology to FalkorDB." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "11d13b78", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Knowledge Graph 'sports_kg' created successfully!\n", + " - Ontology uploaded with 19 entities and 2 relations\n" + ] + } + ], + "source": [ + "from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig\n", + "from graphrag_sdk.models.litellm import LiteModel\n", + "\n", + "\n", + "# Initialize the model\n", + "model = LiteModel(model_name=\"gemini/gemini-2.5-flash\")\n", + "\n", + "# Create Knowledge Graph with the extracted ontology\n", + "kg = KnowledgeGraph(\n", + " name=\"sports_kg\",\n", + " model_config=KnowledgeGraphModelConfig.with_model(model),\n", + " ontology=ontology,\n", + " host=falkor_host,\n", + " port=falkor_port,\n", + " username=falkor_username,\n", + " password=falkor_password\n", + ")\n", + "\n", + "print(f\" Knowledge Graph 'sports_kg' created successfully!\")\n", + "print(f\" - Ontology uploaded with {len(ontology.entities)} entities and {len(ontology.relations)} relations\")" + ] + }, + { + "cell_type": "markdown", + "id": "1a321ade", + "metadata": {}, + "source": [ + "## Step 9: Graph RAG - Query with Chat\n", + "\n", + "Utilize the `chat_session` method to start conversations and query your Knowledge Graph using natural language." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa23fafc", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a chat session\n", + "chat = kg.chat_session()\n", + "\n", + "# Example queries about the sports ontology\n", + "answer = chat.send_message(\"What entities are defined in the sports ontology?\")\n", + "print(f\"Q: {answer['question']}\\nA: {answer['response']}\\n\")\n", + "\n", + "answer = chat.send_message(\"What are the relationships between SportsPerson and Sport?\")\n", + "print(f\"Q: {answer['question']}\\nA: {answer['response']}\\n\")\n", + "\n", + "answer = chat.send_message(\"List all attributes of the Team entity.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b6adc8d", + "metadata": {}, + "outputs": [], + "source": [ + "# Uncomment to delete the Knowledge Graph\n", + "# kg.delete()\n", + "# print(\" Knowledge Graph 'sports_kg' deleted successfully\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "GraphRAG-SDK", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/graphrag_sdk/document_loaders/__init__.py b/graphrag_sdk/document_loaders/__init__.py index 0ef8e97d..aea77f0f 100644 --- a/graphrag_sdk/document_loaders/__init__.py +++ b/graphrag_sdk/document_loaders/__init__.py @@ -5,6 +5,7 @@ from .url import URLLoader from .jsonl import JSONLLoader from .string import StringLoader +from .ttl import TTLLoader __all__ = [ "PDFLoader", @@ -14,4 +15,5 @@ "URLLoader", "JSONLLoader", "StringLoader", + "TTLLoader", ] diff --git a/graphrag_sdk/document_loaders/ttl.py b/graphrag_sdk/document_loaders/ttl.py new file mode 100644 index 00000000..4a069018 --- /dev/null +++ b/graphrag_sdk/document_loaders/ttl.py @@ -0,0 +1,91 @@ +from typing import Iterator +from graphrag_sdk.document import Document +from graphrag_sdk.helpers import extract_name_from_uri + + +class TTLLoader: + """ + TTL (Terse RDF Triple/Turtle Language) loader + + Parses RDF triples from TTL files and groups them by subject. + The entire file is processed as a single document. + """ + + def __init__(self, path: str): + """ + Initialize loader + + Args: + path (str): Path to the TTL file + """ + try: + import rdflib + except ImportError: + raise ImportError( + "rdflib package not found, please install it with " "`pip install rdflib`" + ) + + self.path = path + + def load(self) -> Iterator[Document]: + """ + Load TTL file + + Returns: + Iterator[Document]: document iterator + """ + # Parse the TTL file using shared method + graph = self.get_rdf_graph() + + # Group triples by subject + subjects_dict = {} + for subject, predicate, obj in graph: + # Strip namespaces - get local name only + subj_str = extract_name_from_uri(str(subject)) + pred_str = extract_name_from_uri(str(predicate)) + obj_str = extract_name_from_uri(str(obj)) + + if subj_str not in subjects_dict: + subjects_dict[subj_str] = [] + + # Store as readable triple text + subjects_dict[subj_str].append(f"{subj_str} {pred_str} {obj_str}") + + # Convert to list of (subject, triples) tuples + subjects_list = list(subjects_dict.items()) + + if len(subjects_list) == 0: + # Empty file - yield empty document + yield Document("", self.path) + return + + # Build document content: group all triples by subject + content_lines = [] + for subject, triples in subjects_list: + content_lines.append(f"Subject: {subject}") + for triple in triples: + content_lines.append(f" {triple}") + content_lines.append("") # Empty line between subjects + + content = "\n".join(content_lines) + yield Document(content, self.path) + + def get_rdf_graph(self): + """ + Get the parsed RDF graph for ontology extraction + + Returns: + rdflib.Graph: The parsed RDF graph + + Raises: + Exception: If the file cannot be parsed + """ + from rdflib import Graph as RDFGraph + + try: + graph = RDFGraph() + graph.parse(self.path, format="turtle") + return graph + except Exception as e: + raise Exception(f"Failed to parse TTL file: {e}, please ensure the file is valid TTL format.") + diff --git a/graphrag_sdk/helpers.py b/graphrag_sdk/helpers.py index 8c7693fe..1ddb6220 100644 --- a/graphrag_sdk/helpers.py +++ b/graphrag_sdk/helpers.py @@ -1,9 +1,11 @@ import re import logging -from graphrag_sdk import Ontology -from typing import Union, Optional +from typing import Union, Optional, TYPE_CHECKING from fix_busted_json import repair_json +if TYPE_CHECKING: + from graphrag_sdk import Ontology + logger = logging.getLogger(__name__) @@ -29,6 +31,24 @@ def extract_json(text: Union[str, dict], skip_repair: Optional[bool] = False) -> logger.error(f"Failed to repair JSON: {e} - {text}") return "".join(matches) +def extract_name_from_uri(uri: str) -> str: + """ + Extract local name from URI, stripping namespace. + + Args: + uri (str): Full URI or literal value. + + Returns: + str: Local name without namespace prefix. + """ + # Handle common URI patterns + if "#" in uri: + return uri.split("#")[-1] + elif "/" in uri: + return uri.split("/")[-1] + else: + # Already a local name or literal + return uri def map_dict_to_cypher_properties(d: dict) -> str: """ @@ -48,6 +68,7 @@ def map_dict_to_cypher_properties(d: dict) -> str: cypher += f"{i}: {item}, " cypher = (cypher[:-2] if len(cypher) > 1 else cypher) + "}" return cypher + for key, value in d.items(): # Check value type if isinstance(value, str): @@ -116,7 +137,7 @@ def extract_cypher(text: str) -> str: def validate_cypher( - cypher: str, ontology: Ontology + cypher: str, ontology: "Ontology" ) -> Optional[list[str]]: """ Validates a Cypher query against the ontology. @@ -152,7 +173,7 @@ def validate_cypher( return None -def validate_cypher_entities_exist(cypher: str, ontology: Ontology) -> list[str]: +def validate_cypher_entities_exist(cypher: str, ontology: "Ontology") -> list[str]: """ Validates whether entities in the Cypher query exist in the ontology. @@ -177,7 +198,7 @@ def validate_cypher_entities_exist(cypher: str, ontology: Ontology) -> list[str] ] -def validate_cypher_relations_exist(cypher: str, ontology: Ontology) -> list[str]: +def validate_cypher_relations_exist(cypher: str, ontology: "Ontology") -> list[str]: """ Validates whether relations in the Cypher query exist in the ontology. @@ -208,7 +229,7 @@ def validate_cypher_relations_exist(cypher: str, ontology: Ontology) -> list[str def validate_cypher_relation_directions( - cypher: str, ontology: Ontology + cypher: str, ontology: "Ontology" ) -> list[str]: """ Validates relation directions in a Cypher query. diff --git a/graphrag_sdk/ontology.py b/graphrag_sdk/ontology.py index a771fe01..09b1210d 100644 --- a/graphrag_sdk/ontology.py +++ b/graphrag_sdk/ontology.py @@ -173,6 +173,48 @@ def from_kg_graph(graph: Graph, sample_size: Optional[int] = 100) -> "Ontology": return ontology + @staticmethod + def from_ttl(path: str) -> "Ontology": + """ + Creates an Ontology object from a TTL/Turtle RDF schema file. + + This method parses an RDF schema file (RDFS or OWL) and extracts: + 1. Classes as entities with their datatype properties as attributes + 2. Object properties as relations between entities + 3. Labels (rdfs:label) and descriptions (rdfs:comment) + + Args: + path (str): Path to the TTL file containing the RDF schema + + Returns: + Ontology: The Ontology object extracted from the RDF schema + + Raises: + ValueError: If the file contains individual instances (only schema definitions allowed) + ImportError: If rdflib is not installed + Exception: If the TTL file cannot be parsed + + """ + try: + from graphrag_sdk.document_loaders.ttl import TTLLoader + from graphrag_sdk.rdf_extractor import RDFOntologyExtractor + except ImportError as e: + raise ImportError( + f"Required packages not found: {e}. " + "Please ensure rdflib is installed with `pip install rdflib`" + ) + + # Load the RDF graph from TTL file + loader = TTLLoader(path) + graph = loader.get_rdf_graph() + + # Extract ontology using RDFOntologyExtractor + extractor = RDFOntologyExtractor(graph) + ontology = extractor.extract() + + logger.info(f"Extracted ontology from TTL file: {len(ontology.entities)} entities, {len(ontology.relations)} relations") + return ontology + def add_entity(self, entity: Entity) -> None: """ Adds an entity to the ontology. diff --git a/graphrag_sdk/rdf_extractor.py b/graphrag_sdk/rdf_extractor.py new file mode 100644 index 00000000..fdd492ff --- /dev/null +++ b/graphrag_sdk/rdf_extractor.py @@ -0,0 +1,301 @@ +""" +RDF Ontology Extractor for extracting ontologies from RDF/OWL schema files. +""" + +import logging +from typing import List, Optional, Dict, Set, Tuple +from rdflib import Graph, URIRef, Namespace +from rdflib.namespace import RDF, RDFS, OWL, XSD + +from graphrag_sdk.entity import Entity +from graphrag_sdk.relation import Relation +from graphrag_sdk.attribute import Attribute, AttributeType +from graphrag_sdk.ontology import Ontology +from graphrag_sdk.helpers import extract_name_from_uri + + +logger = logging.getLogger(__name__) + + +class RDFOntologyExtractor: + """ + Extracts ontology (entities, relations, attributes) from RDF/OWL schema graphs. + + This extractor processes RDF graphs containing RDFS or OWL class and property + definitions to generate a GraphRAG-compatible ontology. It enforces that only + schema definitions are present (no individual instances). + + Key Features: + - Extracts classes as entities with labels and comments + - Extracts object properties as relations with domain/range + - Extracts datatype properties as entity attributes + - Validates that no individuals are present in the schema + - Supports RDFS and OWL vocabularies + """ + + def __init__(self, graph: Graph): + """ + Initialize the RDF Ontology Extractor. + + Args: + graph: An rdflib.Graph containing the RDF schema + + Raises: + ValueError: If the graph contains individual instances + """ + self.graph = graph + self.entities: Dict[str, Entity] = {} + self._check_for_individuals() + + def extract(self) -> Ontology: + """ + Extract complete ontology from the RDF graph. + + Returns: + Ontology object containing all entities and relations + """ + entities = self.extract_entities() + relations = self.extract_relations() + + return Ontology( + entities=entities, + relations=relations + ) + + def extract_entities(self) -> List[Entity]: + """ + Extract all classes as entities. + + Returns: + List of Entity objects + """ + entity_list = [] + seen_classes = set() + + # Find all classes (RDFS and OWL) + classes = set() + for s in self.graph.subjects(RDF.type, RDFS.Class): + classes.add(s) + for s in self.graph.subjects(RDF.type, OWL.Class): + classes.add(s) + + for class_uri in classes: + # Skip blank nodes + if not isinstance(class_uri, URIRef): + continue + + if class_uri in seen_classes: + continue + seen_classes.add(class_uri) + + # Extract label and comment + label = self._extract_label(class_uri) + comment = self._extract_comment(class_uri) + local_name = extract_name_from_uri(str(class_uri)) + + # Use label if available, otherwise local name + entity_name = label if label else local_name + + # Extract attributes (properties with this class as domain) + attributes = self._infer_attributes_for_entity(class_uri) + + entity = Entity( + label=entity_name, + attributes=attributes, + description=comment or "" + ) + + self.entities[str(class_uri)] = entity + entity_list.append(entity) + + logger.info(f"Extracted {len(entity_list)} entities from RDF schema") + return entity_list + + def extract_relations(self) -> List[Relation]: + """ + Extract all object properties as relations. + + Returns: + List of Relation objects + """ + relations = [] + + # Find all properties that look like relations + properties = set() + for s in self.graph.subjects(RDF.type, OWL.ObjectProperty): + properties.add(s) + # Also check generic properties that link two classes + for s in self.graph.subjects(RDF.type, RDF.Property): + properties.add(s) + + for prop_uri in properties: + if not isinstance(prop_uri, URIRef): + continue + + domain = self._get_domain(prop_uri) + range_val = self._get_range(prop_uri) + + # Skip if domain or range is missing + if not domain or not range_val: + # Only warn if it's explicitly an ObjectProperty + if (prop_uri, RDF.type, OWL.ObjectProperty) in self.graph: + label = self._extract_label(prop_uri) or extract_name_from_uri(str(prop_uri)) + logger.warning( + f"Property '{label}' is missing domain or range. " + f"This relation will be skipped." + ) + continue + + # Check if domain/range are properties (property chains) + if self._is_property(domain) or self._is_property(range_val): + logger.warning(f"Property {extract_name_from_uri(str(prop_uri))} has property as domain/range - skipping (property chains not supported)") + continue + + # Check if domain and range are known classes (or at least not datatypes) + if self._is_datatype(range_val): + continue + + # We need to map URIs to Entity names + # If we have processed entities, we can use their names + # Otherwise we extract names from URIs + + domain_str = str(domain) + range_str = str(range_val) + + source_name = self.entities[domain_str].label if domain_str in self.entities else (self._extract_label(domain) or extract_name_from_uri(domain_str)) + target_name = self.entities[range_str].label if range_str in self.entities else (self._extract_label(range_val) or extract_name_from_uri(range_str)) + + label = self._extract_label(prop_uri) + local_name = extract_name_from_uri(str(prop_uri)) + relation_name = label if label else local_name + + relation = Relation( + label=relation_name, + source=source_name, + target=target_name + ) + relations.append(relation) + + logger.info(f"Extracted {len(relations)} relations from RDF schema") + return relations + + def _infer_attributes_for_entity(self, entity_uri: URIRef) -> List[Attribute]: + """ + Find properties where rdfs:domain is this entity. + """ + attributes = [] + + # Find properties with this domain + for prop_uri in self.graph.subjects(RDFS.domain, entity_uri): + # Skip if not a URIRef + if not isinstance(prop_uri, URIRef): + continue + + # Check if it's a datatype property (attribute) or object property (relation) + # If range is a literal/datatype, it's an attribute + range_val = self._get_range(prop_uri) + + if not range_val: + # Default to string attribute if no range + attr_type = AttributeType.STRING + elif self._is_datatype(range_val): + attr_type = self._map_xsd_type(range_val) + else: + # It's likely a relation (range is a class), skip here + continue + + label = self._extract_label(prop_uri) + local_name = extract_name_from_uri(str(prop_uri)) + attr_name = label if label else local_name + + attributes.append(Attribute(name=attr_name, attr_type=attr_type, required=False)) + + return attributes + + def _check_for_individuals(self) -> None: + """ + Check if the graph contains any individual instances. + + Raises: + ValueError: If individuals are found in the graph + """ + # Look for instances (subjects that are instances of a class) + individuals = set() + + # Get all classes defined in the schema + classes = set() + for s in self.graph.subjects(RDF.type, RDFS.Class): + classes.add(s) + for s in self.graph.subjects(RDF.type, OWL.Class): + classes.add(s) + + # Now check if there are any subjects that are instances of these classes + for cls in classes: + for individual in self.graph.subjects(RDF.type, cls): + # Make sure this is not a class definition itself + if not (individual, RDF.type, RDFS.Class) in self.graph and \ + not (individual, RDF.type, OWL.Class) in self.graph: + individuals.add(individual) + + if individuals: + individual_list = [extract_name_from_uri(str(ind)) for ind in list(individuals)[:5]] + error_msg = ( + f"The RDF file contains {len(individuals)} individual instance(s), " + f"but only schema definitions (classes and properties) are allowed. " + f"Examples: {', '.join(individual_list)}" + f"{'...' if len(individuals) > 5 else ''}. " + f"Please provide an RDF schema file (RDFS/OWL) without individual instances." + ) + raise ValueError(error_msg) + + def _get_domain(self, prop_uri: URIRef) -> Optional[URIRef]: + for obj in self.graph.objects(prop_uri, RDFS.domain): + if isinstance(obj, URIRef): + return obj + return None + + def _get_range(self, prop_uri: URIRef) -> Optional[URIRef]: + for obj in self.graph.objects(prop_uri, RDFS.range): + if isinstance(obj, URIRef): + return obj + return None + + def _is_property(self, uri: URIRef) -> bool: + """Check if URI is a property definition""" + return (uri, RDF.type, RDF.Property) in self.graph or \ + (uri, RDF.type, OWL.ObjectProperty) in self.graph or \ + (uri, RDF.type, OWL.DatatypeProperty) in self.graph + + def _is_datatype(self, uri: URIRef) -> bool: + """Check if URI is a datatype (XSD)""" + return str(uri).startswith(str(XSD)) + + def _map_xsd_type(self, xsd_uri: URIRef) -> AttributeType: + """Map XSD types to AttributeType""" + uri_str = str(xsd_uri) + + if uri_str in [str(XSD.integer), str(XSD.int), str(XSD.long), + str(XSD.float), str(XSD.decimal), str(XSD.double), + str(XSD.nonNegativeInteger), str(XSD.positiveInteger), + str(XSD.unsignedLong), str(XSD.unsignedInt), + str(XSD.unsignedShort), str(XSD.unsignedByte), + str(XSD.nonPositiveInteger), str(XSD.negativeInteger), + str(XSD.short), str(XSD.byte)]: + return AttributeType.NUMBER + elif uri_str == str(XSD.boolean): + return AttributeType.BOOLEAN + else: + return AttributeType.STRING + + def _extract_label(self, uri: URIRef) -> Optional[str]: + """Extract rdfs:label""" + for label in self.graph.objects(uri, RDFS.label): + return str(label) + return None + + def _extract_comment(self, uri: URIRef) -> Optional[str]: + """Extract rdfs:comment""" + for comment in self.graph.objects(uri, RDFS.comment): + return str(comment) + return None + diff --git a/graphrag_sdk/source.py b/graphrag_sdk/source.py index dbe3b1dc..2c8e87c1 100644 --- a/graphrag_sdk/source.py +++ b/graphrag_sdk/source.py @@ -9,6 +9,7 @@ CSVLoader, JSONLLoader, StringLoader, + TTLLoader, ) @@ -36,6 +37,8 @@ def Source(path: str, instruction: Optional[str] = None) -> "AbstractSource": s = CSV(path) elif ".jsonl" in path.lower(): s = JSONL(path) + elif ".ttl" in path.lower(): + s = TTL(path) elif ".txt" in path.lower(): s = TEXT(path) else: @@ -188,3 +191,13 @@ class STRING(AbstractSource): def __init__(self, data_source: str): super().__init__(data_source) self.loader = StringLoader(self.data_source) + + +class TTL(AbstractSource): + """ + TTL (Terse RDF Triple Language) resource + """ + + def __init__(self, data_source: str): + super().__init__(data_source) + self.loader = TTLLoader(self.data_source) diff --git a/poetry.lock b/poetry.lock index 15a08b5f..024e42d0 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -6,6 +6,7 @@ version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, @@ -17,6 +18,7 @@ version = "3.12.15" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiohttp-3.12.15-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b6fc902bff74d9b1879ad55f5404153e2b33a82e72a95c89cec5eb6cc9e92fbc"}, {file = "aiohttp-3.12.15-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:098e92835b8119b54c693f2f88a1dec690e20798ca5f5fe5f0520245253ee0af"}, @@ -117,7 +119,7 @@ propcache = ">=0.2.0" yarl = ">=1.17.0,<2.0" [package.extras] -speedups = ["Brotli", "aiodns (>=3.3.0)", "brotlicffi"] +speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "brotlicffi ; platform_python_implementation != \"CPython\""] [[package]] name = "aiosignal" @@ -125,6 +127,7 @@ version = "1.4.0" description = "aiosignal: a list of registered asynchronous callbacks" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e"}, {file = "aiosignal-1.4.0.tar.gz", hash = "sha256:f47eecd9468083c2029cc99945502cb7708b082c232f9aca65da147157b251c7"}, @@ -140,6 +143,7 @@ version = "0.7.16" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"}, {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"}, @@ -151,6 +155,7 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -162,6 +167,7 @@ version = "0.49.0" description = "The official Python library for the anthropic API" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "anthropic-0.49.0-py3-none-any.whl", hash = "sha256:bbc17ad4e7094988d2fa86b87753ded8dce12498f4b85fe5810f208f454a8375"}, {file = "anthropic-0.49.0.tar.gz", hash = "sha256:c09e885b0f674b9119b4f296d8508907f6cff0009bc20d5cf6b35936c40b4398"}, @@ -186,6 +192,7 @@ version = "4.10.0" description = "High-level concurrency and networking framework on top of asyncio or Trio" optional = false python-versions = ">=3.9" +groups = ["main", "dev", "test"] files = [ {file = "anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1"}, {file = "anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6"}, @@ -206,6 +213,8 @@ version = "0.1.4" description = "Disable App Nap on macOS >= 10.9" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "platform_system == \"Darwin\"" files = [ {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"}, @@ -217,6 +226,7 @@ version = "25.1.0" description = "Argon2 for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "argon2_cffi-25.1.0-py3-none-any.whl", hash = "sha256:fdc8b074db390fccb6eb4a3604ae7231f219aa669a2652e0f20e16ba513d5741"}, {file = "argon2_cffi-25.1.0.tar.gz", hash = "sha256:694ae5cc8a42f4c4e2bf2ca0e64e51e23a040c6a517a85074683d3959e1346c1"}, @@ -231,6 +241,7 @@ version = "25.1.0" description = "Low-level CFFI bindings for Argon2" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:3d3f05610594151994ca9ccb3c771115bdb4daef161976a266f0dd8aa9996b8f"}, {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:8b8efee945193e667a396cbc7b4fb7d357297d6234d30a489905d96caabde56b"}, @@ -269,6 +280,7 @@ version = "1.3.0" description = "Better dates & times for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"}, {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"}, @@ -288,6 +300,7 @@ version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, @@ -303,6 +316,7 @@ version = "2.0.5" description = "Simple LRU cache for asyncio" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "async_lru-2.0.5-py3-none-any.whl", hash = "sha256:ab95404d8d2605310d345932697371a5f40def0487c03d6d0ad9138de52c9943"}, {file = "async_lru-2.0.5.tar.gz", hash = "sha256:481d52ccdd27275f42c43a928b4a50c3bfb2d67af4e78b170e3e0bb39c66e5bb"}, @@ -317,10 +331,12 @@ version = "5.0.1" description = "Timeout context manager for asyncio programs" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c"}, {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"}, ] +markers = {main = "python_full_version < \"3.11.3\"", test = "python_version < \"3.11\""} [[package]] name = "attrs" @@ -328,18 +344,19 @@ version = "25.3.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, {file = "attrs-25.3.0.tar.gz", hash = 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"coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"] -tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] +tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""] [[package]] name = "babel" @@ -347,13 +364,14 @@ version = "2.17.0" description = "Internationalization utilities" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2"}, {file = "babel-2.17.0.tar.gz", hash = "sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d"}, ] [package.extras] -dev = ["backports.zoneinfo", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata"] +dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata ; sys_platform == \"win32\""] [[package]] name = "backoff" @@ -361,6 +379,7 @@ version = "2.2.1" description = "Function decoration for backoff and retry" optional = false python-versions = ">=3.7,<4.0" +groups = ["main", "test"] files = [ {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"}, {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"}, @@ -372,6 +391,8 @@ version = "1.2.0" description = "Backport of asyncio.Runner, a context manager that controls event loop life cycle." optional = false python-versions = "<3.11,>=3.8" +groups = ["test"] +markers = "python_version < \"3.11\"" files = [ {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"}, {file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"}, @@ -383,6 +404,7 @@ version = "4.13.5" description = "Screen-scraping library" optional = false python-versions = ">=3.7.0" +groups = ["main", "dev"] files = [ {file = "beautifulsoup4-4.13.5-py3-none-any.whl", hash = "sha256:642085eaa22233aceadff9c69651bc51e8bf3f874fb6d7104ece2beb24b47c4a"}, {file = "beautifulsoup4-4.13.5.tar.gz", hash = "sha256:5e70131382930e7c3de33450a2f54a63d5e4b19386eab43a5b34d594268f3695"}, @@ -405,6 +427,7 @@ version = "6.2.0" description = "An easy safelist-based HTML-sanitizing tool." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "bleach-6.2.0-py3-none-any.whl", hash = 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"sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407"}, @@ -445,6 +470,7 @@ version = "2.0.0" description = "Foreign Function Interface for Python calling C code." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"}, {file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"}, @@ -541,6 +567,7 @@ version = "3.4.3" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." optional = false python-versions = ">=3.7" +groups = ["main", "dev", "test"] files = [ {file = "charset_normalizer-3.4.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fb7f67a1bfa6e40b438170ebdc8158b78dc465a5a67b6dde178a46987b244a72"}, {file = "charset_normalizer-3.4.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:cc9370a2da1ac13f0153780040f465839e6cccb4a1e44810124b4e22483c93fe"}, @@ -629,6 +656,7 @@ version = "8.1.8" description = "Composable command line interface toolkit" optional = false python-versions = ">=3.7" +groups = ["main", "test"] files = [ {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"}, {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"}, @@ -643,10 +671,12 @@ version = "0.4.6" description = "Cross-platform colored terminal text." optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +groups = ["main", "dev", "test"] files = [ {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, ] +markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\"", test = "platform_system == \"Windows\" or sys_platform == \"win32\""} [[package]] name = "comm" @@ -654,6 +684,7 @@ version = "0.2.3" description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "comm-0.2.3-py3-none-any.whl", hash = "sha256:c615d91d75f7f04f095b30d1c1711babd43bdc6419c1be9886a85f2f4e489417"}, {file = "comm-0.2.3.tar.gz", hash = "sha256:2dc8048c10962d55d7ad693be1e7045d891b7ce8d999c97963a5e3e99c055971"}, @@ -668,6 +699,7 @@ version = "1.8.16" description = "An implementation of the Debug Adapter Protocol for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "debugpy-1.8.16-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:2a3958fb9c2f40ed8ea48a0d34895b461de57a1f9862e7478716c35d76f56c65"}, {file = "debugpy-1.8.16-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e5ca7314042e8a614cc2574cd71f6ccd7e13a9708ce3c6d8436959eae56f2378"}, @@ -703,6 +735,7 @@ version = "5.2.1" description = "Decorators for Humans" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "decorator-5.2.1-py3-none-any.whl", hash = "sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a"}, {file = "decorator-5.2.1.tar.gz", hash = "sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360"}, @@ -714,6 +747,7 @@ version = "2.9.7" description = "The LLM Evaluation Framework" optional = false python-versions = "<4.0,>=3.9" +groups = ["test"] files = [ {file = "deepeval-2.9.7-py3-none-any.whl", hash = "sha256:1e998c75bb555d6ee5684c02303861ca1c93931feacc93437022e5309217430c"}, {file = "deepeval-2.9.7.tar.gz", hash = "sha256:d20982e5ba809365234538af8e81fb70b1cb50fd4c84bfa0ceddb2ada781f057"}, @@ -754,6 +788,7 @@ version = "0.7.1" description = "XML bomb protection for Python stdlib modules" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +groups = ["dev"] files = [ {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"}, {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"}, @@ -765,6 +800,7 @@ version = "1.9.0" description = "Distro - an OS platform information API" optional = false python-versions = ">=3.6" +groups = ["main", "test"] files = [ {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"}, {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, @@ -776,6 +812,7 @@ version = "0.20.1" description = "Docutils -- Python Documentation Utilities" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "docutils-0.20.1-py3-none-any.whl", hash = "sha256:96f387a2c5562db4476f09f13bbab2192e764cac08ebbf3a34a95d9b1e4a59d6"}, {file = "docutils-0.20.1.tar.gz", hash = "sha256:f08a4e276c3a1583a86dce3e34aba3fe04d02bba2dd51ed16106244e8a923e3b"}, @@ -787,6 +824,8 @@ version = "1.3.0" description = "Backport of PEP 654 (exception groups)" optional = false python-versions = ">=3.7" +groups = ["main", "dev", "test"] +markers = "python_version < \"3.11\"" files = [ {file = 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"executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4"}, ] [package.extras] -tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"] +tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich ; python_version >= \"3.11\""] [[package]] name = "falkordb" @@ -832,6 +873,7 @@ version = "1.2.0" description = "Python client for interacting with FalkorDB database" optional = false python-versions = "<4.0,>=3.8" +groups = ["main"] files = [ {file = "falkordb-1.2.0-py3-none-any.whl", hash = "sha256:7572d9cc377735d22efc52fe6fe73c7a435422c827b6ea3ca223a850a77be12e"}, {file = "falkordb-1.2.0.tar.gz", hash = "sha256:ce57365b86722d538e75aa5d438de67ecd8eb9478da612506d9812cd7f182d0b"}, @@ -847,6 +889,7 @@ version = "2.21.2" description = "Fastest Python implementation of JSON schema" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "fastjsonschema-2.21.2-py3-none-any.whl", hash = "sha256:1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463"}, {file = "fastjsonschema-2.21.2.tar.gz", hash = "sha256:b1eb43748041c880796cd077f1a07c3d94e93ae84bba5ed36800a33554ae05de"}, @@ -861,6 +904,7 @@ version = "0.12.0" description = "Python bindings to Rust's UUID library." optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "fastuuid-0.12.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:22a900ef0956aacf862b460e20541fdae2d7c340594fe1bd6fdcb10d5f0791a9"}, {file = "fastuuid-0.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0302f5acf54dc75de30103025c5a95db06d6c2be36829043a0aa16fc170076bc"}, @@ -878,6 +922,7 @@ files = [ {file = "fastuuid-0.12.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b9b31dd488d0778c36f8279b306dc92a42f16904cba54acca71e107d65b60b0c"}, {file = 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">=3.9" +groups = ["main"] files = [ {file = "filelock-3.19.1-py3-none-any.whl", hash = "sha256:d38e30481def20772f5baf097c122c3babc4fcdb7e14e57049eb9d88c6dc017d"}, {file = "filelock-3.19.1.tar.gz", hash = "sha256:66eda1888b0171c998b35be2bcc0f6d75c388a7ce20c3f3f37aa8e96c2dddf58"}, @@ -906,6 +952,7 @@ version = "0.0.18" description = "Fixes broken JSON string objects" optional = false python-versions = ">=3.6" +groups = ["main"] files = [ {file = "fix-busted-json-0.0.18.tar.gz", hash = "sha256:93c5dab7cae3b5d0b055f2c7043f9fe727a88a80d0be753c5f2c20bb9b69672f"}, {file = "fix_busted_json-0.0.18-py3-none-any.whl", hash = "sha256:fdce0e02c9a810b3aa28e1c3c32c24b21b44e89f6315ec25d2b963bd52a6ef03"}, @@ -917,6 +964,7 @@ version = "1.5.1" description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers" optional = false python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4" +groups = ["dev"] files = [ {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"}, {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"}, @@ -928,6 +976,7 @@ version = "1.7.0" description = "A list-like structure which implements collections.abc.MutableSequence" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "frozenlist-1.7.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:cc4df77d638aa2ed703b878dd093725b72a824c3c546c076e8fdf276f78ee84a"}, {file = "frozenlist-1.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:716a9973a2cc963160394f701964fe25012600f3d311f60c790400b00e568b61"}, @@ -1041,6 +1090,7 @@ version = "2025.9.0" description = "File-system specification" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "fsspec-2025.9.0-py3-none-any.whl", hash = "sha256:530dc2a2af60a414a832059574df4a6e10cce927f6f4a78209390fe38955cfb7"}, {file = "fsspec-2025.9.0.tar.gz", hash = "sha256:19fd429483d25d28b65ec68f9f4adc16c17ea2c7c7bf54ec61360d478fb19c19"}, @@ -1071,7 +1121,7 @@ smb = ["smbprotocol"] ssh = ["paramiko"] test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"] test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"] -test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"] +test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard ; python_version < \"3.14\""] tqdm = ["tqdm"] [[package]] @@ -1080,6 +1130,7 @@ version = "2.40.3" description = "Google Authentication Library" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "google_auth-2.40.3-py2.py3-none-any.whl", hash = "sha256:1370d4593e86213563547f97a92752fc658456fe4514c809544f330fed45a7ca"}, {file = "google_auth-2.40.3.tar.gz", hash = "sha256:500c3a29adedeb36ea9cf24b8d10858e152f2412e3ca37829b3fa18e33d63b77"}, @@ -1093,11 +1144,11 @@ rsa = ">=3.1.4,<5" [package.extras] aiohttp = ["aiohttp (>=3.6.2,<4.0.0)", "requests (>=2.20.0,<3.0.0)"] enterprise-cert = ["cryptography", "pyopenssl"] -pyjwt = ["cryptography (<39.0.0)", "cryptography (>=38.0.3)", "pyjwt (>=2.0)"] -pyopenssl = ["cryptography (<39.0.0)", "cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"] +pyjwt = ["cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "pyjwt (>=2.0)"] +pyopenssl = ["cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"] reauth = ["pyu2f (>=0.1.5)"] requests = ["requests (>=2.20.0,<3.0.0)"] -testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "cryptography (<39.0.0)", "cryptography (>=38.0.3)", "flask", "freezegun", "grpcio", "mock", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"] +testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "flask", "freezegun", "grpcio", "mock", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"] urllib3 = ["packaging", "urllib3"] [[package]] @@ -1106,6 +1157,7 @@ version = "1.38.0" description = "GenAI Python SDK" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "google_genai-1.38.0-py3-none-any.whl", hash = "sha256:95407425132d42b3fa11bc92b3f5cf61a0fbd8d9add1f0e89aac52c46fbba090"}, {file = "google_genai-1.38.0.tar.gz", hash = "sha256:363272fc4f677d0be6a1aed7ebabe8adf45e1626a7011a7886a587e9464ca9ec"}, @@ -1131,6 +1183,7 @@ version = "1.70.0" description = "Common protobufs used in Google APIs" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "googleapis_common_protos-1.70.0-py3-none-any.whl", hash = "sha256:b8bfcca8c25a2bb253e0e0b0adaf8c00773e5e6af6fd92397576680b807e0fd8"}, {file = "googleapis_common_protos-1.70.0.tar.gz", hash = "sha256:0e1b44e0ea153e6594f9f394fef15193a68aaaea2d843f83e2742717ca753257"}, @@ -1148,6 +1201,7 @@ version = "1.75.0" description = "HTTP/2-based RPC framework" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "grpcio-1.75.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:1ec9cbaec18d9597c718b1ed452e61748ac0b36ba350d558f9ded1a94cc15ec7"}, {file = "grpcio-1.75.0-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:7ee5ee42bfae8238b66a275f9ebcf6f295724375f2fa6f3b52188008b6380faf"}, @@ -1214,6 +1268,7 @@ version = "0.16.0" description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1" optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86"}, {file = "h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1"}, @@ -1225,6 +1280,8 @@ version = "1.1.10" description = "Fast transfer of large files with the Hugging Face Hub." optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\"" files = [ {file = "hf_xet-1.1.10-cp37-abi3-macosx_10_12_x86_64.whl", hash = "sha256:686083aca1a6669bc85c21c0563551cbcdaa5cf7876a91f3d074a030b577231d"}, {file = "hf_xet-1.1.10-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:71081925383b66b24eedff3013f8e6bbd41215c3338be4b94ba75fd75b21513b"}, @@ -1245,6 +1302,7 @@ version = "1.0.9" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55"}, {file = "httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8"}, @@ -1266,6 +1324,7 @@ version = "0.28.1" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"}, {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"}, @@ -1278,7 +1337,7 @@ httpcore = "==1.*" idna = "*" [package.extras] -brotli = ["brotli", "brotlicffi"] +brotli = ["brotli ; platform_python_implementation == \"CPython\"", "brotlicffi ; platform_python_implementation != \"CPython\""] cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] @@ -1290,6 +1349,7 @@ version = "0.35.0" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" +groups = ["main"] files = [ {file = "huggingface_hub-0.35.0-py3-none-any.whl", hash = "sha256:f2e2f693bca9a26530b1c0b9bcd4c1495644dad698e6a0060f90e22e772c31e9"}, {file = "huggingface_hub-0.35.0.tar.gz", hash = "sha256:ccadd2a78eef75effff184ad89401413629fabc52cefd76f6bbacb9b1c0676ac"}, @@ -1306,16 +1366,16 @@ tqdm = ">=4.42.1" typing-extensions = ">=3.7.4.3" [package.extras] -all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "mypy (>=1.14.1,<1.15.0)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] +all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] cli = ["InquirerPy (==0.3.4)"] -dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "mypy (>=1.14.1,<1.15.0)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] +dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"] hf-transfer = ["hf-transfer (>=0.1.4)"] hf-xet = ["hf-xet (>=1.1.2,<2.0.0)"] inference = ["aiohttp"] mcp = ["aiohttp", "mcp (>=1.8.0)", "typer"] oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"] -quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "mypy (>=1.14.1,<1.15.0)", "ruff (>=0.9.0)", "ty"] +quality = ["libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "ruff (>=0.9.0)", "ty"] tensorflow = ["graphviz", "pydot", "tensorflow"] tensorflow-testing = ["keras (<3.0)", "tensorflow"] testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"] @@ -1328,6 +1388,7 @@ version = "3.10" description = "Internationalized Domain Names in Applications (IDNA)" optional = false python-versions = ">=3.6" +groups = ["main", "dev", "test"] files = [ {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"}, {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"}, @@ -1342,6 +1403,7 @@ version = "1.4.1" description = "Getting image size from png/jpeg/jpeg2000/gif file" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +groups = ["dev"] files = [ {file = "imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b"}, {file = "imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a"}, @@ -1353,6 +1415,7 @@ version = "8.7.0" description = "Read metadata from Python packages" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd"}, {file = "importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000"}, @@ -1362,12 +1425,12 @@ files = [ zipp = ">=3.20" [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] perf = ["ipython"] -test = ["flufl.flake8", "importlib_resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"] +test = ["flufl.flake8", "importlib_resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"] type = ["pytest-mypy"] [[package]] @@ -1376,6 +1439,7 @@ version = "2.1.0" description = "brain-dead simple config-ini parsing" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760"}, {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"}, @@ -1387,6 +1451,7 @@ version = "6.30.1" description = "IPython Kernel for Jupyter" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "ipykernel-6.30.1-py3-none-any.whl", hash = "sha256:aa6b9fb93dca949069d8b85b6c79b2518e32ac583ae9c7d37c51d119e18b3fb4"}, {file = "ipykernel-6.30.1.tar.gz", hash = "sha256:6abb270161896402e76b91394fcdce5d1be5d45f456671e5080572f8505be39b"}, @@ -1420,6 +1485,7 @@ version = "8.37.0" description = "IPython: Productive Interactive Computing" optional = false python-versions = ">=3.10" +groups = ["dev"] files = [ {file = "ipython-8.37.0-py3-none-any.whl", hash = "sha256:ed87326596b878932dbcb171e3e698845434d8c61b8d8cd474bf663041a9dcf2"}, {file = "ipython-8.37.0.tar.gz", hash = "sha256:ca815841e1a41a1e6b73a0b08f3038af9b2252564d01fc405356d34033012216"}, @@ -1441,7 +1507,7 @@ typing_extensions = {version = ">=4.6", markers = "python_version < \"3.12\""} [package.extras] all = ["ipython[black,doc,kernel,matplotlib,nbconvert,nbformat,notebook,parallel,qtconsole]", "ipython[test,test-extra]"] black = ["black"] -doc = ["docrepr", "exceptiongroup", "intersphinx_registry", "ipykernel", "ipython[test]", "matplotlib", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "sphinxcontrib-jquery", "tomli", "typing_extensions"] +doc = ["docrepr", "exceptiongroup", "intersphinx_registry", "ipykernel", "ipython[test]", "matplotlib", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "sphinxcontrib-jquery", "tomli ; python_version < \"3.11\"", "typing_extensions"] kernel = ["ipykernel"] matplotlib = ["matplotlib"] nbconvert = ["nbconvert"] @@ -1458,6 +1524,7 @@ version = "8.1.7" description = "Jupyter interactive widgets" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "ipywidgets-8.1.7-py3-none-any.whl", hash = "sha256:764f2602d25471c213919b8a1997df04bef869251db4ca8efba1b76b1bd9f7bb"}, {file = "ipywidgets-8.1.7.tar.gz", hash = "sha256:15f1ac050b9ccbefd45dccfbb2ef6bed0029d8278682d569d71b8dd96bee0376"}, @@ -1473,12 +1540,26 @@ widgetsnbextension = ">=4.0.14,<4.1.0" [package.extras] test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"] +[[package]] +name = "isodate" +version = "0.7.2" +description = "An ISO 8601 date/time/duration parser and formatter" +optional = false +python-versions = ">=3.7" +groups = ["main"] +markers = "python_version < \"3.11\"" +files = [ + {file = "isodate-0.7.2-py3-none-any.whl", hash = "sha256:28009937d8031054830160fce6d409ed342816b543597cece116d966c6d99e15"}, + {file = "isodate-0.7.2.tar.gz", hash = "sha256:4cd1aa0f43ca76f4a6c6c0292a85f40b35ec2e43e315b59f06e6d32171a953e6"}, +] + [[package]] name = "isoduration" version = "20.11.0" description = "Operations with ISO 8601 durations" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"}, {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"}, @@ -1493,6 +1574,7 @@ version = "0.19.2" description = "An autocompletion tool for Python that can be used for text editors." optional = false python-versions = ">=3.6" +groups = ["dev"] files = [ {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"}, {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"}, @@ -1512,6 +1594,7 @@ version = "3.1.6" description = "A very fast and expressive template engine." optional = false python-versions = ">=3.7" +groups = ["main", "dev"] files = [ {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"}, {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"}, @@ -1529,6 +1612,7 @@ version = "0.11.0" description = "Fast iterable JSON parser." optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "jiter-0.11.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:3893ce831e1c0094a83eeaf56c635a167d6fa8cc14393cc14298fd6fdc2a2449"}, {file = "jiter-0.11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:25c625b9b61b5a8725267fdf867ef2e51b429687f6a4eef211f4612e95607179"}, @@ -1616,13 +1700,14 @@ version = "0.12.1" description = "A Python implementation of the JSON5 data format." optional = false python-versions = ">=3.8.0" +groups = ["dev"] files = [ {file = "json5-0.12.1-py3-none-any.whl", hash = "sha256:d9c9b3bc34a5f54d43c35e11ef7cb87d8bdd098c6ace87117a7b7e83e705c1d5"}, {file = "json5-0.12.1.tar.gz", hash = "sha256:b2743e77b3242f8d03c143dd975a6ec7c52e2f2afe76ed934e53503dd4ad4990"}, ] [package.extras] -dev = ["build (==1.2.2.post1)", "coverage (==7.5.4)", "coverage (==7.8.0)", "mypy (==1.14.1)", "mypy (==1.15.0)", "pip (==25.0.1)", "pylint (==3.2.7)", "pylint (==3.3.6)", "ruff (==0.11.2)", "twine (==6.1.0)", "uv (==0.6.11)"] +dev = ["build (==1.2.2.post1)", "coverage (==7.5.4) ; python_version < \"3.9\"", "coverage (==7.8.0) ; python_version >= \"3.9\"", "mypy (==1.14.1) ; python_version < \"3.9\"", "mypy (==1.15.0) ; python_version >= \"3.9\"", "pip (==25.0.1)", "pylint (==3.2.7) ; python_version < \"3.9\"", "pylint (==3.3.6) ; python_version >= \"3.9\"", "ruff (==0.11.2)", "twine (==6.1.0)", "uv (==0.6.11)"] [[package]] name = "jsonpointer" @@ -1630,6 +1715,7 @@ version = "3.0.0" description = "Identify specific nodes in a JSON document (RFC 6901)" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"}, {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"}, @@ -1641,6 +1727,7 @@ version = "4.25.1" description = "An implementation of JSON Schema validation for Python" optional = false python-versions = ">=3.9" +groups = ["main", "dev"] files = [ {file = "jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63"}, {file = "jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85"}, @@ -1671,6 +1758,7 @@ version = "2025.9.1" description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry" optional = false python-versions = ">=3.9" +groups = ["main", "dev"] files = [ {file = "jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe"}, {file = "jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d"}, @@ -1685,6 +1773,7 @@ version = "1.1.1" description = "Jupyter metapackage. Install all the Jupyter components in one go." optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "jupyter-1.1.1-py2.py3-none-any.whl", hash = "sha256:7a59533c22af65439b24bbe60373a4e95af8f16ac65a6c00820ad378e3f7cc83"}, {file = "jupyter-1.1.1.tar.gz", hash = "sha256:d55467bceabdea49d7e3624af7e33d59c37fff53ed3a350e1ac957bed731de7a"}, @@ -1704,6 +1793,7 @@ version = "8.6.3" description = "Jupyter protocol implementation and client libraries" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyter_client-8.6.3-py3-none-any.whl", hash = "sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f"}, {file = "jupyter_client-8.6.3.tar.gz", hash = "sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419"}, @@ -1718,7 +1808,7 @@ traitlets = ">=5.3" [package.extras] docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"] -test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"] +test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko ; sys_platform == \"win32\"", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"] [[package]] name = "jupyter-console" @@ -1726,6 +1816,7 @@ version = "6.6.3" description = "Jupyter terminal console" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "jupyter_console-6.6.3-py3-none-any.whl", hash = "sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485"}, {file = "jupyter_console-6.6.3.tar.gz", hash = "sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539"}, @@ -1750,6 +1841,7 @@ version = "5.8.1" description = "Jupyter core package. A base package on which Jupyter projects rely." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyter_core-5.8.1-py3-none-any.whl", hash = "sha256:c28d268fc90fb53f1338ded2eb410704c5449a358406e8a948b75706e24863d0"}, {file = "jupyter_core-5.8.1.tar.gz", hash = "sha256:0a5f9706f70e64786b75acba995988915ebd4601c8a52e534a40b51c95f59941"}, @@ -1770,6 +1862,7 @@ version = "0.12.0" description = "Jupyter Event System library" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "jupyter_events-0.12.0-py3-none-any.whl", hash = "sha256:6464b2fa5ad10451c3d35fabc75eab39556ae1e2853ad0c0cc31b656731a97fb"}, {file = "jupyter_events-0.12.0.tar.gz", hash = "sha256:fc3fce98865f6784c9cd0a56a20644fc6098f21c8c33834a8d9fe383c17e554b"}, @@ -1796,6 +1889,7 @@ version = "2.3.0" description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyter_lsp-2.3.0-py3-none-any.whl", hash = "sha256:e914a3cb2addf48b1c7710914771aaf1819d46b2e5a79b0f917b5478ec93f34f"}, {file = "jupyter_lsp-2.3.0.tar.gz", hash = "sha256:458aa59339dc868fb784d73364f17dbce8836e906cd75fd471a325cba02e0245"}, @@ -1810,6 +1904,7 @@ version = "2.17.0" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "jupyter_server-2.17.0-py3-none-any.whl", hash = "sha256:e8cb9c7db4251f51ed307e329b81b72ccf2056ff82d50524debde1ee1870e13f"}, {file = "jupyter_server-2.17.0.tar.gz", hash = "sha256:c38ea898566964c888b4772ae1ed58eca84592e88251d2cfc4d171f81f7e99d5"}, @@ -1846,6 +1941,7 @@ version = "0.5.3" description = "A Jupyter Server Extension Providing Terminals." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyter_server_terminals-0.5.3-py3-none-any.whl", hash = "sha256:41ee0d7dc0ebf2809c668e0fc726dfaf258fcd3e769568996ca731b6194ae9aa"}, {file = "jupyter_server_terminals-0.5.3.tar.gz", hash = "sha256:5ae0295167220e9ace0edcfdb212afd2b01ee8d179fe6f23c899590e9b8a5269"}, @@ -1865,6 +1961,7 @@ version = "4.4.7" description = "JupyterLab computational environment" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "jupyterlab-4.4.7-py3-none-any.whl", hash = "sha256:808bae6136b507a4d18f04254218bfe71ed8ba399a36ef3280d5f259e69abf80"}, {file = "jupyterlab-4.4.7.tar.gz", hash = "sha256:8c8e225492f4513ebde9bbbc00a05b651ab9a1f5b0013015d96fabf671c37188"}, @@ -1899,6 +1996,7 @@ version = "0.3.0" description = "Pygments theme using JupyterLab CSS variables" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780"}, {file = "jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d"}, @@ -1910,6 +2008,7 @@ version = "2.27.3" description = "A set of server components for JupyterLab and JupyterLab like applications." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "jupyterlab_server-2.27.3-py3-none-any.whl", hash = "sha256:e697488f66c3db49df675158a77b3b017520d772c6e1548c7d9bcc5df7944ee4"}, {file = "jupyterlab_server-2.27.3.tar.gz", hash = "sha256:eb36caca59e74471988f0ae25c77945610b887f777255aa21f8065def9e51ed4"}, @@ -1935,6 +2034,7 @@ version = "3.0.15" description = "Jupyter interactive widgets for JupyterLab" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "jupyterlab_widgets-3.0.15-py3-none-any.whl", hash = "sha256:d59023d7d7ef71400d51e6fee9a88867f6e65e10a4201605d2d7f3e8f012a31c"}, {file = "jupyterlab_widgets-3.0.15.tar.gz", hash = "sha256:2920888a0c2922351a9202817957a68c07d99673504d6cd37345299e971bb08b"}, @@ -1946,6 +2046,7 @@ version = "1.2.2" description = "a modern parsing library" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "lark-1.2.2-py3-none-any.whl", hash = "sha256:c2276486b02f0f1b90be155f2c8ba4a8e194d42775786db622faccd652d8e80c"}, {file = "lark-1.2.2.tar.gz", hash = "sha256:ca807d0162cd16cef15a8feecb862d7319e7a09bdb13aef927968e45040fed80"}, @@ -1963,6 +2064,7 @@ version = "1.77.1" description = "Library to easily interface with LLM API providers" optional = false python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8" +groups = ["main"] files = [ {file = "litellm-1.77.1-py3-none-any.whl", hash = "sha256:407761dc3c35fbcd41462d3fe65dd3ed70aac705f37cde318006c18940f695a0"}, {file = "litellm-1.77.1.tar.gz", hash = "sha256:76bab5203115efb9588244e5bafbfc07a800a239be75d8dc6b1b9d17394c6418"}, @@ -1984,10 +2086,10 @@ tokenizers = "*" [package.extras] caching = ["diskcache (>=5.6.1,<6.0.0)"] -extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-iam (>=2.19.1,<3.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0)", "resend (>=0.8.0,<0.9.0)"] -mlflow = ["mlflow (>3.1.4)"] -proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-storage-blob (>=12.25.1,<13.0.0)", "backoff", "boto3 (==1.36.0)", "cryptography", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "litellm-enterprise (==0.1.19)", "litellm-proxy-extras (==0.2.18)", "mcp (>=1.10.0,<2.0.0)", "orjson (>=3.9.7,<4.0.0)", "polars (>=1.31.0,<2.0.0)", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rich (==13.7.1)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0)", "websockets (>=13.1.0,<14.0.0)"] -semantic-router = ["semantic-router"] +extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-iam (>=2.19.1,<3.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0) ; python_version >= \"3.9\" and python_version < \"3.14\"", "resend (>=0.8.0,<0.9.0)"] +mlflow = ["mlflow (>3.1.4) ; python_version >= \"3.10\""] +proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-storage-blob (>=12.25.1,<13.0.0)", "backoff", "boto3 (==1.36.0)", "cryptography", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "litellm-enterprise (==0.1.19)", "litellm-proxy-extras (==0.2.18)", "mcp (>=1.10.0,<2.0.0) ; python_version >= \"3.10\"", "orjson (>=3.9.7,<4.0.0)", "polars (>=1.31.0,<2.0.0) ; python_version >= \"3.10\"", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rich (==13.7.1)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0) ; sys_platform != \"win32\"", "websockets (>=13.1.0,<14.0.0)"] +semantic-router = ["semantic-router ; python_version >= \"3.9\""] utils = ["numpydoc"] [[package]] @@ -1996,6 +2098,7 @@ version = "4.0.0" description = "Python port of markdown-it. Markdown parsing, done right!" optional = false python-versions = ">=3.10" +groups = ["main", "test"] files = [ {file = "markdown_it_py-4.0.0-py3-none-any.whl", hash = "sha256:87327c59b172c5011896038353a81343b6754500a08cd7a4973bb48c6d578147"}, {file = "markdown_it_py-4.0.0.tar.gz", hash = "sha256:cb0a2b4aa34f932c007117b194e945bd74e0ec24133ceb5bac59009cda1cb9f3"}, @@ -2019,6 +2122,7 @@ version = "3.0.2" description = "Safely add untrusted strings to HTML/XML markup." optional = false python-versions = ">=3.9" +groups = ["main", "dev"] files = [ {file = "MarkupSafe-3.0.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7e94c425039cde14257288fd61dcfb01963e658efbc0ff54f5306b06054700f8"}, {file = "MarkupSafe-3.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9e2d922824181480953426608b81967de705c3cef4d1af983af849d7bd619158"}, @@ -2089,6 +2193,7 @@ version = "0.1.7" description = "Inline Matplotlib backend for Jupyter" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "matplotlib_inline-0.1.7-py3-none-any.whl", hash = "sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca"}, {file = "matplotlib_inline-0.1.7.tar.gz", hash = "sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90"}, @@ -2103,6 +2208,7 @@ version = "0.1.2" description = "Markdown URL utilities" optional = false python-versions = ">=3.7" +groups = ["main", "test"] files = [ {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"}, {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"}, @@ -2114,6 +2220,7 @@ version = "3.1.4" description = "A sane and fast Markdown parser with useful plugins and renderers" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "mistune-3.1.4-py3-none-any.whl", hash = "sha256:93691da911e5d9d2e23bc54472892aff676df27a75274962ff9edc210364266d"}, {file = "mistune-3.1.4.tar.gz", hash = "sha256:b5a7f801d389f724ec702840c11d8fc48f2b33519102fc7ee739e8177b672164"}, @@ -2128,6 +2235,7 @@ version = "1.6" description = "An implementation of time.monotonic() for Python 2 & < 3.3" optional = false python-versions = "*" +groups = ["test"] files = [ {file = "monotonic-1.6-py2.py3-none-any.whl", hash = "sha256:68687e19a14f11f26d140dd5c86f3dba4bf5df58003000ed467e0e2a69bca96c"}, {file = "monotonic-1.6.tar.gz", hash = "sha256:3a55207bcfed53ddd5c5bae174524062935efed17792e9de2ad0205ce9ad63f7"}, @@ -2139,6 +2247,7 @@ version = "6.6.4" description = "multidict implementation" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "multidict-6.6.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b8aa6f0bd8125ddd04a6593437bad6a7e70f300ff4180a531654aa2ab3f6d58f"}, {file = "multidict-6.6.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b9e5853bbd7264baca42ffc53391b490d65fe62849bf2c690fa3f6273dbcd0cb"}, @@ -2261,6 +2370,7 @@ version = "0.10.2" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." optional = false python-versions = ">=3.9.0" +groups = ["dev"] files = [ {file = "nbclient-0.10.2-py3-none-any.whl", hash = "sha256:4ffee11e788b4a27fabeb7955547e4318a5298f34342a4bfd01f2e1faaeadc3d"}, {file = "nbclient-0.10.2.tar.gz", hash = "sha256:90b7fc6b810630db87a6d0c2250b1f0ab4cf4d3c27a299b0cde78a4ed3fd9193"}, @@ -2283,6 +2393,7 @@ version = "7.16.6" description = "Converting Jupyter Notebooks (.ipynb files) to other formats. Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script. nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "nbconvert-7.16.6-py3-none-any.whl", hash = "sha256:1375a7b67e0c2883678c48e506dc320febb57685e5ee67faa51b18a90f3a712b"}, {file = "nbconvert-7.16.6.tar.gz", hash = "sha256:576a7e37c6480da7b8465eefa66c17844243816ce1ccc372633c6b71c3c0f582"}, @@ -2319,6 +2430,7 @@ version = "5.10.4" description = "The Jupyter Notebook format" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "nbformat-5.10.4-py3-none-any.whl", hash = "sha256:3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b"}, {file = "nbformat-5.10.4.tar.gz", hash = "sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a"}, @@ -2340,6 +2452,7 @@ version = "1.6.0" description = "Patch asyncio to allow nested event loops" optional = false python-versions = ">=3.5" +groups = ["dev", "test"] files = [ {file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"}, {file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"}, @@ -2351,6 +2464,7 @@ version = "7.4.5" description = "Jupyter Notebook - A web-based notebook environment for interactive computing" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "notebook-7.4.5-py3-none-any.whl", hash = "sha256:351635461aca9dad08cf8946a4216f963e2760cc1bf7b1aaaecb23afc33ec046"}, {file = "notebook-7.4.5.tar.gz", hash = "sha256:7c2c4ea245913c3ad8ab3e5d36b34a842c06e524556f5c2e1f5d7d08c986615e"}, @@ -2366,7 +2480,7 @@ tornado = ">=6.2.0" [package.extras] dev = ["hatch", "pre-commit"] docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"] -test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] +test = ["importlib-resources (>=5.0) ; python_version < \"3.10\"", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"] [[package]] name = "notebook-shim" @@ -2374,6 +2488,7 @@ version = "0.2.4" description = "A shim layer for notebook traits and config" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "notebook_shim-0.2.4-py3-none-any.whl", hash = "sha256:411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef"}, {file = "notebook_shim-0.2.4.tar.gz", hash = "sha256:b4b2cfa1b65d98307ca24361f5b30fe785b53c3fd07b7a47e89acb5e6ac638cb"}, @@ -2391,6 +2506,8 @@ version = "2.2.6" description = "Fundamental package for array computing in Python" optional = false python-versions = ">=3.10" +groups = ["dev"] +markers = "python_version < \"3.11\"" files = [ {file = "numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb"}, {file = "numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90"}, @@ -2455,6 +2572,8 @@ version = "2.3.3" description = "Fundamental package for array computing in Python" optional = false python-versions = ">=3.11" +groups = ["dev"] +markers = "python_version >= \"3.11\"" files = [ {file = "numpy-2.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0ffc4f5caba7dfcbe944ed674b7eef683c7e94874046454bb79ed7ee0236f59d"}, {file = "numpy-2.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e7e946c7170858a0295f79a60214424caac2ffdb0063d4d79cb681f9aa0aa569"}, @@ -2538,6 +2657,7 @@ version = "0.5.4" description = "The official Python client for Ollama." optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "ollama-0.5.4-py3-none-any.whl", hash = "sha256:6374c9bb4f2a371b3583c09786112ba85b006516745689c172a7e28af4d4d1a2"}, {file = "ollama-0.5.4.tar.gz", hash = "sha256:75857505a5d42e5e58114a1b78cc8c24596d8866863359d8a2329946a9b6d6f3"}, @@ -2553,6 +2673,7 @@ version = "1.107.3" description = "The official Python library for the openai API" optional = false python-versions = ">=3.8" +groups = ["main", "test"] files = [ {file = "openai-1.107.3-py3-none-any.whl", hash = "sha256:4ca54a847235ac04c6320da70fdc06b62d71439de9ec0aa40d5690c3064d4025"}, {file = "openai-1.107.3.tar.gz", hash = "sha256:69bb8032b05c5f00f7660e422f70f9aabc94793b9a30c5f899360ed21e46314f"}, @@ -2580,6 +2701,7 @@ version = "1.37.0" description = "OpenTelemetry Python API" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_api-1.37.0-py3-none-any.whl", hash = "sha256:accf2024d3e89faec14302213bc39550ec0f4095d1cf5ca688e1bfb1c8612f47"}, {file = "opentelemetry_api-1.37.0.tar.gz", hash = "sha256:540735b120355bd5112738ea53621f8d5edb35ebcd6fe21ada3ab1c61d1cd9a7"}, @@ -2595,6 +2717,7 @@ version = "1.37.0" description = "OpenTelemetry Protobuf encoding" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_exporter_otlp_proto_common-1.37.0-py3-none-any.whl", hash = "sha256:53038428449c559b0c564b8d718df3314da387109c4d36bd1b94c9a641b0292e"}, {file = "opentelemetry_exporter_otlp_proto_common-1.37.0.tar.gz", hash = "sha256:c87a1bdd9f41fdc408d9cc9367bb53f8d2602829659f2b90be9f9d79d0bfe62c"}, @@ -2609,6 +2732,7 @@ version = "1.37.0" description = "OpenTelemetry Collector Protobuf over gRPC Exporter" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_exporter_otlp_proto_grpc-1.37.0-py3-none-any.whl", hash = "sha256:aee5104835bf7993b7ddaaf380b6467472abaedb1f1dbfcc54a52a7d781a3890"}, {file = "opentelemetry_exporter_otlp_proto_grpc-1.37.0.tar.gz", hash = "sha256:f55bcb9fc848ce05ad3dd954058bc7b126624d22c4d9e958da24d8537763bec5"}, @@ -2632,6 +2756,7 @@ version = "1.37.0" description = "OpenTelemetry Python Proto" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_proto-1.37.0-py3-none-any.whl", hash = "sha256:8ed8c066ae8828bbf0c39229979bdf583a126981142378a9cbe9d6fd5701c6e2"}, {file = "opentelemetry_proto-1.37.0.tar.gz", hash = "sha256:30f5c494faf66f77faeaefa35ed4443c5edb3b0aa46dad073ed7210e1a789538"}, @@ -2646,6 +2771,7 @@ version = "1.37.0" description = "OpenTelemetry Python SDK" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_sdk-1.37.0-py3-none-any.whl", hash = "sha256:8f3c3c22063e52475c5dbced7209495c2c16723d016d39287dfc215d1771257c"}, {file = "opentelemetry_sdk-1.37.0.tar.gz", hash = "sha256:cc8e089c10953ded765b5ab5669b198bbe0af1b3f89f1007d19acd32dc46dda5"}, @@ -2662,6 +2788,7 @@ version = "0.58b0" description = "OpenTelemetry Semantic Conventions" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "opentelemetry_semantic_conventions-0.58b0-py3-none-any.whl", hash = "sha256:5564905ab1458b96684db1340232729fce3b5375a06e140e8904c78e4f815b28"}, {file = "opentelemetry_semantic_conventions-0.58b0.tar.gz", hash = "sha256:6bd46f51264279c433755767bb44ad00f1c9e2367e1b42af563372c5a6fa0c25"}, @@ -2677,6 +2804,8 @@ version = "7.7.0" description = "A decorator to automatically detect mismatch when overriding a method." optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "python_version <= \"3.11\"" files = [ {file = "overrides-7.7.0-py3-none-any.whl", hash = "sha256:c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49"}, {file = "overrides-7.7.0.tar.gz", hash = "sha256:55158fa3d93b98cc75299b1e67078ad9003ca27945c76162c1c0766d6f91820a"}, @@ -2688,6 +2817,7 @@ version = "25.0" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484"}, {file = "packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f"}, @@ -2699,6 +2829,7 @@ version = "2.3.2" description = "Powerful data structures for data analysis, time series, and statistics" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "pandas-2.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:52bc29a946304c360561974c6542d1dd628ddafa69134a7131fdfd6a5d7a1a35"}, {file = "pandas-2.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:220cc5c35ffaa764dd5bb17cf42df283b5cb7fdf49e10a7b053a06c9cb48ee2b"}, @@ -2785,6 +2916,7 @@ version = "1.5.1" description = "Utilities for writing pandoc filters in python" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +groups = ["dev"] files = [ {file = "pandocfilters-1.5.1-py2.py3-none-any.whl", hash = "sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc"}, {file = "pandocfilters-1.5.1.tar.gz", hash = "sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e"}, @@ -2796,6 +2928,7 @@ version = "0.8.5" description = "A Python Parser" optional = false python-versions = ">=3.6" +groups = ["dev"] files = [ {file = "parso-0.8.5-py2.py3-none-any.whl", hash = "sha256:646204b5ee239c396d040b90f9e272e9a8017c630092bf59980beb62fd033887"}, {file = "parso-0.8.5.tar.gz", hash = "sha256:034d7354a9a018bdce352f48b2a8a450f05e9d6ee85db84764e9b6bd96dafe5a"}, @@ -2811,6 +2944,8 @@ version = "4.9.0" description = "Pexpect allows easy control of interactive console applications." optional = false python-versions = "*" +groups = ["dev"] +markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\"" files = [ {file = "pexpect-4.9.0-py2.py3-none-any.whl", hash = "sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523"}, {file = "pexpect-4.9.0.tar.gz", hash = "sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f"}, @@ -2825,6 +2960,7 @@ version = "4.4.0" description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "platformdirs-4.4.0-py3-none-any.whl", hash = "sha256:abd01743f24e5287cd7a5db3752faf1a2d65353f38ec26d98e25a6db65958c85"}, {file = "platformdirs-4.4.0.tar.gz", hash = "sha256:ca753cf4d81dc309bc67b0ea38fd15dc97bc30ce419a7f58d13eb3bf14c4febf"}, @@ -2841,6 +2977,7 @@ version = "1.6.0" description = "plugin and hook calling mechanisms for python" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746"}, {file = "pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3"}, @@ -2856,6 +2993,7 @@ version = "3.2.0" description = "Wraps the portalocker recipe for easy usage" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "portalocker-3.2.0-py3-none-any.whl", hash = "sha256:3cdc5f565312224bc570c49337bd21428bba0ef363bbcf58b9ef4a9f11779968"}, {file = "portalocker-3.2.0.tar.gz", hash = "sha256:1f3002956a54a8c3730586c5c77bf18fae4149e07eaf1c29fc3faf4d5a3f89ac"}, @@ -2875,6 +3013,7 @@ version = "3.25.0" description = "Integrate PostHog into any python application." optional = false python-versions = "*" +groups = ["test"] files = [ {file = "posthog-3.25.0-py2.py3-none-any.whl", hash = "sha256:85db78c13d1ecb11aed06fad53759c4e8fb3633442c2f3d0336bc0ce8a585d30"}, {file = "posthog-3.25.0.tar.gz", hash = "sha256:9168f3e7a0a5571b6b1065c41b3c171fbc68bfe72c3ac0bfd6e3d2fcdb7df2ca"}, @@ -2900,6 +3039,7 @@ version = "0.22.1" description = "Python client for the Prometheus monitoring system." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "prometheus_client-0.22.1-py3-none-any.whl", hash = "sha256:cca895342e308174341b2cbf99a56bef291fbc0ef7b9e5412a0f26d653ba7094"}, {file = "prometheus_client-0.22.1.tar.gz", hash = "sha256:190f1331e783cf21eb60bca559354e0a4d4378facecf78f5428c39b675d20d28"}, @@ -2914,6 +3054,7 @@ version = "3.0.52" description = "Library for building powerful interactive command lines in Python" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "prompt_toolkit-3.0.52-py3-none-any.whl", hash = "sha256:9aac639a3bbd33284347de5ad8d68ecc044b91a762dc39b7c21095fcd6a19955"}, {file = "prompt_toolkit-3.0.52.tar.gz", hash = "sha256:28cde192929c8e7321de85de1ddbe736f1375148b02f2e17edd840042b1be855"}, @@ -2928,6 +3069,7 @@ version = "0.3.2" description = "Accelerated property cache" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "propcache-0.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:22d9962a358aedbb7a2e36187ff273adeaab9743373a272976d2e348d08c7770"}, {file = "propcache-0.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0d0fda578d1dc3f77b6b5a5dce3b9ad69a8250a891760a548df850a5e8da87f3"}, @@ -3035,6 +3177,7 @@ version = "6.32.1" description = "" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "protobuf-6.32.1-cp310-abi3-win32.whl", hash = "sha256:a8a32a84bc9f2aad712041b8b366190f71dde248926da517bde9e832e4412085"}, {file = "protobuf-6.32.1-cp310-abi3-win_amd64.whl", hash = "sha256:b00a7d8c25fa471f16bc8153d0e53d6c9e827f0953f3c09aaa4331c718cae5e1"}, @@ -3053,6 +3196,7 @@ version = "7.0.0" description = "Cross-platform lib for process and system monitoring in Python. NOTE: the syntax of this script MUST be kept compatible with Python 2.7." optional = false python-versions = ">=3.6" +groups = ["dev"] files = [ {file = "psutil-7.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:101d71dc322e3cffd7cea0650b09b3d08b8e7c4109dd6809fe452dfd00e58b25"}, {file = "psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:39db632f6bb862eeccf56660871433e111b6ea58f2caea825571951d4b6aa3da"}, @@ -3076,6 +3220,8 @@ version = "0.7.0" description = "Run a subprocess in a pseudo terminal" optional = false python-versions = "*" +groups = ["dev"] +markers = "os_name != \"nt\" or sys_platform != \"win32\" and sys_platform != \"emscripten\"" files = [ {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"}, {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"}, @@ -3087,6 +3233,7 @@ version = "0.2.3" description = "Safely evaluate AST nodes without side effects" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0"}, {file = "pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42"}, @@ -3101,6 +3248,7 @@ version = "0.6.1" description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"}, {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"}, @@ -3112,6 +3260,7 @@ version = "0.4.2" description = "A collection of ASN.1-based protocols modules" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "pyasn1_modules-0.4.2-py3-none-any.whl", hash = "sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a"}, {file = "pyasn1_modules-0.4.2.tar.gz", hash = "sha256:677091de870a80aae844b1ca6134f54652fa2c8c5a52aa396440ac3106e941e6"}, @@ -3126,6 +3275,8 @@ version = "2.23" description = "C parser in Python" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "implementation_name != \"PyPy\"" files = [ {file = "pycparser-2.23-py3-none-any.whl", hash = "sha256:e5c6e8d3fbad53479cab09ac03729e0a9faf2bee3db8208a550daf5af81a5934"}, {file = "pycparser-2.23.tar.gz", hash = "sha256:78816d4f24add8f10a06d6f05b4d424ad9e96cfebf68a4ddc99c65c0720d00c2"}, @@ -3137,6 +3288,7 @@ version = "2.11.9" description = "Data validation using Python type hints" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "pydantic-2.11.9-py3-none-any.whl", hash = "sha256:c42dd626f5cfc1c6950ce6205ea58c93efa406da65f479dcb4029d5934857da2"}, {file = "pydantic-2.11.9.tar.gz", hash = "sha256:6b8ffda597a14812a7975c90b82a8a2e777d9257aba3453f973acd3c032a18e2"}, @@ -3150,7 +3302,7 @@ typing-inspection = ">=0.4.0" [package.extras] email = ["email-validator (>=2.0.0)"] -timezone = ["tzdata"] +timezone = ["tzdata ; python_version >= \"3.9\" and platform_system == \"Windows\""] [[package]] name = "pydantic-core" @@ -3158,6 +3310,7 @@ version = "2.33.2" description = "Core functionality for Pydantic validation and serialization" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "pydantic_core-2.33.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2b3d326aaef0c0399d9afffeb6367d5e26ddc24d351dbc9c636840ac355dc5d8"}, {file = "pydantic_core-2.33.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0e5b2671f05ba48b94cb90ce55d8bdcaaedb8ba00cc5359f6810fc918713983d"}, @@ -3269,6 +3422,7 @@ version = "2.19.2" description = "Pygments is a syntax highlighting package written in Python." optional = false python-versions = ">=3.8" +groups = ["main", "dev", "test"] files = [ {file = "pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b"}, {file = "pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887"}, @@ -3283,6 +3437,7 @@ version = "2.10.1" description = "JSON Web Token implementation in Python" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "PyJWT-2.10.1-py3-none-any.whl", hash = "sha256:dcdd193e30abefd5debf142f9adfcdd2b58004e644f25406ffaebd50bd98dacb"}, {file = "pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953"}, @@ -3294,12 +3449,28 @@ dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pyte docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"] tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"] +[[package]] +name = "pyparsing" +version = "3.2.5" +description = "pyparsing - Classes and methods to define and execute parsing grammars" +optional = false +python-versions = ">=3.9" +groups = ["main"] +files = [ + {file = "pyparsing-3.2.5-py3-none-any.whl", hash = "sha256:e38a4f02064cf41fe6593d328d0512495ad1f3d8a91c4f73fc401b3079a59a5e"}, + {file = "pyparsing-3.2.5.tar.gz", hash = "sha256:2df8d5b7b2802ef88e8d016a2eb9c7aeaa923529cd251ed0fe4608275d4105b6"}, +] + +[package.extras] +diagrams = ["jinja2", "railroad-diagrams"] + [[package]] name = "pypdf" version = "5.9.0" description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files" optional = false python-versions = ">=3.8" +groups = ["main"] files = [ {file = "pypdf-5.9.0-py3-none-any.whl", hash = "sha256:be10a4c54202f46d9daceaa8788be07aa8cd5ea8c25c529c50dd509206382c35"}, {file = "pypdf-5.9.0.tar.gz", hash = "sha256:30f67a614d558e495e1fbb157ba58c1de91ffc1718f5e0dfeb82a029233890a1"}, @@ -3322,6 +3493,7 @@ version = "8.4.2" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest-8.4.2-py3-none-any.whl", hash = "sha256:872f880de3fc3a5bdc88a11b39c9710c3497a547cfa9320bc3c5e62fbf272e79"}, {file = "pytest-8.4.2.tar.gz", hash = "sha256:86c0d0b93306b961d58d62a4db4879f27fe25513d4b969df351abdddb3c30e01"}, @@ -3345,6 +3517,7 @@ version = "1.2.0" description = "Pytest support for asyncio" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest_asyncio-1.2.0-py3-none-any.whl", hash = "sha256:8e17ae5e46d8e7efe51ab6494dd2010f4ca8dae51652aa3c8d55acf50bfb2e99"}, {file = "pytest_asyncio-1.2.0.tar.gz", hash = "sha256:c609a64a2a8768462d0c99811ddb8bd2583c33fd33cf7f21af1c142e824ffb57"}, @@ -3365,6 +3538,7 @@ version = "0.9.4" description = "pytest plugin for repeating tests" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest_repeat-0.9.4-py3-none-any.whl", hash = "sha256:c1738b4e412a6f3b3b9e0b8b29fcd7a423e50f87381ad9307ef6f5a8601139f3"}, {file = "pytest_repeat-0.9.4.tar.gz", hash = "sha256:d92ac14dfaa6ffcfe6917e5d16f0c9bc82380c135b03c2a5f412d2637f224485"}, @@ -3379,6 +3553,7 @@ version = "12.0" description = "pytest plugin to re-run tests to eliminate flaky failures" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "pytest-rerunfailures-12.0.tar.gz", hash = "sha256:784f462fa87fe9bdf781d0027d856b47a4bfe6c12af108f6bd887057a917b48e"}, {file = "pytest_rerunfailures-12.0-py3-none-any.whl", hash = "sha256:9a1afd04e21b8177faf08a9bbbf44de7a0fe3fc29f8ddbe83b9684bd5f8f92a9"}, @@ -3394,6 +3569,7 @@ version = "3.8.0" description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "pytest_xdist-3.8.0-py3-none-any.whl", hash = "sha256:202ca578cfeb7370784a8c33d6d05bc6e13b4f25b5053c30a152269fd10f0b88"}, {file = "pytest_xdist-3.8.0.tar.gz", hash = "sha256:7e578125ec9bc6050861aa93f2d59f1d8d085595d6551c2c90b6f4fad8d3a9f1"}, @@ -3414,6 +3590,7 @@ version = "2.9.0.post0" description = "Extensions to the standard Python datetime module" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main", "dev", "test"] files = [ {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, @@ -3428,6 +3605,7 @@ version = "1.1.1" description = "Read key-value pairs from a .env file and set them as environment variables" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "python_dotenv-1.1.1-py3-none-any.whl", hash = "sha256:31f23644fe2602f88ff55e1f5c79ba497e01224ee7737937930c448e4d0e24dc"}, {file = "python_dotenv-1.1.1.tar.gz", hash = "sha256:a8a6399716257f45be6a007360200409fce5cda2661e3dec71d23dc15f6189ab"}, @@ -3442,13 +3620,14 @@ version = "3.3.0" description = "JSON Log Formatter for the Python Logging Package" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "python_json_logger-3.3.0-py3-none-any.whl", hash = "sha256:dd980fae8cffb24c13caf6e158d3d61c0d6d22342f932cb6e9deedab3d35eec7"}, {file = "python_json_logger-3.3.0.tar.gz", hash = "sha256:12b7e74b17775e7d565129296105bbe3910842d9d0eb083fc83a6a617aa8df84"}, ] [package.extras] -dev = ["backports.zoneinfo", "black", "build", "freezegun", "mdx_truly_sane_lists", "mike", "mkdocs", "mkdocs-awesome-pages-plugin", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-material (>=8.5)", "mkdocstrings[python]", "msgspec", "mypy", "orjson", "pylint", "pytest", "tzdata", "validate-pyproject[all]"] +dev = ["backports.zoneinfo ; python_version < \"3.9\"", "black", "build", "freezegun", "mdx_truly_sane_lists", "mike", "mkdocs", "mkdocs-awesome-pages-plugin", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-material (>=8.5)", "mkdocstrings[python]", "msgspec ; implementation_name != \"pypy\"", "mypy", "orjson ; implementation_name != \"pypy\"", "pylint", "pytest", "tzdata", "validate-pyproject[all]"] [[package]] name = "pytz" @@ -3456,6 +3635,7 @@ version = "2025.2" description = "World timezone definitions, modern and historical" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00"}, {file = "pytz-2025.2.tar.gz", hash = "sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3"}, @@ -3467,6 +3647,7 @@ version = "311" description = "Python for Window Extensions" optional = false python-versions = "*" +groups = ["dev", "test"] files = [ {file = "pywin32-311-cp310-cp310-win32.whl", hash = "sha256:d03ff496d2a0cd4a5893504789d4a15399133fe82517455e78bad62efbb7f0a3"}, {file = "pywin32-311-cp310-cp310-win_amd64.whl", hash = "sha256:797c2772017851984b97180b0bebe4b620bb86328e8a884bb626156295a63b3b"}, @@ -3489,6 +3670,7 @@ files = [ {file = "pywin32-311-cp39-cp39-win_amd64.whl", hash = "sha256:e0c4cfb0621281fe40387df582097fd796e80430597cb9944f0ae70447bacd91"}, {file = "pywin32-311-cp39-cp39-win_arm64.whl", hash = "sha256:62ea666235135fee79bb154e695f3ff67370afefd71bd7fea7512fc70ef31e3d"}, ] +markers = {dev = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\"", test = "platform_system == \"Windows\""} [[package]] name = "pywinpty" @@ -3496,6 +3678,8 @@ version = "3.0.0" description = "" optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "os_name == \"nt\"" files = [ {file = "pywinpty-3.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:327b6034e0dc38352c1c99a7c0b3e54941b4e506a5f21acce63609cd2ab6cce2"}, {file = 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"sha256:507b6f430bdcf0ee48c0d30e734ea89ce5567fd7b8a0f0044a369c176aa44556"}, @@ -3678,16 +3864,42 @@ version = "2.2.1" description = "API rate limit decorator" optional = false python-versions = "*" +groups = ["main"] files = [ {file = "ratelimit-2.2.1.tar.gz", hash = "sha256:af8a9b64b821529aca09ebaf6d8d279100d766f19e90b5059ac6a718ca6dee42"}, ] +[[package]] +name = "rdflib" +version = "7.5.0" +description = "RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information." +optional = false +python-versions = ">=3.8.1" +groups = ["main"] +files = [ + {file = "rdflib-7.5.0-py3-none-any.whl", hash = "sha256:b011dfc40d0fc8a44252e906dcd8fc806a7859bc231be190c37e9568a31ac572"}, + {file = "rdflib-7.5.0.tar.gz", hash = "sha256:663083443908b1830e567350d72e74d9948b310f827966358d76eebdc92bf592"}, +] + +[package.dependencies] +isodate = {version = ">=0.7.2,<1.0.0", markers = "python_version < \"3.11\""} +pyparsing = ">=2.1.0,<4" + +[package.extras] 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"sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa"}, @@ -3723,6 +3936,7 @@ version = "2025.9.1" description = "Alternative regular expression module, to replace re." optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "regex-2025.9.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c5aa2a6a73bf218515484b36a0d20c6ad9dc63f6339ff6224147b0e2c095ee55"}, {file = "regex-2025.9.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:8c2ff5c01d5e47ad5fc9d31bcd61e78c2fa0068ed00cab86b7320214446da766"}, @@ -3819,6 +4033,7 @@ version = "2.32.5" description = "Python HTTP for Humans." optional = false python-versions = ">=3.9" +groups = ["main", "dev", "test"] files = [ {file = "requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6"}, {file = "requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf"}, @@ -3840,6 +4055,7 @@ version = "0.1.4" description = "A pure python RFC3339 validator" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +groups = ["dev"] files = [ {file = "rfc3339_validator-0.1.4-py2.py3-none-any.whl", hash = "sha256:24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa"}, {file = "rfc3339_validator-0.1.4.tar.gz", hash = "sha256:138a2abdf93304ad60530167e51d2dfb9549521a836871b88d7f4695d0022f6b"}, @@ -3854,6 +4070,7 @@ version = "0.1.1" description = "Pure python rfc3986 validator" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +groups = ["dev"] files = [ {file = "rfc3986_validator-0.1.1-py2.py3-none-any.whl", hash = "sha256:2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9"}, {file = "rfc3986_validator-0.1.1.tar.gz", hash = "sha256:3d44bde7921b3b9ec3ae4e3adca370438eccebc676456449b145d533b240d055"}, @@ -3865,6 +4082,7 @@ version = "1.1.0" description = "Helper functions to syntactically validate strings according to RFC 3987." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "rfc3987_syntax-1.1.0-py3-none-any.whl", hash = "sha256:6c3d97604e4c5ce9f714898e05401a0445a641cfa276432b0a648c80856f6a3f"}, {file = "rfc3987_syntax-1.1.0.tar.gz", hash = "sha256:717a62cbf33cffdd16dfa3a497d81ce48a660ea691b1ddd7be710c22f00b4a0d"}, @@ -3882,6 +4100,7 @@ version = "13.9.4" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false python-versions = ">=3.8.0" +groups = ["main", "test"] files = [ {file = "rich-13.9.4-py3-none-any.whl", hash = "sha256:6049d5e6ec054bf2779ab3358186963bac2ea89175919d699e378b99738c2a90"}, {file = "rich-13.9.4.tar.gz", hash = "sha256:439594978a49a09530cff7ebc4b5c7103ef57baf48d5ea3184f21d9a2befa098"}, @@ -3901,6 +4120,7 @@ version = "0.27.1" description = "Python bindings to Rust's persistent data structures (rpds)" optional = false python-versions = ">=3.9" +groups = ["main", "dev"] files = [ {file = "rpds_py-0.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:68afeec26d42ab3b47e541b272166a0b4400313946871cba3ed3a4fc0cab1cef"}, {file = "rpds_py-0.27.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:74e5b2f7bb6fa38b1b10546d27acbacf2a022a8b5543efb06cfebc72a59c85be"}, @@ -4065,6 +4285,7 @@ version = "4.9.1" description = "Pure-Python RSA implementation" optional = false python-versions = "<4,>=3.6" +groups = ["test"] files = [ {file = "rsa-4.9.1-py3-none-any.whl", hash = "sha256:68635866661c6836b8d39430f97a996acbd61bfa49406748ea243539fe239762"}, {file = "rsa-4.9.1.tar.gz", hash = "sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75"}, @@ -4079,15 +4300,16 @@ version = "1.8.3" description = "Send file to trash natively under Mac OS X, Windows and Linux" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +groups = ["dev"] files = [ {file = "Send2Trash-1.8.3-py3-none-any.whl", hash = "sha256:0c31227e0bd08961c7665474a3d1ef7193929fedda4233843689baa056be46c9"}, {file = "Send2Trash-1.8.3.tar.gz", hash = "sha256:b18e7a3966d99871aefeb00cfbcfdced55ce4871194810fc71f4aa484b953abf"}, ] [package.extras] -nativelib = ["pyobjc-framework-Cocoa", "pywin32"] -objc = ["pyobjc-framework-Cocoa"] -win32 = ["pywin32"] +nativelib = ["pyobjc-framework-Cocoa ; sys_platform == \"darwin\"", "pywin32 ; sys_platform == \"win32\""] +objc = ["pyobjc-framework-Cocoa ; sys_platform == \"darwin\""] +win32 = ["pywin32 ; sys_platform == \"win32\""] [[package]] name = "sentry-sdk" @@ -4095,6 +4317,7 @@ version = "2.38.0" description = "Python client for Sentry (https://sentry.io)" optional = false python-versions = ">=3.6" +groups = ["test"] files = [ {file = "sentry_sdk-2.38.0-py2.py3-none-any.whl", hash = "sha256:2324aea8573a3fa1576df7fb4d65c4eb8d9929c8fa5939647397a07179eef8d0"}, {file = "sentry_sdk-2.38.0.tar.gz", hash = "sha256:792d2af45e167e2f8a3347143f525b9b6bac6f058fb2014720b40b84ccbeb985"}, @@ -4152,19 +4375,20 @@ version = "80.9.0" description = "Easily download, build, install, upgrade, and uninstall Python packages" optional = false python-versions = ">=3.9" +groups = ["dev", "test"] files = [ {file = "setuptools-80.9.0-py3-none-any.whl", hash = "sha256:062d34222ad13e0cc312a4c02d73f059e86a4acbfbdea8f8f76b28c99f306922"}, {file = "setuptools-80.9.0.tar.gz", hash = "sha256:f36b47402ecde768dbfafc46e8e4207b4360c654f1f3bb84475f0a28628fb19c"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.8.0)"] -core = ["importlib_metadata (>=6)", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\"", "ruff (>=0.8.0) ; sys_platform != \"cygwin\""] +core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"] enabler = ["pytest-enabler (>=2.2)"] -test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] -type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.14.*)", "pytest-mypy"] +test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21) ; python_version >= \"3.9\" and sys_platform != \"cygwin\"", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf ; sys_platform != \"cygwin\"", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] +type = ["importlib_metadata (>=7.0.2) ; python_version < \"3.10\"", "jaraco.develop (>=7.21) ; sys_platform != \"cygwin\"", "mypy (==1.14.*)", "pytest-mypy"] [[package]] name = "shellingham" @@ -4172,6 +4396,7 @@ version = "1.5.4" description = "Tool to Detect Surrounding Shell" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "shellingham-1.5.4-py2.py3-none-any.whl", hash = "sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686"}, {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"}, @@ -4183,6 +4408,7 @@ version = "1.17.0" description = "Python 2 and 3 compatibility utilities" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main", "dev", "test"] files = [ {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, @@ -4194,6 +4420,7 @@ version = "1.3.1" description = "Sniff out which async library your code is running under" optional = false python-versions = ">=3.7" +groups = ["main", "dev", "test"] files = [ {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"}, {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"}, @@ -4205,6 +4432,7 @@ version = "3.0.1" description = "This package provides 32 stemmers for 30 languages generated from Snowball algorithms." optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*" +groups = ["dev"] files = [ {file = "snowballstemmer-3.0.1-py3-none-any.whl", hash = "sha256:6cd7b3897da8d6c9ffb968a6781fa6532dce9c3618a4b127d920dab764a19064"}, {file = "snowballstemmer-3.0.1.tar.gz", hash = "sha256:6d5eeeec8e9f84d4d56b847692bacf79bc2c8e90c7f80ca4444ff8b6f2e52895"}, @@ -4216,6 +4444,7 @@ version = "2.8" description = "A modern CSS selector implementation for Beautiful Soup." optional = false python-versions = ">=3.9" +groups = ["main", "dev"] files = [ {file = "soupsieve-2.8-py3-none-any.whl", hash = "sha256:0cc76456a30e20f5d7f2e14a98a4ae2ee4e5abdc7c5ea0aafe795f344bc7984c"}, {file = "soupsieve-2.8.tar.gz", hash = "sha256:e2dd4a40a628cb5f28f6d4b0db8800b8f581b65bb380b97de22ba5ca8d72572f"}, @@ -4227,6 +4456,7 @@ version = "7.4.7" description = "Python documentation generator" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinx-7.4.7-py3-none-any.whl", hash = "sha256:c2419e2135d11f1951cd994d6eb18a1835bd8fdd8429f9ca375dc1f3281bd239"}, {file = "sphinx-7.4.7.tar.gz", hash = "sha256:242f92a7ea7e6c5b406fdc2615413890ba9f699114a9c09192d7dfead2ee9cfe"}, @@ -4262,6 +4492,7 @@ version = "2.0.0" description = "Read the Docs theme for Sphinx" optional = false python-versions = ">=3.6" +groups = ["dev"] files = [ {file = "sphinx_rtd_theme-2.0.0-py2.py3-none-any.whl", hash = "sha256:ec93d0856dc280cf3aee9a4c9807c60e027c7f7b461b77aeffed682e68f0e586"}, {file = "sphinx_rtd_theme-2.0.0.tar.gz", hash = "sha256:bd5d7b80622406762073a04ef8fadc5f9151261563d47027de09910ce03afe6b"}, @@ -4281,6 +4512,7 @@ version = "2.0.0" description = "sphinxcontrib-applehelp is a Sphinx extension which outputs Apple help books" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinxcontrib_applehelp-2.0.0-py3-none-any.whl", hash = "sha256:4cd3f0ec4ac5dd9c17ec65e9ab272c9b867ea77425228e68ecf08d6b28ddbdb5"}, {file = "sphinxcontrib_applehelp-2.0.0.tar.gz", hash = "sha256:2f29ef331735ce958efa4734873f084941970894c6090408b079c61b2e1c06d1"}, @@ -4297,6 +4529,7 @@ version = "2.0.0" description = "sphinxcontrib-devhelp is a sphinx extension which outputs Devhelp documents" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinxcontrib_devhelp-2.0.0-py3-none-any.whl", hash = "sha256:aefb8b83854e4b0998877524d1029fd3e6879210422ee3780459e28a1f03a8a2"}, {file = "sphinxcontrib_devhelp-2.0.0.tar.gz", hash = "sha256:411f5d96d445d1d73bb5d52133377b4248ec79db5c793ce7dbe59e074b4dd1ad"}, @@ -4313,6 +4546,7 @@ version = "2.1.0" description = "sphinxcontrib-htmlhelp is a sphinx extension which renders HTML help files" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinxcontrib_htmlhelp-2.1.0-py3-none-any.whl", hash = "sha256:166759820b47002d22914d64a075ce08f4c46818e17cfc9470a9786b759b19f8"}, {file = "sphinxcontrib_htmlhelp-2.1.0.tar.gz", hash = "sha256:c9e2916ace8aad64cc13a0d233ee22317f2b9025b9cf3295249fa985cc7082e9"}, @@ -4329,6 +4563,7 @@ version = "4.1" description = "Extension to include jQuery on newer Sphinx releases" optional = false python-versions = ">=2.7" +groups = ["dev"] files = [ {file = "sphinxcontrib-jquery-4.1.tar.gz", hash = "sha256:1620739f04e36a2c779f1a131a2dfd49b2fd07351bf1968ced074365933abc7a"}, {file = "sphinxcontrib_jquery-4.1-py2.py3-none-any.whl", hash = "sha256:f936030d7d0147dd026a4f2b5a57343d233f1fc7b363f68b3d4f1cb0993878ae"}, @@ -4343,6 +4578,7 @@ version = "1.0.1" description = "A sphinx extension which renders display math in HTML via JavaScript" optional = false python-versions = ">=3.5" +groups = ["dev"] files = [ {file = "sphinxcontrib-jsmath-1.0.1.tar.gz", hash = "sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8"}, {file = "sphinxcontrib_jsmath-1.0.1-py2.py3-none-any.whl", hash = "sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178"}, @@ -4357,6 +4593,7 @@ version = "2.0.0" description = "sphinxcontrib-qthelp is a sphinx extension which outputs QtHelp documents" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinxcontrib_qthelp-2.0.0-py3-none-any.whl", hash = "sha256:b18a828cdba941ccd6ee8445dbe72ffa3ef8cbe7505d8cd1fa0d42d3f2d5f3eb"}, {file = "sphinxcontrib_qthelp-2.0.0.tar.gz", hash = "sha256:4fe7d0ac8fc171045be623aba3e2a8f613f8682731f9153bb2e40ece16b9bbab"}, @@ -4373,6 +4610,7 @@ version = "2.0.0" description = "sphinxcontrib-serializinghtml is a sphinx extension which outputs \"serialized\" HTML files (json and pickle)" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl", hash = "sha256:6e2cb0eef194e10c27ec0023bfeb25badbbb5868244cf5bc5bdc04e4464bf331"}, {file = "sphinxcontrib_serializinghtml-2.0.0.tar.gz", hash = "sha256:e9d912827f872c029017a53f0ef2180b327c3f7fd23c87229f7a8e8b70031d4d"}, @@ -4389,6 +4627,7 @@ version = "0.6.3" description = "Extract data from python stack frames and tracebacks for informative displays" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"}, {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"}, @@ -4408,6 +4647,7 @@ version = "0.9.0" description = "Pretty-print tabular data" optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"}, {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"}, @@ -4422,6 +4662,7 @@ version = "9.0.0" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"}, {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"}, @@ -4437,6 +4678,7 @@ version = "0.18.1" description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "terminado-0.18.1-py3-none-any.whl", hash = "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0"}, {file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"}, @@ -4458,6 +4700,7 @@ version = "0.11.0" description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "tiktoken-0.11.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:8a9b517d6331d7103f8bef29ef93b3cca95fa766e293147fe7bacddf310d5917"}, {file = "tiktoken-0.11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b4ddb1849e6bf0afa6cc1c5d809fb980ca240a5fffe585a04e119519758788c0"}, @@ -4505,6 +4748,7 @@ version = "1.4.0" description = "A tiny CSS parser" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "tinycss2-1.4.0-py3-none-any.whl", hash = "sha256:3a49cf47b7675da0b15d0c6e1df8df4ebd96e9394bb905a5775adb0d884c5289"}, {file = "tinycss2-1.4.0.tar.gz", hash = "sha256:10c0972f6fc0fbee87c3edb76549357415e94548c1ae10ebccdea16fb404a9b7"}, @@ -4523,6 +4767,7 @@ version = "0.22.0" description = "" optional = false python-versions = ">=3.9" +groups = ["main"] files = [ {file = "tokenizers-0.22.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:eaa9620122a3fb99b943f864af95ed14c8dfc0f47afa3b404ac8c16b3f2bb484"}, {file = "tokenizers-0.22.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:71784b9ab5bf0ff3075bceeb198149d2c5e068549c0d18fe32d06ba0deb63f79"}, @@ -4555,6 +4800,8 @@ version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" +groups = ["dev", "test"] +markers = "python_version < \"3.11\"" files = [ {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, @@ -4596,6 +4843,7 @@ version = "6.5.2" description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "tornado-6.5.2-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:2436822940d37cde62771cff8774f4f00b3c8024fe482e16ca8387b8a2724db6"}, {file = "tornado-6.5.2-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:583a52c7aa94ee046854ba81d9ebb6c81ec0fd30386d96f7640c96dad45a03ef"}, @@ -4617,6 +4865,7 @@ version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" +groups = ["main", "test"] files = [ {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, @@ -4638,6 +4887,7 @@ version = "5.14.3" description = "Traitlets Python configuration system" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"}, {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"}, @@ -4653,6 +4903,7 @@ version = "0.17.4" description = "Typer, build great CLIs. Easy to code. Based on Python type hints." optional = false python-versions = ">=3.7" +groups = ["test"] files = [ {file = "typer-0.17.4-py3-none-any.whl", hash = "sha256:015534a6edaa450e7007eba705d5c18c3349dcea50a6ad79a5ed530967575824"}, {file = "typer-0.17.4.tar.gz", hash = "sha256:b77dc07d849312fd2bb5e7f20a7af8985c7ec360c45b051ed5412f64d8dc1580"}, @@ -4670,6 +4921,7 @@ version = "2.9.0.20250822" description = "Typing stubs for python-dateutil" optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "types_python_dateutil-2.9.0.20250822-py3-none-any.whl", hash = "sha256:849d52b737e10a6dc6621d2bd7940ec7c65fcb69e6aa2882acf4e56b2b508ddc"}, {file = "types_python_dateutil-2.9.0.20250822.tar.gz", hash = "sha256:84c92c34bd8e68b117bff742bc00b692a1e8531262d4507b33afcc9f7716cd53"}, @@ -4681,6 +4933,7 @@ version = "4.15.0" description = "Backported and Experimental Type Hints for Python 3.9+" optional = false python-versions = ">=3.9" +groups = ["main", "dev", "test"] files = [ {file = "typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548"}, {file = "typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466"}, @@ -4692,6 +4945,7 @@ version = "0.4.1" description = "Runtime typing introspection tools" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51"}, {file = "typing_inspection-0.4.1.tar.gz", hash = "sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28"}, @@ -4706,6 +4960,7 @@ version = "2025.2" description = "Provider of IANA time zone data" optional = false python-versions = ">=2" +groups = ["dev"] files = [ {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"}, {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, @@ -4717,6 +4972,7 @@ version = "1.3.0" description = "RFC 6570 URI Template Processor" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"}, {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"}, @@ -4731,13 +4987,14 @@ version = "2.5.0" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" +groups = ["main", "dev", "test"] files = [ {file = "urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc"}, {file = "urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760"}, ] [package.extras] -brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"] +brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""] h2 = ["h2 (>=4,<5)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] zstd = ["zstandard (>=0.18.0)"] @@ -4748,6 +5005,7 @@ version = "0.2.13" description = "Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, @@ -4759,6 +5017,7 @@ version = "24.11.1" description = "A library for working with the color formats defined by HTML and CSS." optional = false python-versions = ">=3.9" +groups = ["dev"] files = [ {file = "webcolors-24.11.1-py3-none-any.whl", hash = "sha256:515291393b4cdf0eb19c155749a096f779f7d909f7cceea072791cb9095b92e9"}, {file = "webcolors-24.11.1.tar.gz", hash = "sha256:ecb3d768f32202af770477b8b65f318fa4f566c22948673a977b00d589dd80f6"}, @@ -4770,6 +5029,7 @@ version = "0.5.1" description = "Character encoding aliases for legacy web content" optional = false python-versions = "*" +groups = ["dev"] files = [ {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"}, {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"}, @@ -4781,6 +5041,7 @@ version = "1.8.0" description = "WebSocket client for Python with low level API options" optional = false python-versions = ">=3.8" +groups = ["dev"] files = [ {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"}, {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"}, @@ -4797,6 +5058,7 @@ version = "15.0.1" description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)" optional = false python-versions = ">=3.9" +groups = ["test"] files = [ {file = "websockets-15.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d63efaa0cd96cf0c5fe4d581521d9fa87744540d4bc999ae6e08595a1014b45b"}, {file = "websockets-15.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ac60e3b188ec7574cb761b08d50fcedf9d77f1530352db4eef1707fe9dee7205"}, @@ -4875,6 +5137,7 @@ version = "0.45.1" description = "A built-package format for Python" optional = false python-versions = ">=3.8" +groups = ["test"] files = [ {file = "wheel-0.45.1-py3-none-any.whl", hash = "sha256:708e7481cc80179af0e556bbf0cc00b8444c7321e2700b8d8580231d13017248"}, {file = "wheel-0.45.1.tar.gz", hash = "sha256:661e1abd9198507b1409a20c02106d9670b2576e916d58f520316666abca6729"}, @@ -4889,6 +5152,7 @@ version = "4.0.14" description = "Jupyter interactive widgets for Jupyter Notebook" optional = false python-versions = ">=3.7" +groups = ["dev"] files = [ {file = "widgetsnbextension-4.0.14-py3-none-any.whl", hash = "sha256:4875a9eaf72fbf5079dc372a51a9f268fc38d46f767cbf85c43a36da5cb9b575"}, {file = "widgetsnbextension-4.0.14.tar.gz", hash = "sha256:a3629b04e3edb893212df862038c7232f62973373869db5084aed739b437b5af"}, @@ -4900,6 +5164,7 @@ version = "1.20.1" description = "Yet another URL library" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "yarl-1.20.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6032e6da6abd41e4acda34d75a816012717000fa6839f37124a47fcefc49bec4"}, {file = "yarl-1.20.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2c7b34d804b8cf9b214f05015c4fee2ebe7ed05cf581e7192c06555c71f4446a"}, @@ -5018,13 +5283,14 @@ version = "3.23.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" +groups = ["main", "test"] files = [ {file = "zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e"}, {file = "zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] @@ -5032,6 +5298,6 @@ test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_it type = ["pytest-mypy"] [metadata] -lock-version = "2.0" +lock-version = "2.1" python-versions = "^3.10.0, <3.14" -content-hash = "b2e17ad632017816fa8be30d8a4116ad3078868130dfc04b77862aab3cfb198e" +content-hash = "c40393bd66a0e818bd77c634e05720d0088c604d5ffb26472cfe43b453f84023" diff --git a/pyproject.toml b/pyproject.toml index be3dd689..07b2091c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,7 @@ python-dotenv = "^1.0.1" fix-busted-json = "^0.0.18" rich = "^13.9.4" litellm = "^1.73.1" +rdflib = "^7.0.0" [tool.poetry.extras] # All optional extras removed - litellm handles all providers From b952282a1f36086964e7f1304b8cbd403c46ff02 Mon Sep 17 00:00:00 2001 From: Dianjan Date: Sun, 14 Dec 2025 18:40:25 +0530 Subject: [PATCH 107/136] Add TTLLoader to import TTL files to improve GraphRAG-SDK --- examples/sports/demo-sports.ipynb | 292 +++++++++++++++++------------- 1 file changed, 163 insertions(+), 129 deletions(-) diff --git a/examples/sports/demo-sports.ipynb b/examples/sports/demo-sports.ipynb index 9894600f..f1575117 100644 --- a/examples/sports/demo-sports.ipynb +++ b/examples/sports/demo-sports.ipynb @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 18, "id": "d4264f31", "metadata": {}, "outputs": [ @@ -44,6 +44,10 @@ "from graphrag_sdk import Ontology\n", "import json\n", "\n", + "from dotenv import load_dotenv\n", + "# Load environment variables\n", + "load_dotenv()\n", + "\n", "# Get the path to the sports.ttl file\n", "ttl_file_path = os.path.join(Path(os.getcwd()).parent.parent, \"examples\", \"data/ttl\", \"sports.ttl\")\n", "print(f\"TTL file path: {ttl_file_path}\")\n", @@ -60,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "0a6fd10f", "metadata": {}, "outputs": [ @@ -69,7 +73,7 @@ "output_type": "stream", "text": [ "Extracting ontology from sports.ttl...\n", - "✓ Successfully extracted ontology!\n", + " Successfully extracted ontology!\n", " - Entities: 19\n", " - Relations: 2\n" ] @@ -87,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 20, "id": "078f3221", "metadata": {}, "outputs": [ @@ -96,25 +100,25 @@ "output_type": "stream", "text": [ "Entities:\n", - "\f- (:Equipments {})\n", + "\f- (:Workouts {})\n", + "- (:LowerBody {})\n", + "- (:Sport {})\n", + "- (:FocusedAreas {})\n", + "- (:Flexibility {})\n", + "- (:Badminton {})\n", + "- (:Agility {})\n", + "- (:Equipments {})\n", "- (:SportsPerson {})\n", "- (:MusclePower {})\n", - "- (:Football {})\n", - "- (:Agility {})\n", - "- (:Flexibility {})\n", + "- (:Cricket {})\n", "- (:Endurance {})\n", + "- (:UpperBody {})\n", "- (:Core {})\n", "- (:Functional {})\n", - "- (:FocusedAreas {})\n", - "- (:Workouts {})\n", - "- (:Cricket {})\n", - "- (:Badmintion {})\n", - "- (:Balance {})\n", - "- (:UpperBody {})\n", - "- (:LowerBody {})\n", + "- (:Football {})\n", "- (:Speed {})\n", - "- (:Sport {})\n", "- (:Tennis {})\n", + "- (:Balance {})\n", "\n", "Edges:\n", "\f- (:Workouts)-[:PARTOF {}]->(:FocusedAreas)\n", @@ -138,7 +142,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 21, "id": "3d308940", "metadata": {}, "outputs": [ @@ -150,80 +154,80 @@ "ENTITIES (Classes)\n", "================================================================================\n", "\n", - " Equipments\n", - " Description: Tools and gear used in sports activities\n", - " No attributes defined\n", - "\n", - " SportsPerson\n", - " Description: An individual who participates in sports\n", + " Workouts\n", + " Description: Training exercises and routines for athletic development\n", " No attributes defined\n", "\n", - " MusclePower\n", - " Description: Combination of strength and speed in muscle contraction\n", + " LowerBody\n", + " Description: Exercises targeting legs, glutes, and hips\n", " No attributes defined\n", "\n", - " Football\n", - " Description: Team sport played with a spherical ball\n", + " Sport\n", + " Description: A physical activity or game with competitive elements\n", " No attributes defined\n", "\n", - " Agility\n", - " Description: Ability to move quickly and change direction effectively\n", + " FocusedAreas\n", + " Description: Specific physical attributes targeted by training\n", " No attributes defined\n", "\n", " Flexibility\n", " Description: Range of motion in joints and muscles\n", " No attributes defined\n", "\n", - " Endurance\n", - " Description: Ability to sustain prolonged physical effort\n", + " Badminton\n", + " Description: Racket sport using a shuttlecock\n", " No attributes defined\n", "\n", - " Core\n", - " Description: Exercises targeting abdominal and back muscles\n", + " Agility\n", + " Description: Ability to move quickly and change direction effectively\n", " No attributes defined\n", "\n", - " Functional\n", - " Description: Multi-joint exercises that mimic everyday movements\n", + " Equipments\n", + " Description: Tools and gear used in sports activities\n", " No attributes defined\n", "\n", - " FocusedAreas\n", - " Description: Specific physical attributes targeted by training\n", + " SportsPerson\n", + " Description: An individual who participates in sports\n", " No attributes defined\n", "\n", - " Workouts\n", - " Description: Training exercises and routines for athletic development\n", + " MusclePower\n", + " Description: Combination of strength and speed in muscle contraction\n", " No attributes defined\n", "\n", " Cricket\n", " Description: Bat-and-ball game played between two teams\n", " No attributes defined\n", "\n", - " Badmintion\n", - " Description: Racket sport using a shuttlecock\n", - " No attributes defined\n", - "\n", - " Balance\n", - " Description: Ability to maintain body equilibrium\n", + " Endurance\n", + " Description: Ability to sustain prolonged physical effort\n", " No attributes defined\n", "\n", " UpperBody\n", " Description: Exercises targeting chest, shoulders, arms, and back\n", " No attributes defined\n", "\n", - " LowerBody\n", - " Description: Exercises targeting legs, glutes, and hips\n", + " Core\n", + " Description: Exercises targeting abdominal and back muscles\n", " No attributes defined\n", "\n", - " Speed\n", - " Description: Rate of movement or action\n", + " Functional\n", + " Description: Multi-joint exercises that mimic everyday movements\n", " No attributes defined\n", "\n", - " Sport\n", - " Description: A physical activity or game with competitive elements\n", + " Football\n", + " Description: Team sport played with a spherical ball\n", + " No attributes defined\n", + "\n", + " Speed\n", + " Description: Rate of movement or action\n", " No attributes defined\n", "\n", " Tennis\n", " Description: Racket sport played individually or in pairs\n", + " No attributes defined\n", + "\n", + " Balance\n", + " Description: Ability to maintain body equilibrium\n", " No attributes defined\n" ] } @@ -257,7 +261,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 22, "id": "ead7c3a1", "metadata": {}, "outputs": [ @@ -302,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "64d8ee34", "metadata": {}, "outputs": [ @@ -317,19 +321,19 @@ "{\n", " \"entities\": [\n", " {\n", - " \"label\": \"Endurance\",\n", + " \"label\": \"Workouts\",\n", " \"attributes\": [],\n", - " \"description\": \"Ability to sustain prolonged physical effort\"\n", + " \"description\": \"Training exercises and routines for athletic development\"\n", " },\n", " {\n", - " \"label\": \"Core\",\n", + " \"label\": \"LowerBody\",\n", " \"attributes\": [],\n", - " \"description\": \"Exercises targeting abdominal and back muscles\"\n", + " \"description\": \"Exercises targeting legs, glutes, and hips\"\n", " },\n", " {\n", - " \"label\": \"Balance\",\n", + " \"label\": \"Sport\",\n", " \"attributes\": [],\n", - " \"description\": \"Ability to maintain body equilibrium\"\n", + " \"description\": \"A physical activity or game with competitive elements\"\n", " },\n", " {\n", " \"label\": \"FocusedAreas\",\n", @@ -337,19 +341,19 @@ " \"description\": \"Specific physical attributes targeted by training\"\n", " },\n", " {\n", - " \"label\": \"Tennis\",\n", + " \"label\": \"Flexibility\",\n", " \"attributes\": [],\n", - " \"description\": \"Racket sport played individually or in pairs\"\n", + " \"description\": \"Range of motion in joints and muscles\"\n", " },\n", " {\n", - " \"label\": \"Sport\",\n", + " \"label\": \"Badminton\",\n", " \"attributes\": [],\n", - " \"description\": \"A physical activity or game with competitive elements\"\n", + " \"description\": \"Racket sport using a shuttlecock\"\n", " },\n", " {\n", - " \"label\": \"Flexibility\",\n", + " \"label\": \"Agility\",\n", " \"attributes\": [],\n", - " \"description\": \"Range of motion in joints and muscles\"\n", + " \"description\": \"Ability to move quickly and change direction effectively\"\n", " },\n", " {\n", " \"label\": \"Equipments\",\n", @@ -357,86 +361,84 @@ " \"description\": \"Tools and gear used in sports activities\"\n", " },\n", " {\n", - " \"label\": \"Badmintion\",\n", + " \"label\": \"SportsPerson\",\n", " \"attributes\": [],\n", - " \"description\": \"Racket sport using a shuttlecock\"\n", + " \"description\": \"An individual who participates in sports\"\n", " },\n", " {\n", - " \"label\": \"Speed\",\n", + " \"label\": \"MusclePower\",\n", " \"attributes\": [],\n", - " \"description\": \"Rate of movement or action\"\n", + " \"description\": \"Combination of strength and speed in muscle contraction\"\n", " },\n", " {\n", - " \"label\": \"SportsPerson\",\n", + " \"label\": \"Cricket\",\n", " \"attributes\": [],\n", - " \"description\": \"An individual who participates in sports\"\n", + " \"description\": \"Bat-and-ball game played between two teams\"\n", " },\n", " {\n", - " \"label\": \"UpperBody\",\n", + " \"label\": \"Endurance\",\n", " \"attributes\": [],\n", - " \"description\": \"Exercises targeting chest, shoulders, arms, and back\"\n", + " \"description\": \"Ability to sustain prolonged physical effort\"\n", " },\n", " {\n", - " \"label\": \"Cricket\",\n", + " \"label\": \"UpperBody\",\n", " \"attributes\": [],\n", - " \"description\": \"Bat-and-ball game played between two teams\"\n", + " \"description\": \"Exercises targeting chest, shoulders, arms, and back\"\n", " },\n", " {\n", - " \"label\": \"Football\",\n", + " \"label\": \"Core\",\n", " \"attributes\": [],\n", - " \"description\": \"Team sport played with a spherical ball\"\n", + " \"description\": \"Exercises targeting abdominal and back muscles\"\n", " },\n", " {\n", - " \"label\": \"MusclePower\",\n", + " \"label\": \"Functional\",\n", " \"attributes\": [],\n", - " \"description\": \"Combination of strength and speed in muscle contraction\"\n", + " \"description\": \"Multi-joint exercises that mimic everyday movements\"\n", " },\n", " {\n", - " \"label\": \"LowerBody\",\n", + " \"label\": \"Football\",\n", " \"attributes\": [],\n", - " \"description\": \"Exercises targeting legs, glutes, and hips\"\n", + " \"description\": \"Team sport played with a spherical ball\"\n", " },\n", " {\n", - " \"label\": \"Workouts\",\n", + " \"label\": \"Speed\",\n", " \"attributes\": [],\n", - " \"description\": \"Training exercises and routines for athletic development\"\n", + " \"description\": \"Rate of movement or action\"\n", " },\n", " {\n", - " \"label\": \"Agility\",\n", + " \"label\": \"Tennis\",\n", " \"attributes\": [],\n", - " \"description\": \"Ability to move quickly and change direction effectively\"\n", + " \"description\": \"Racket sport played individually or in pairs\"\n", " },\n", " {\n", - " \"label\": \"Functional\",\n", + " \"label\": \"Balance\",\n", " \"attributes\": [],\n", - " \"description\": \"Multi-joint exercises that mimic everyday movements\"\n", + " \"description\": \"Ability to maintain body equilibrium\"\n", " }\n", " ],\n", " \"relations\": [\n", " {\n", - " \"label\": \"ASSOCIATEDTO\",\n", + " \"label\": \"PARTOF\",\n", " \"source\": {\n", - " \"label\": \"SportsPerson\"\n", + " \"label\": \"Workouts\"\n", " },\n", " \"target\": {\n", - " \"label\": \"Sport\"\n", + " \"label\": \"FocusedAreas\"\n", " },\n", " \"attributes\": []\n", " },\n", " {\n", - " \"label\": \"PARTOF\",\n", + " \"label\": \"ASSOCIATEDTO\",\n", " \"source\": {\n", - " \"label\": \"Workouts\"\n", + " \"label\": \"SportsPerson\"\n", " },\n", " \"target\": {\n", - " \"label\": \"FocusedAreas\"\n", + " \"label\": \"Sport\"\n", " },\n", " \"attributes\": []\n", " }\n", " ]\n", - "}\n", - "\n", - "✓ Ontology saved to sports_ontology.json\n" + "}\n" ] } ], @@ -467,7 +469,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 24, "id": "fa7c5ba4", "metadata": {}, "outputs": [ @@ -487,25 +489,25 @@ " Total Attributes: 0\n", "\n", " Entity List:\n", + " - Workouts (0 attributes)\n", + " - LowerBody (0 attributes)\n", + " - Sport (0 attributes)\n", + " - FocusedAreas (0 attributes)\n", + " - Flexibility (0 attributes)\n", + " - Badminton (0 attributes)\n", + " - Agility (0 attributes)\n", " - Equipments (0 attributes)\n", " - SportsPerson (0 attributes)\n", " - MusclePower (0 attributes)\n", - " - Football (0 attributes)\n", - " - Agility (0 attributes)\n", - " - Flexibility (0 attributes)\n", + " - Cricket (0 attributes)\n", " - Endurance (0 attributes)\n", + " - UpperBody (0 attributes)\n", " - Core (0 attributes)\n", " - Functional (0 attributes)\n", - " - FocusedAreas (0 attributes)\n", - " - Workouts (0 attributes)\n", - " - Cricket (0 attributes)\n", - " - Badmintion (0 attributes)\n", - " - Balance (0 attributes)\n", - " - UpperBody (0 attributes)\n", - " - LowerBody (0 attributes)\n", + " - Football (0 attributes)\n", " - Speed (0 attributes)\n", - " - Sport (0 attributes)\n", " - Tennis (0 attributes)\n", + " - Balance (0 attributes)\n", "\n", " Relation List:\n", " - (:Workouts) → PARTOF → (:FocusedAreas)\n", @@ -571,7 +573,8 @@ "falkor_host = \"\"\n", "falkor_port = None\n", "falkor_username = \"\"\n", - "falkor_password = \"\"" + "falkor_password = \"\"\n", + "\n" ] }, { @@ -579,47 +582,78 @@ "id": "beddd528", "metadata": {}, "source": [ - "## Step 8: Create Knowledge Graph and Upload Ontology\n", + "## Step 8: Create Knowledge Graph\n", "\n", - "Create a Knowledge Graph instance and upload the extracted ontology to FalkorDB." + "Two ways to create a Knowledge Graph with the TTL ontology:" + ] + }, + { + "cell_type": "markdown", + "id": "7a7432aa", + "metadata": {}, + "source": [ + "### Option 1: Using Ontology.from_ttl() + KnowledgeGraph()" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "11d13b78", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Knowledge Graph 'sports_kg' created successfully!\n", - " - Ontology uploaded with 19 entities and 2 relations\n" - ] - } - ], + "outputs": [], "source": [ + "from litellm import models_by_provider\n", "from graphrag_sdk import KnowledgeGraph, KnowledgeGraphModelConfig\n", "from graphrag_sdk.models.litellm import LiteModel\n", "\n", - "\n", "# Initialize the model\n", - "model = LiteModel(model_name=\"gemini/gemini-2.5-flash\")\n", + "model = LiteModel(model_name=\"openai/gpt-4.1\")\n", + "\n", + "# Method 1: Use pre-extracted ontology\n", + "# kg = KnowledgeGraph(\n", + "# name=\"sports_kg\",\n", + "# model_config=KnowledgeGraphModelConfig.with_model(model),\n", + "# ontology=ontology, # Use the ontology extracted in Step 2\n", + "# host=falkor_host,\n", + "# port=falkor_port,\n", + "# username=falkor_username,\n", + "# password=falkor_password\n", + "# )\n", + "\n", + "# print(f\"✓ Knowledge Graph created!\")\n", + "# print(f\" - {len(ontology.entities)} entities, {len(ontology.relations)} relations\")" + ] + }, + { + "cell_type": "markdown", + "id": "865dfdc0", + "metadata": {}, + "source": [ + "### Option 2: Using KnowledgeGraph.from_ttl() (One-Step)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "112d9d3b", + "metadata": {}, + "outputs": [], + "source": [ + "# Method 2: Create KG directly from TTL file (alternative approach)\n", + "\n", "\n", - "# Create Knowledge Graph with the extracted ontology\n", - "kg = KnowledgeGraph(\n", + "kg = KnowledgeGraph.from_ttl(\n", + " path=ttl_file_path,\n", " name=\"sports_kg\",\n", " model_config=KnowledgeGraphModelConfig.with_model(model),\n", - " ontology=ontology,\n", " host=falkor_host,\n", " port=falkor_port,\n", " username=falkor_username,\n", " password=falkor_password\n", ")\n", "\n", - "print(f\" Knowledge Graph 'sports_kg' created successfully!\")\n", - "print(f\" - Ontology uploaded with {len(ontology.entities)} entities and {len(ontology.relations)} relations\")" + "print(f\"✓ Knowledge Graph created directly from TTL!\")\n", + "print(f\" - {len(kg.ontology.entities)} entities, {len(kg.ontology.relations)} relations\")" ] }, { From 9fdc4ea8d9b18623af060f08ee8bd3c91243696c Mon Sep 17 00:00:00 2001 From: Dianjan Date: Sun, 14 Dec 2025 18:41:05 +0530 Subject: [PATCH 108/136] Add TTLLoader to import TTL files to improve GraphRAG-SDK --- examples/data/ttl/sports.ttl | 2 +- graphrag_sdk/document_loaders/__init__.py | 2 - graphrag_sdk/document_loaders/ttl.py | 91 ----------------------- graphrag_sdk/kg.py | 56 ++++++++++++++ graphrag_sdk/ontology.py | 14 +++- graphrag_sdk/source.py | 13 ---- 6 files changed, 67 insertions(+), 111 deletions(-) delete mode 100644 graphrag_sdk/document_loaders/ttl.py diff --git a/examples/data/ttl/sports.ttl b/examples/data/ttl/sports.ttl index e5947f21..d86a9c1b 100644 --- a/examples/data/ttl/sports.ttl +++ b/examples/data/ttl/sports.ttl @@ -92,7 +92,7 @@ rdfs:subClassOf :Sport ; rdfs:comment "Racket sport played individually or in pairs" . -:Badmintion rdf:type owl:Class ; +:Badminton rdf:type owl:Class ; rdfs:subClassOf :Sport ; rdfs:comment "Racket sport using a shuttlecock" . diff --git a/graphrag_sdk/document_loaders/__init__.py b/graphrag_sdk/document_loaders/__init__.py index aea77f0f..0ef8e97d 100644 --- a/graphrag_sdk/document_loaders/__init__.py +++ b/graphrag_sdk/document_loaders/__init__.py @@ -5,7 +5,6 @@ from .url import URLLoader from .jsonl import JSONLLoader from .string import StringLoader -from .ttl import TTLLoader __all__ = [ "PDFLoader", @@ -15,5 +14,4 @@ "URLLoader", "JSONLLoader", "StringLoader", - "TTLLoader", ] diff --git a/graphrag_sdk/document_loaders/ttl.py b/graphrag_sdk/document_loaders/ttl.py deleted file mode 100644 index 4a069018..00000000 --- a/graphrag_sdk/document_loaders/ttl.py +++ /dev/null @@ -1,91 +0,0 @@ -from typing import Iterator -from graphrag_sdk.document import Document -from graphrag_sdk.helpers import extract_name_from_uri - - -class TTLLoader: - """ - TTL (Terse RDF Triple/Turtle Language) loader - - Parses RDF triples from TTL files and groups them by subject. - The entire file is processed as a single document. - """ - - def __init__(self, path: str): - """ - Initialize loader - - Args: - path (str): Path to the TTL file - """ - try: - import rdflib - except ImportError: - raise ImportError( - "rdflib package not found, please install it with " "`pip install rdflib`" - ) - - self.path = path - - def load(self) -> Iterator[Document]: - """ - Load TTL file - - Returns: - Iterator[Document]: document iterator - """ - # Parse the TTL file using shared method - graph = self.get_rdf_graph() - - # Group triples by subject - subjects_dict = {} - for subject, predicate, obj in graph: - # Strip namespaces - get local name only - subj_str = extract_name_from_uri(str(subject)) - pred_str = extract_name_from_uri(str(predicate)) - obj_str = extract_name_from_uri(str(obj)) - - if subj_str not in subjects_dict: - subjects_dict[subj_str] = [] - - # Store as readable triple text - subjects_dict[subj_str].append(f"{subj_str} {pred_str} {obj_str}") - - # Convert to list of (subject, triples) tuples - subjects_list = list(subjects_dict.items()) - - if len(subjects_list) == 0: - # Empty file - yield empty document - yield Document("", self.path) - return - - # Build document content: group all triples by subject - content_lines = [] - for subject, triples in subjects_list: - content_lines.append(f"Subject: {subject}") - for triple in triples: - content_lines.append(f" {triple}") - content_lines.append("") # Empty line between subjects - - content = "\n".join(content_lines) - yield Document(content, self.path) - - def get_rdf_graph(self): - """ - Get the parsed RDF graph for ontology extraction - - Returns: - rdflib.Graph: The parsed RDF graph - - Raises: - Exception: If the file cannot be parsed - """ - from rdflib import Graph as RDFGraph - - try: - graph = RDFGraph() - graph.parse(self.path, format="turtle") - return graph - except Exception as e: - raise Exception(f"Failed to parse TTL file: {e}, please ensure the file is valid TTL format.") - diff --git a/graphrag_sdk/kg.py b/graphrag_sdk/kg.py index a0a4e74b..19c84de6 100644 --- a/graphrag_sdk/kg.py +++ b/graphrag_sdk/kg.py @@ -117,6 +117,62 @@ def __init__( self.qa_prompt = qa_prompt self.cypher_gen_prompt_history = cypher_gen_prompt_history + @staticmethod + def from_ttl( + path: str, + name: str, + model_config: KnowledgeGraphModelConfig, + host: Optional[str] = "127.0.0.1", + port: Optional[int] = 6379, + username: Optional[str] = None, + password: Optional[str] = None, + cypher_system_instruction: Optional[str] = None, + qa_system_instruction: Optional[str] = None, + cypher_gen_prompt: Optional[str] = None, + qa_prompt: Optional[str] = None, + cypher_gen_prompt_history: Optional[str] = None, + ) -> "KnowledgeGraph": + """ + Create a KnowledgeGraph from a TTL (Turtle) RDF schema file. + + Args: + path (str): Path to the TTL file. + name (str): Knowledge graph name. + model_config (KnowledgeGraphModelConfig): Model configuration. + host (Optional[str]): FalkorDB hostname. + port (Optional[int]): FalkorDB port number. + username (Optional[str]): FalkorDB username. + password (Optional[str]): FalkorDB password. + cypher_system_instruction (Optional[str]): Cypher system instruction. + qa_system_instruction (Optional[str]): QA system instruction. + cypher_gen_prompt (Optional[str]): Cypher generation prompt. + qa_prompt (Optional[str]): QA prompt. + cypher_gen_prompt_history (Optional[str]): Cypher generation prompt with history. + + Returns: + KnowledgeGraph: New instance with extracted ontology. + """ + logger.info(f"Creating KnowledgeGraph from TTL file: {path}") + + # Extract ontology from TTL file + ontology = Ontology.from_ttl(path) + + # Create and return the KnowledgeGraph instance + return KnowledgeGraph( + name=name, + model_config=model_config, + ontology=ontology, + host=host, + port=port, + username=username, + password=password, + cypher_system_instruction=cypher_system_instruction, + qa_system_instruction=qa_system_instruction, + cypher_gen_prompt=cypher_gen_prompt, + qa_prompt=qa_prompt, + cypher_gen_prompt_history=cypher_gen_prompt_history, + ) + # Attributes @property diff --git a/graphrag_sdk/ontology.py b/graphrag_sdk/ontology.py index 09b1210d..5c9de1cb 100644 --- a/graphrag_sdk/ontology.py +++ b/graphrag_sdk/ontology.py @@ -196,7 +196,7 @@ def from_ttl(path: str) -> "Ontology": """ try: - from graphrag_sdk.document_loaders.ttl import TTLLoader + from rdflib import Graph as RDFGraph from graphrag_sdk.rdf_extractor import RDFOntologyExtractor except ImportError as e: raise ImportError( @@ -204,9 +204,15 @@ def from_ttl(path: str) -> "Ontology": "Please ensure rdflib is installed with `pip install rdflib`" ) - # Load the RDF graph from TTL file - loader = TTLLoader(path) - graph = loader.get_rdf_graph() + # Parse the RDF graph from TTL file + try: + graph = RDFGraph() + graph.parse(path, format="turtle") + except Exception as e: + raise Exception( + f"Failed to parse TTL file: {e}. " + "Please ensure the file is valid TTL format." + ) # Extract ontology using RDFOntologyExtractor extractor = RDFOntologyExtractor(graph) diff --git a/graphrag_sdk/source.py b/graphrag_sdk/source.py index 2c8e87c1..dbe3b1dc 100644 --- a/graphrag_sdk/source.py +++ b/graphrag_sdk/source.py @@ -9,7 +9,6 @@ CSVLoader, JSONLLoader, StringLoader, - TTLLoader, ) @@ -37,8 +36,6 @@ def Source(path: str, instruction: Optional[str] = None) -> "AbstractSource": s = CSV(path) elif ".jsonl" in path.lower(): s = JSONL(path) - elif ".ttl" in path.lower(): - s = TTL(path) elif ".txt" in path.lower(): s = TEXT(path) else: @@ -191,13 +188,3 @@ class STRING(AbstractSource): def __init__(self, data_source: str): super().__init__(data_source) self.loader = StringLoader(self.data_source) - - -class TTL(AbstractSource): - """ - TTL (Terse RDF Triple Language) resource - """ - - def __init__(self, data_source: str): - super().__init__(data_source) - self.loader = TTLLoader(self.data_source) From 4ff48c35e7b030ac0d2a267c5c89cbe566a67779 Mon Sep 17 00:00:00 2001 From: Dianjan Date: Sun, 14 Dec 2025 19:04:51 +0530 Subject: [PATCH 109/136] Add TTLLoader to import TTL files to improve GraphRAG-SDK --- examples/sports/demo-sports.ipynb | 24 ++++++++++++------------ graphrag_sdk/ontology.py | 8 ++++---- 2 files changed, 16 insertions(+), 16 deletions(-) diff --git a/examples/sports/demo-sports.ipynb b/examples/sports/demo-sports.ipynb index f1575117..ea56a6b1 100644 --- a/examples/sports/demo-sports.ipynb +++ b/examples/sports/demo-sports.ipynb @@ -610,18 +610,18 @@ "model = LiteModel(model_name=\"openai/gpt-4.1\")\n", "\n", "# Method 1: Use pre-extracted ontology\n", - "# kg = KnowledgeGraph(\n", - "# name=\"sports_kg\",\n", - "# model_config=KnowledgeGraphModelConfig.with_model(model),\n", - "# ontology=ontology, # Use the ontology extracted in Step 2\n", - "# host=falkor_host,\n", - "# port=falkor_port,\n", - "# username=falkor_username,\n", - "# password=falkor_password\n", - "# )\n", - "\n", - "# print(f\"✓ Knowledge Graph created!\")\n", - "# print(f\" - {len(ontology.entities)} entities, {len(ontology.relations)} relations\")" + "kg = KnowledgeGraph(\n", + " name=\"sports_kg\",\n", + " model_config=KnowledgeGraphModelConfig.with_model(model),\n", + " ontology=ontology, # Use the ontology extracted in Step 2\n", + " host=falkor_host,\n", + " port=falkor_port,\n", + " username=falkor_username,\n", + " password=falkor_password\n", + ")\n", + "\n", + "print(f\"✓ Knowledge Graph created!\")\n", + "print(f\" - {len(ontology.entities)} entities, {len(ontology.relations)} relations\")" ] }, { diff --git a/graphrag_sdk/ontology.py b/graphrag_sdk/ontology.py index 5c9de1cb..aa3ba42b 100644 --- a/graphrag_sdk/ontology.py +++ b/graphrag_sdk/ontology.py @@ -208,10 +208,10 @@ def from_ttl(path: str) -> "Ontology": try: graph = RDFGraph() graph.parse(path, format="turtle") - except Exception as e: - raise Exception( - f"Failed to parse TTL file: {e}. " - "Please ensure the file is valid TTL format." + except (FileNotFoundError, OSError, SyntaxError) as e: + raise ValueError( + f"Failed to parse TTL file: {e}. " + "Please ensure the file is valid TTL format." ) # Extract ontology using RDFOntologyExtractor From 40fa7cf8d340b5423ca04205848d054812676707 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Sun, 14 Dec 2025 16:54:10 +0200 Subject: [PATCH 110/136] Update graphrag_sdk/helpers.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- graphrag_sdk/helpers.py | 1 - 1 file changed, 1 deletion(-) diff --git a/graphrag_sdk/helpers.py b/graphrag_sdk/helpers.py index 1ddb6220..6b4783cf 100644 --- a/graphrag_sdk/helpers.py +++ b/graphrag_sdk/helpers.py @@ -68,7 +68,6 @@ def map_dict_to_cypher_properties(d: dict) -> str: cypher += f"{i}: {item}, " cypher = (cypher[:-2] if len(cypher) > 1 else cypher) + "}" return cypher - for key, value in d.items(): # Check value type if isinstance(value, str): From 25603b39cc5bdefeef3b1a701427dea53f7b7238 Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Sat, 27 Dec 2025 15:50:30 +0200 Subject: [PATCH 111/136] Create dependabot.yml --- .github/dependabot.yml | 11 +++++++++++ 1 file changed, 11 insertions(+) create mode 100644 .github/dependabot.yml diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 00000000..9d866e39 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,11 @@ +# To get started with Dependabot version updates, you'll need to specify which +# package ecosystems to update and where the package manifests are located. +# Please see the documentation for all configuration options: +# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file + +version: 2 +updates: + - package-ecosystem: "pip" # See documentation for possible values + directory: "/" # Location of package manifests + schedule: + interval: "weekly" From 40e2f301a37cc5c560a4d281e63b8a6d92039bd0 Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Sat, 27 Dec 2025 15:59:58 +0200 Subject: [PATCH 112/136] Change Dependabot schedule from weekly to daily --- .github/dependabot.yml | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/.github/dependabot.yml b/.github/dependabot.yml index 9d866e39..ac851055 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -3,9 +3,15 @@ # Please see the documentation for all configuration options: # https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file + version: 2 updates: - - package-ecosystem: "pip" # See documentation for possible values - directory: "/" # Location of package manifests + - package-ecosystem: "pip" + directory: "/" + schedule: + interval: "daily" + + - package-ecosystem: "github-actions" + directory: "/" schedule: interval: "weekly" From 1798312b4f74c29fa110e04715b76bfb009534f2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:20:50 +0000 Subject: [PATCH 113/136] Bump google-github-actions/setup-gcloud from 2 to 3 Bumps [google-github-actions/setup-gcloud](https://github.com/google-github-actions/setup-gcloud) from 2 to 3. - [Release notes](https://github.com/google-github-actions/setup-gcloud/releases) - [Changelog](https://github.com/google-github-actions/setup-gcloud/blob/main/CHANGELOG.md) - [Commits](https://github.com/google-github-actions/setup-gcloud/compare/v2...v3) --- updated-dependencies: - dependency-name: google-github-actions/setup-gcloud dependency-version: '3' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c95d44a3..0e2f13fb 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -52,7 +52,7 @@ jobs: credentials_json: ${{ secrets.GCP_SA_KEY }} - name: "Set up Cloud SDK" - uses: "google-github-actions/setup-gcloud@v2" + uses: "google-github-actions/setup-gcloud@v3" with: version: ">= 363.0.0" From c0dda29c35e14eea28ca1ee72c7272b6df9bc375 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:20:54 +0000 Subject: [PATCH 114/136] Bump actions/setup-python from 5 to 6 Bumps [actions/setup-python](https://github.com/actions/setup-python) from 5 to 6. - [Release notes](https://github.com/actions/setup-python/releases) - [Commits](https://github.com/actions/setup-python/compare/v5...v6) --- updated-dependencies: - dependency-name: actions/setup-python dependency-version: '6' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/sync-dependencies.yml | 2 +- .github/workflows/test.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index b721abe3..5250bb72 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -20,7 +20,7 @@ jobs: ref: ${{ github.head_ref || github.ref }} - name: Setup Python - uses: actions/setup-python@v5 + uses: actions/setup-python@v6 with: python-version: '3.11' diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c95d44a3..e25e5ae2 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -33,7 +33,7 @@ jobs: - uses: actions/checkout@v4 - name: Set up Python - uses: actions/setup-python@v5 + uses: actions/setup-python@v6 with: python-version: 3.11.0 # Update with desired Python version From 97025fc3075c6e4a3467a2df58400973a05ad4fc Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:20:57 +0000 Subject: [PATCH 115/136] Bump rojopolis/spellcheck-github-actions from 0.33.1 to 0.56.0 Bumps [rojopolis/spellcheck-github-actions](https://github.com/rojopolis/spellcheck-github-actions) from 0.33.1 to 0.56.0. - [Release notes](https://github.com/rojopolis/spellcheck-github-actions/releases) - [Changelog](https://github.com/rojopolis/spellcheck-github-actions/blob/master/CHANGELOG.md) - [Commits](https://github.com/rojopolis/spellcheck-github-actions/compare/0.33.1...0.56.0) --- updated-dependencies: - dependency-name: rojopolis/spellcheck-github-actions dependency-version: 0.56.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- .github/workflows/spellcheck.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/spellcheck.yml b/.github/workflows/spellcheck.yml index 5dc182d3..c4b4f4f6 100644 --- a/.github/workflows/spellcheck.yml +++ b/.github/workflows/spellcheck.yml @@ -11,7 +11,7 @@ jobs: - name: Checkout uses: actions/checkout@v3 - name: Check Spelling - uses: rojopolis/spellcheck-github-actions@0.33.1 + uses: rojopolis/spellcheck-github-actions@0.56.0 with: config_path: .spellcheck.yml task_name: Markdown From d49b55aa088368f3a5dba06babe4e359655e3876 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:21:00 +0000 Subject: [PATCH 116/136] Bump actions/cache from 4 to 5 Bumps [actions/cache](https://github.com/actions/cache) from 4 to 5. - [Release notes](https://github.com/actions/cache/releases) - [Changelog](https://github.com/actions/cache/blob/main/RELEASES.md) - [Commits](https://github.com/actions/cache/compare/v4...v5) --- updated-dependencies: - dependency-name: actions/cache dependency-version: '5' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c95d44a3..35f6e228 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -39,7 +39,7 @@ jobs: - name: Cache Poetry virtualenv id: cache - uses: actions/cache@v4 + uses: actions/cache@v5 with: path: ~/.poetry/virtualenvs key: ${{ runner.os }}-poetry-${{ hashFiles('poetry.lock') }} From 27bf894ce1351d75a90a1e50b839c9c5ba1826b5 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:21:03 +0000 Subject: [PATCH 117/136] Bump google-github-actions/auth from 2 to 3 Bumps [google-github-actions/auth](https://github.com/google-github-actions/auth) from 2 to 3. - [Release notes](https://github.com/google-github-actions/auth/releases) - [Changelog](https://github.com/google-github-actions/auth/blob/main/CHANGELOG.md) - [Commits](https://github.com/google-github-actions/auth/compare/v2...v3) --- updated-dependencies: - dependency-name: google-github-actions/auth dependency-version: '3' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/test.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index c95d44a3..1eccf993 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -47,7 +47,7 @@ jobs: ${{ runner.os }}-poetry- - id: "auth" - uses: "google-github-actions/auth@v2" + uses: "google-github-actions/auth@v3" with: credentials_json: ${{ secrets.GCP_SA_KEY }} From f05574b2dbeafcaa5b6a86b60083ac91ee14a12c Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:22:34 +0000 Subject: [PATCH 118/136] Bump beautifulsoup4 from 4.13.5 to 4.14.3 Bumps [beautifulsoup4](https://www.crummy.com/software/BeautifulSoup/bs4/) from 4.13.5 to 4.14.3. --- updated-dependencies: - dependency-name: beautifulsoup4 dependency-version: 4.14.3 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- poetry.lock | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/poetry.lock b/poetry.lock index 024e42d0..efc12954 100644 --- a/poetry.lock +++ b/poetry.lock @@ -400,18 +400,18 @@ files = [ [[package]] name = "beautifulsoup4" -version = "4.13.5" +version = "4.14.3" description = "Screen-scraping library" optional = false python-versions = ">=3.7.0" groups = ["main", "dev"] files = [ - {file = "beautifulsoup4-4.13.5-py3-none-any.whl", hash = "sha256:642085eaa22233aceadff9c69651bc51e8bf3f874fb6d7104ece2beb24b47c4a"}, - {file = "beautifulsoup4-4.13.5.tar.gz", hash = "sha256:5e70131382930e7c3de33450a2f54a63d5e4b19386eab43a5b34d594268f3695"}, + {file = "beautifulsoup4-4.14.3-py3-none-any.whl", hash = "sha256:0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb"}, + {file = "beautifulsoup4-4.14.3.tar.gz", hash = "sha256:6292b1c5186d356bba669ef9f7f051757099565ad9ada5dd630bd9de5fa7fb86"}, ] [package.dependencies] -soupsieve = ">1.2" +soupsieve = ">=1.6.1" typing-extensions = ">=4.0.0" [package.extras] @@ -3221,7 +3221,7 @@ description = "Run a subprocess in a pseudo terminal" optional = false python-versions = "*" groups = ["dev"] -markers = "os_name != \"nt\" or sys_platform != \"win32\" and sys_platform != \"emscripten\"" +markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\" or os_name != \"nt\"" files = [ {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"}, {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"}, From 02cf2d9c5908cbaa32b259253d5caac9387214e2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 29 Dec 2025 11:24:18 +0000 Subject: [PATCH 119/136] Bump pandas from 2.3.2 to 2.3.3 Bumps [pandas](https://github.com/pandas-dev/pandas) from 2.3.2 to 2.3.3. - [Release notes](https://github.com/pandas-dev/pandas/releases) - [Commits](https://github.com/pandas-dev/pandas/compare/v2.3.2...v2.3.3) --- updated-dependencies: - dependency-name: pandas dependency-version: 2.3.3 dependency-type: direct:development update-type: version-update:semver-patch ... 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Signed-off-by: dependabot[bot] --- .github/workflows/pypi-publish.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pypi-publish.yaml b/.github/workflows/pypi-publish.yaml index 5d24505a..4eda02eb 100644 --- a/.github/workflows/pypi-publish.yaml +++ b/.github/workflows/pypi-publish.yaml @@ -10,7 +10,7 @@ jobs: steps: - uses: actions/checkout@v4 - name: Build and publish to pypi - uses: JRubics/poetry-publish@v2.0 + uses: JRubics/poetry-publish@v2.1 with: pypi_token: ${{ secrets.PYPI_API_TOKEN }} build_format: "sdist" From 501351e2fbac41df70ec8760be1b6b83e1bae044 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 5 Jan 2026 03:27:57 +0000 Subject: [PATCH 121/136] Bump actions/checkout from 3 to 6 Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 6. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](https://github.com/actions/checkout/compare/v3...v6) --- updated-dependencies: - dependency-name: actions/checkout dependency-version: '6' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/pypi-publish.yaml | 2 +- .github/workflows/spellcheck.yml | 2 +- .github/workflows/sync-dependencies.yml | 2 +- .github/workflows/test.yml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/pypi-publish.yaml b/.github/workflows/pypi-publish.yaml index 5d24505a..5ac5ab83 100644 --- a/.github/workflows/pypi-publish.yaml +++ b/.github/workflows/pypi-publish.yaml @@ -8,7 +8,7 @@ jobs: build: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 - name: Build and publish to pypi uses: JRubics/poetry-publish@v2.0 with: diff --git a/.github/workflows/spellcheck.yml b/.github/workflows/spellcheck.yml index c4b4f4f6..4123b7d8 100644 --- a/.github/workflows/spellcheck.yml +++ b/.github/workflows/spellcheck.yml @@ -9,7 +9,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Checkout - uses: actions/checkout@v3 + uses: actions/checkout@v6 - name: Check Spelling uses: rojopolis/spellcheck-github-actions@0.56.0 with: diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml index 5250bb72..1fa5514f 100644 --- a/.github/workflows/sync-dependencies.yml +++ b/.github/workflows/sync-dependencies.yml @@ -14,7 +14,7 @@ jobs: permissions: contents: write steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 with: fetch-depth: 0 ref: ${{ github.head_ref || github.ref }} diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 4d60946a..7f76790b 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -30,7 +30,7 @@ jobs: model: [openai/gpt-4.1] # List of models steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v6 - name: Set up Python uses: actions/setup-python@v6 From 123ee1f44ee9aef166376fbe4aa5b69b8cb736c9 Mon Sep 17 00:00:00 2001 From: Gal Shubeli Date: Thu, 15 Jan 2026 15:00:16 +0200 Subject: [PATCH 122/136] spellcheck --- .wordlist.txt | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.wordlist.txt b/.wordlist.txt index 1502caae..054ddcc2 100644 --- a/.wordlist.txt +++ b/.wordlist.txt @@ -14,6 +14,7 @@ orchestrators LLM env JSONL +JSON CSV Orchestrator orchestrator @@ -25,6 +26,7 @@ html https www faq +codebase Ollama ollama Cypher From 66d2814a0501e610f8b601d1f67f0947554c5fa0 Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Thu, 15 Jan 2026 15:33:09 +0200 Subject: [PATCH 123/136] rename to - --- .gitignore | 3 +- poetry.lock | 4054 +++++++++++++++++++++++++--------------------- pyproject.toml | 4 +- requirements.txt | 18 - 4 files changed, 2256 insertions(+), 1823 deletions(-) delete mode 100644 requirements.txt diff --git a/.gitignore b/.gitignore index adcdef9f..f79ebf93 100644 --- a/.gitignore +++ b/.gitignore @@ -10,4 +10,5 @@ falkordb-data weaviate-data .deepeval_telemtry.txt -.claude \ No newline at end of file +.claude +dist/ diff --git a/poetry.lock b/poetry.lock index 26e2a0b8..b4e07909 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand. 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"Enables graph-based RAG and integration with LLMs for advanced querying and knowledge graph creation." authors = ["FalkorDB "] diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 90c5a221..00000000 --- a/requirements.txt +++ /dev/null @@ -1,18 +0,0 @@ -# Auto-generated from pyproject.toml [tool.poetry.dependencies] -# This file contains only DIRECT dependencies, not transitive ones -# Source of truth: pyproject.toml -# -# To install: -# pip install -r requirements.txt - -backoff>=2.2.1,<3.0.0 -beautifulsoup4>=4.12.3,<5.0.0 -falkordb>=1.0.9,<2.0.0 -fix-busted-json>=0.0.18,<0.0.19 -litellm>=1.73.1,<2.0.0 -pypdf>=5.9.0,<6.0.0 -python-dotenv>=1.0.1,<2.0.0 -ratelimit>=2.2.1,<3.0.0 -requests>=2.32.3,<3.0.0 -rich>=13.9.4,<14.0.0 -typing-extensions>=4.12.1,<5.0.0 From 6ef7837cb2d41720e95a184074edd870443fa712 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Thu, 15 Jan 2026 13:34:07 +0000 Subject: [PATCH 124/136] Auto-sync requirements.txt from pyproject.toml --- requirements.txt | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) create mode 100644 requirements.txt diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 00000000..9ab53f36 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,19 @@ +# Auto-generated from pyproject.toml [tool.poetry.dependencies] +# This file contains only DIRECT dependencies, not transitive ones +# Source of truth: pyproject.toml +# +# To install: +# pip install -r requirements.txt + +backoff>=2.2.1,<3.0.0 +beautifulsoup4>=4.12.3,<5.0.0 +falkordb>=1.0.9,<2.0.0 +fix-busted-json>=0.0.18,<0.0.19 +litellm>=1.73.1,<2.0.0 +pypdf>=5.9.0,<6.0.0 +python-dotenv>=1.0.1,<2.0.0 +ratelimit>=2.2.1,<3.0.0 +rdflib>=7.0.0,<8.0.0 +requests>=2.32.3,<3.0.0 +rich>=13.9.4,<14.0.0 +typing-extensions>=4.12.1,<5.0.0 From 7a931eccd68cb354c58dac26ec7b3e6a39e13418 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Thu, 15 Jan 2026 13:50:56 +0000 Subject: [PATCH 125/136] Initial plan From b6fe3ffacd62034e35cc2febc128eb839c595398 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Thu, 15 Jan 2026 13:56:40 +0000 Subject: [PATCH 126/136] Migrate project from Poetry to UV - Updated pyproject.toml to use standard PEP 621 format with hatchling build backend - Updated GitHub Actions workflows to use UV instead of Poetry - Removed Poetry-specific sync-dependencies workflow (UV handles this natively) - Updated CONTRIBUTING.md with UV installation and usage instructions - Removed poetry.lock, added uv.lock - Updated requirements.txt header to reflect new tooling Co-authored-by: gkorland <753206+gkorland@users.noreply.github.com> --- .github/workflows/pypi-publish.yaml | 20 +- .github/workflows/sync-dependencies.yml | 230 - .github/workflows/test.yml | 20 +- CONTRIBUTING.md | 13 +- poetry.lock | 5316 ----------------------- pyproject.toml | 83 +- requirements.txt | 5 +- uv.lock | 3875 +++++++++++++++++ 8 files changed, 3959 insertions(+), 5603 deletions(-) delete mode 100644 .github/workflows/sync-dependencies.yml delete mode 100644 poetry.lock create mode 100644 uv.lock diff --git a/.github/workflows/pypi-publish.yaml b/.github/workflows/pypi-publish.yaml index 85205da6..4269830d 100644 --- a/.github/workflows/pypi-publish.yaml +++ b/.github/workflows/pypi-publish.yaml @@ -9,9 +9,19 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v6 - - name: Build and publish to pypi - uses: JRubics/poetry-publish@v2.1 + + - name: Set up Python + uses: actions/setup-python@v6 with: - pypi_token: ${{ secrets.PYPI_API_TOKEN }} - build_format: "sdist" - ignore_dev_requirements: "yes" + python-version: '3.11' + + - name: Install uv + uses: astral-sh/setup-uv@v4 + + - name: Build package + run: uv build + + - name: Publish to PyPI + env: + UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }} + run: uv publish diff --git a/.github/workflows/sync-dependencies.yml b/.github/workflows/sync-dependencies.yml deleted file mode 100644 index 1fa5514f..00000000 --- a/.github/workflows/sync-dependencies.yml +++ /dev/null @@ -1,230 +0,0 @@ -name: Sync Dependencies - -on: - push: - paths: ['pyproject.toml'] - branches: [main] - pull_request: - paths: ['pyproject.toml'] - branches: [main] - -jobs: - sync: - runs-on: ubuntu-latest - permissions: - contents: write - steps: - - uses: actions/checkout@v6 - with: - fetch-depth: 0 - ref: ${{ github.head_ref || github.ref }} - - - name: Setup Python - uses: actions/setup-python@v6 - with: - python-version: '3.11' - - - name: Install tomli for Python <3.11 - run: | - python3 -c "import sys; sys.exit(0 if sys.version_info >= (3, 11) else 1)" || python3 -m pip install -q tomli - - - name: Sync requirements - run: | - set -euo pipefail - python3 - <<'PY' - import sys - import re - try: - import tomllib - except ImportError: - import tomli as tomllib - - def caret_to_range(v: str) -> str: - """Convert Poetry caret constraint to pip-compatible range with proper pre-1.0 semantics, incl. ^0 and ^0.0.""" - base = v[1:] - parts = base.split('.') - def num(seg): - m = re.match(r'(\d+)', str(seg)) - return int(m.group(1)) if m else 0 - major = num(parts[0]) if len(parts) > 0 else 0 - minor = num(parts[1]) if len(parts) > 1 else 0 - patch = num(parts[2]) if len(parts) > 2 else 0 - # Proper caret semantics: - # - ^X[.Y[.Z]] with X>0 -> <(X+1).0.0 - # - ^0.Y[.Z] with Y>0 -> <0.(Y+1).0 - # - ^0.0.Z -> <0.0.(Z+1) - # - ^0 -> <1.0.0 - # - ^0.0 -> <0.1.0 - if major > 0: - upper = f'{major+1}.0.0' - elif len(parts) == 1: # ^0 - upper = '1.0.0' - elif len(parts) == 2 and minor == 0: # ^0.0 - upper = '0.1.0' - elif minor > 0: - upper = f'0.{minor+1}.0' - else: - upper = f'0.0.{patch+1}' - return f'>={base},<{upper}' - - try: - with open('pyproject.toml', 'rb') as f: - data = tomllib.load(f) - except Exception as e: - print(f"Error reading pyproject.toml: {e}") - sys.exit(1) - - deps_table = data.get('tool', {}).get('poetry', {}).get('dependencies', {}) - if not deps_table: - print("No dependencies found in pyproject.toml") - sys.exit(1) - - deps = [] - - for name, spec in deps_table.items(): - if name.lower() == 'python': - continue - - extras = [] - req_line = None - version = None - markers = None - - try: - if isinstance(spec, str): - version = spec.strip() - elif isinstance(spec, dict): - extras = sorted(spec.get('extras') or []) - markers = (spec.get('markers') or '').strip() or None - - if 'version' in spec: - version = str(spec['version']).strip() - elif 'git' in spec: - ref = spec.get('rev') or spec.get('tag') or spec.get('branch') or '' - frag = f'@{ref}' if ref else '' - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ git+{spec['git']}{frag}" - if markers: - req_line += f"; {markers}" - elif 'url' in spec: - extras_part = f"[{','.join(extras)}]" if extras else '' - req_line = f"{name}{extras_part} @ {spec['url']}" - if markers: - req_line += f"; {markers}" - elif 'path' in spec: - # Skip local path dependencies as they can't be in requirements.txt - print(f"Skipping local path dependency: {name}") - continue - else: - print(f"Skipping unsupported dependency spec for {name}: {spec}") - continue - else: - print(f"Skipping unsupported dependency type for {name}: {type(spec)}") - continue - - if req_line is None and version is not None: - def normalize(ver: str) -> str: - ver = ver.strip() - if not ver: - return '' - if ver == '*' or ver.lower() == 'any': - return '' - if ver.startswith('^'): - return caret_to_range(ver) - # Check for existing constraints/operators - has_constraint = any(op in ver for op in ['<', '>', '!=', '==', '===', '~=', '~', '*']) - has_space = ' ' in ver # Combined constraints like ">=1.0 <2.0" - return ver if (has_constraint or has_space) else f'>={ver}' - - normalized_version = normalize(version) - extras_part = f"[{','.join(extras)}]" if extras else '' - if normalized_version: - req_line 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direct dependencies') - - # Print summary - print('\nGenerated dependencies:') - for dep in deps: - print(f' - {dep}') - - except Exception as e: - print(f"Error writing requirements.txt: {e}") - sys.exit(1) - PY - - - name: Configure Git - run: | - set -e - git config --local user.email "github-actions[bot]@users.noreply.github.com" - git config --local user.name "github-actions[bot]" - - - name: Check for changes - id: changes - run: | - if git diff --quiet HEAD -- requirements.txt; then - echo "changed=false" >> $GITHUB_OUTPUT - echo "No changes to requirements.txt" - else - echo "changed=true" >> $GITHUB_OUTPUT - echo "Changes detected in requirements.txt" - fi - - - name: Commit changes - env: - PR_REF: ${{ github.head_ref }} - run: | - set -e - git add requirements.txt - if git diff --staged --quiet; then - echo "No changes to commit" - else - git commit -m "Auto-sync requirements.txt from pyproject.toml" - if [ "${{ github.event_name }}" = "pull_request" ]; then - case "${PR_REF}" in - *[!A-Za-z0-9_-]*|'') echo "Unsafe PR ref; skipping push"; exit 0;; - esac - git push origin "HEAD:${PR_REF}" - else - git push - fi - fi - - - name: Summary - run: | - if [[ "${{ steps.changes.outputs.changed }}" == "true" ]]; then - echo "requirements.txt has been updated and committed" - else - echo "requirements.txt is already up to date" - fi \ No newline at end of file diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 7f76790b..b3dea72a 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -37,14 +37,11 @@ jobs: with: python-version: 3.11.0 # Update with desired Python version - - name: Cache Poetry virtualenv - id: cache - uses: actions/cache@v5 + - name: Install uv + uses: astral-sh/setup-uv@v4 with: - path: ~/.poetry/virtualenvs - key: ${{ runner.os }}-poetry-${{ hashFiles('poetry.lock') }} - restore-keys: | - ${{ runner.os }}-poetry- + enable-cache: true + cache-dependency-glob: "uv.lock" - id: "auth" uses: "google-github-actions/auth@v3" @@ -56,13 +53,8 @@ jobs: with: version: ">= 363.0.0" - - name: Install Poetry - if: steps.cache.outputs.cache-hit != true - run: | - curl -sSL https://install.python-poetry.org | python3 - - - name: Install dependencies - run: poetry install --with test + run: uv sync --extra test - name: Wait for Ollama to be ready run: | @@ -82,4 +74,4 @@ jobs: AZURE_API_VERSION: ${{ secrets.AZURE_API_VERSION }} AZURE_API_KEY: ${{ secrets.AZURE_API_KEY }} TEST_MODEL: ${{ matrix.model }} # Pass the model as an environment variable - run: poetry run pytest + run: uv run pytest diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index a03ac48d..4a72ca16 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -52,9 +52,16 @@ To set up **GraphRAG-SDK** for local development: cd GraphRAG-SDK ``` -2. Install the required dependencies: +2. Install uv (if not already installed): ```bash - poetry install --extras "all" + pip install uv + # Or on macOS/Linux: + # curl -LsSf https://astral.sh/uv/install.sh | sh + ``` + +3. Install the required dependencies: + ```bash + uv sync --all-extras ``` ## Pull Request Guidelines @@ -99,7 +106,7 @@ Testing is essential for ensuring code quality in **GraphRAG-SDK**. Before submi export REGION=${REGION} export OPENAI_API_KEY=${OPENAI_API_KEY} export GOOGLE_API_KEY=${GOOGLE_API_KEY} - poetry run pytest + uv run pytest ``` ## Thank You! diff --git a/poetry.lock b/poetry.lock deleted file mode 100644 index 26e2a0b8..00000000 --- a/poetry.lock +++ /dev/null @@ -1,5316 +0,0 @@ -# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. - -[[package]] -name = "aiohappyeyeballs" -version = "2.6.1" -description = "Happy Eyeballs for asyncio" -optional = false -python-versions = ">=3.9" -groups = ["main", "test"] -files = [ - {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, - {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, -] - -[[package]] -name = "aiohttp" -version = "3.12.15" -description = "Async http client/server framework (asyncio)" -optional = false -python-versions = ">=3.9" -groups = ["main", "test"] -files = [ - 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deletion(-) diff --git a/.gitignore b/.gitignore index adcdef9f..7a113890 100644 --- a/.gitignore +++ b/.gitignore @@ -10,4 +10,6 @@ falkordb-data weaviate-data .deepeval_telemtry.txt -.claude \ No newline at end of file +.claude# Build artifacts +dist/ +build/ From 8eff589b404e9b6af56f6d54225607b5c06f8d19 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Thu, 15 Jan 2026 15:00:04 +0000 Subject: [PATCH 128/136] Fix merge conflicts and add spelling words - Resolved .gitignore conflict (proper formatting for .claude and build artifacts) - Updated version to 0.8.2 from main branch - Fixed package name to use hyphens (graphrag-sdk) per PyPI conventions - Removed poetry.lock (using uv.lock instead) - Updated uv.lock with new version - Added 'uv' and 'hatchling' to .wordlist.txt for spellcheck Co-authored-by: gkorland <753206+gkorland@users.noreply.github.com> --- .wordlist.txt | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.wordlist.txt b/.wordlist.txt index 054ddcc2..a9618949 100644 --- a/.wordlist.txt +++ b/.wordlist.txt @@ -41,4 +41,6 @@ Embeddings NLP graphrag gemini -gpt \ No newline at end of file +gpt +uv +hatchling \ No newline at end of file From fca97588b37e426a94fbfe739986e3a821f6ab48 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 15 Jan 2026 15:05:27 +0000 Subject: [PATCH 129/136] Bump ipykernel from 6.30.1 to 7.1.0 Bumps [ipykernel](https://github.com/ipython/ipykernel) from 6.30.1 to 7.1.0. - [Release notes](https://github.com/ipython/ipykernel/releases) - [Changelog](https://github.com/ipython/ipykernel/blob/main/CHANGELOG.md) - [Commits](https://github.com/ipython/ipykernel/compare/v6.30.1...v7.1.0) --- updated-dependencies: - dependency-name: ipykernel dependency-version: 7.1.0 dependency-type: direct:development update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- poetry.lock | 16 ++++++++-------- pyproject.toml | 2 +- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/poetry.lock b/poetry.lock index b4e07909..ac234130 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" @@ -1600,14 +1600,14 @@ files = [ [[package]] name = "ipykernel" -version = "6.31.0" +version = "7.1.0" description = "IPython Kernel for Jupyter" optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" groups = ["dev"] files = [ - {file = "ipykernel-6.31.0-py3-none-any.whl", hash = "sha256:abe5386f6ced727a70e0eb0cf1da801fa7c5fa6ff82147747d5a0406cd8c94af"}, - {file = "ipykernel-6.31.0.tar.gz", hash = "sha256:2372ce8bc1ff4f34e58cafed3a0feb2194b91fc7cad0fc72e79e47b45ee9e8f6"}, + {file = "ipykernel-7.1.0-py3-none-any.whl", hash = "sha256:763b5ec6c5b7776f6a8d7ce09b267693b4e5ce75cb50ae696aaefb3c85e1ea4c"}, + {file = "ipykernel-7.1.0.tar.gz", hash = "sha256:58a3fc88533d5930c3546dc7eac66c6d288acde4f801e2001e65edc5dc9cf0db"}, ] [package.dependencies] @@ -1627,7 +1627,7 @@ traitlets = ">=5.4.0" [package.extras] cov = ["coverage[toml]", "matplotlib", "pytest-cov", "trio"] -docs = ["intersphinx-registry", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"] +docs = ["intersphinx-registry", "myst-parser", "pydata-sphinx-theme", "sphinx (<8.2.0)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"] pyqt5 = ["pyqt5"] pyside6 = ["pyside6"] test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0,<9)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"] @@ -3566,7 +3566,7 @@ description = "Run a subprocess in a pseudo terminal" optional = false python-versions = "*" groups = ["dev"] -markers = "os_name != \"nt\" or sys_platform != \"win32\" and sys_platform != \"emscripten\"" +markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\" or os_name != \"nt\"" files = [ {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"}, {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"}, @@ -5763,4 +5763,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.1" python-versions = "^3.10.0, <3.14" -content-hash = "c40393bd66a0e818bd77c634e05720d0088c604d5ffb26472cfe43b453f84023" +content-hash = "94fd6a7ba7a121f7567f30f4d694896e39259afbac037055743be5983749d566" diff --git a/pyproject.toml b/pyproject.toml index e9cfac79..763c3693 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,7 +36,7 @@ sphinx = "^7.3.7" sphinx-rtd-theme = "^2.0.0" pandas = "^2.2.2" jupyter = "^1.0.0" -ipykernel = "^6.29.5" +ipykernel = ">=6.29.5,<8.0.0" [build-system] requires = ["poetry-core"] From d80ada490618148cf81aaff35d9bde0193472dab Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Thu, 15 Jan 2026 15:28:50 +0000 Subject: [PATCH 130/136] Fix test import error and update dependabot config - Remove numpy import from test_rag.py (not needed, only used for mean) - Replace np.mean(scores) with sum(scores)/len(scores) built-in - Add clarifying comment to dependabot.yml about UV/pip compatibility - Dependabot continues to use "pip" ecosystem as it reads pyproject.toml (PEP 621) Co-authored-by: gkorland <753206+gkorland@users.noreply.github.com> --- .github/dependabot.yml | 3 +++ tests/test_rag.py | 3 +-- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/.github/dependabot.yml b/.github/dependabot.yml index ac851055..949a88a1 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -2,6 +2,9 @@ # package ecosystems to update and where the package manifests are located. # Please see the documentation for all configuration options: # https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file +# +# Note: This project uses UV for package management, but Dependabot uses the "pip" +# ecosystem to read pyproject.toml (PEP 621 format) which is compatible with UV. version: 2 diff --git a/tests/test_rag.py b/tests/test_rag.py index 6beffb4e..035e8d7b 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -1,7 +1,6 @@ import os import pytest import logging -import numpy as np from dotenv import load_dotenv from graphrag_sdk.entity import Entity from deepeval.test_case import LLMTestCase @@ -202,6 +201,6 @@ def test_movie_actor_queries(self, knowledge_graph_setup, delete_kg): delete_kg(kg) # Verify that the average score meets the threshold - average_score = np.mean(scores) + average_score = sum(scores) / len(scores) logger.info(f"Average Score: {average_score}") assert average_score >= 0.5, f"Average score {average_score} is below threshold of 0.5" \ No newline at end of file From 1aa70c6e82e3f667dca00f22703995b5b21e0064 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Thu, 15 Jan 2026 15:30:40 +0000 Subject: [PATCH 131/136] Add guard against division by zero in test - Add assertion to check len(scores) > 0 before calculating average - Prevents potential ZeroDivisionError if no test cases are run Co-authored-by: gkorland <753206+gkorland@users.noreply.github.com> --- tests/test_rag.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/test_rag.py b/tests/test_rag.py index 035e8d7b..cd626aef 100644 --- a/tests/test_rag.py +++ b/tests/test_rag.py @@ -201,6 +201,7 @@ def test_movie_actor_queries(self, knowledge_graph_setup, delete_kg): delete_kg(kg) # Verify that the average score meets the threshold + assert len(scores) > 0, "No scores were collected" average_score = sum(scores) / len(scores) logger.info(f"Average Score: {average_score}") assert average_score >= 0.5, f"Average score {average_score} is below threshold of 0.5" \ No newline at end of file From 6fcf78338f2d814c8788efdcebab3fccf16c293b Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 15 Jan 2026 16:18:55 +0000 Subject: [PATCH 132/136] Bump astral-sh/setup-uv from 4 to 7 Bumps [astral-sh/setup-uv](https://github.com/astral-sh/setup-uv) from 4 to 7. - [Release notes](https://github.com/astral-sh/setup-uv/releases) - [Commits](https://github.com/astral-sh/setup-uv/compare/v4...v7) --- updated-dependencies: - dependency-name: astral-sh/setup-uv dependency-version: '7' dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/pypi-publish.yaml | 2 +- .github/workflows/test.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/pypi-publish.yaml b/.github/workflows/pypi-publish.yaml index 4269830d..f870765a 100644 --- a/.github/workflows/pypi-publish.yaml +++ b/.github/workflows/pypi-publish.yaml @@ -16,7 +16,7 @@ jobs: python-version: '3.11' - name: Install uv - uses: astral-sh/setup-uv@v4 + uses: astral-sh/setup-uv@v7 - name: Build package run: uv build diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index b3dea72a..f599f895 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -38,7 +38,7 @@ jobs: python-version: 3.11.0 # Update with desired Python version - name: Install uv - uses: astral-sh/setup-uv@v4 + uses: astral-sh/setup-uv@v7 with: enable-cache: true cache-dependency-glob: "uv.lock" From ec932741df3ef0019bac9ae9877c7dc2f7c32adf Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 15 Jan 2026 16:18:59 +0000 Subject: [PATCH 133/136] Bump rojopolis/spellcheck-github-actions from 0.56.0 to 0.57.0 Bumps [rojopolis/spellcheck-github-actions](https://github.com/rojopolis/spellcheck-github-actions) from 0.56.0 to 0.57.0. - [Release notes](https://github.com/rojopolis/spellcheck-github-actions/releases) - [Changelog](https://github.com/rojopolis/spellcheck-github-actions/blob/master/CHANGELOG.md) - [Commits](https://github.com/rojopolis/spellcheck-github-actions/compare/0.56.0...0.57.0) --- updated-dependencies: - dependency-name: rojopolis/spellcheck-github-actions dependency-version: 0.57.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- .github/workflows/spellcheck.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/spellcheck.yml b/.github/workflows/spellcheck.yml index 4123b7d8..87c36144 100644 --- a/.github/workflows/spellcheck.yml +++ b/.github/workflows/spellcheck.yml @@ -11,7 +11,7 @@ jobs: - name: Checkout uses: actions/checkout@v6 - name: Check Spelling - uses: rojopolis/spellcheck-github-actions@0.56.0 + uses: rojopolis/spellcheck-github-actions@0.57.0 with: config_path: .spellcheck.yml task_name: Markdown From 7dab65715d93c5aa2f48a2be13c93a3c6e8eef34 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 15 Jan 2026 16:19:16 +0000 Subject: [PATCH 134/136] Update sphinx-rtd-theme requirement Updates the requirements on [sphinx-rtd-theme](https://github.com/readthedocs/sphinx_rtd_theme) to permit the latest version. - [Changelog](https://github.com/readthedocs/sphinx_rtd_theme/blob/master/docs/changelog.rst) - [Commits](https://github.com/readthedocs/sphinx_rtd_theme/compare/2.0.0...3.1.0) --- updated-dependencies: - dependency-name: sphinx-rtd-theme dependency-version: 3.1.0 dependency-type: direct:development ... Signed-off-by: dependabot[bot] --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index fb3efbef..05313c88 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,7 +42,7 @@ test = [ ] dev = [ "sphinx>=7.3.7,<8.0.0", - "sphinx-rtd-theme>=2.0.0,<3.0.0", + "sphinx-rtd-theme>=2.0.0,<4.0.0", "pandas>=2.2.2,<3.0.0", "jupyter>=1.0.0,<2.0.0", "ipykernel>=6.29.5,<8.0.0", From 63aab07bfd2e53495eb8239ed139a30c40463071 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 15 Jan 2026 16:19:22 +0000 Subject: [PATCH 135/136] Bump pypdf from 5.9.0 to 6.6.0 in the uv group across 1 directory Bumps the uv group with 1 update in the / directory: [pypdf](https://github.com/py-pdf/pypdf). Updates `pypdf` from 5.9.0 to 6.6.0 - [Release notes](https://github.com/py-pdf/pypdf/releases) - [Changelog](https://github.com/py-pdf/pypdf/blob/main/CHANGELOG.md) - [Commits](https://github.com/py-pdf/pypdf/compare/5.9.0...6.6.0) --- updated-dependencies: - dependency-name: pypdf dependency-version: 6.6.0 dependency-type: direct:production dependency-group: uv ... Signed-off-by: dependabot[bot] --- pyproject.toml | 2 +- requirements.txt | 2 +- uv.lock | 8 ++++---- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index fb3efbef..c516eecb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,7 +24,7 @@ dependencies = [ "falkordb>=1.0.9,<2.0.0", "typing-extensions>=4.12.1,<5.0.0", "beautifulsoup4>=4.12.3,<5.0.0", - "pypdf>=5.9.0,<6.0.0", + "pypdf>=5.9.0,<7.0.0", "backoff>=2.2.1,<3.0.0", "requests>=2.32.3,<3.0.0", "ratelimit>=2.2.1,<3.0.0", diff --git a/requirements.txt b/requirements.txt index 55028dec..c952afd0 100644 --- a/requirements.txt +++ b/requirements.txt @@ -12,7 +12,7 @@ beautifulsoup4>=4.12.3,<5.0.0 falkordb>=1.0.9,<2.0.0 fix-busted-json>=0.0.18,<0.0.19 litellm>=1.73.1,<2.0.0 -pypdf>=5.9.0,<6.0.0 +pypdf>=5.9.0,<7.0.0 python-dotenv>=1.0.1,<2.0.0 ratelimit>=2.2.1,<3.0.0 rdflib>=7.0.0,<8.0.0 diff --git a/uv.lock b/uv.lock index 4a9e3dfd..90a00ba7 100644 --- a/uv.lock +++ b/uv.lock @@ -916,7 +916,7 @@ requires-dist = [ { name = "jupyter", marker = "extra == 'dev'", specifier = ">=1.0.0,<2.0.0" }, { name = "litellm", specifier = ">=1.73.1,<2.0.0" }, { name = "pandas", marker = "extra == 'dev'", specifier = ">=2.2.2,<3.0.0" }, - { name = "pypdf", specifier = ">=5.9.0,<6.0.0" }, + { name = "pypdf", specifier = ">=5.9.0,<7.0.0" }, { name = "pytest", marker = "extra == 'test'", specifier = ">=8.2.1,<9.0.0" }, { name = "python-dotenv", specifier = ">=1.0.1,<2.0.0" }, { name = "ratelimit", specifier = ">=2.2.1,<3.0.0" }, @@ -2626,14 +2626,14 @@ wheels = [ [[package]] name = "pypdf" -version = "5.9.0" +version = "6.6.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "typing-extensions", marker = "python_full_version < '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/89/3a/584b97a228950ed85aec97c811c68473d9b8d149e6a8c155668287cf1a28/pypdf-5.9.0.tar.gz", hash = "sha256:30f67a614d558e495e1fbb157ba58c1de91ffc1718f5e0dfeb82a029233890a1", size = 5035118, upload-time = "2025-07-27T14:04:52.364Z" } +sdist = { url = "https://files.pythonhosted.org/packages/d8/f4/801632a8b62a805378b6af2b5a3fcbfd8923abf647e0ed1af846a83433b2/pypdf-6.6.0.tar.gz", hash = "sha256:4c887ef2ea38d86faded61141995a3c7d068c9d6ae8477be7ae5de8a8e16592f", size = 5281063, upload-time = "2026-01-09T11:20:11.786Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/48/d9/6cff57c80a6963e7dd183bf09e9f21604a77716644b1e580e97b259f7612/pypdf-5.9.0-py3-none-any.whl", hash = "sha256:be10a4c54202f46d9daceaa8788be07aa8cd5ea8c25c529c50dd509206382c35", size = 313193, upload-time = "2025-07-27T14:04:50.53Z" }, + { url = "https://files.pythonhosted.org/packages/b2/ba/96f99276194f720e74ed99905a080f6e77810558874e8935e580331b46de/pypdf-6.6.0-py3-none-any.whl", hash = "sha256:bca9091ef6de36c7b1a81e09327c554b7ce51e88dad68f5890c2b4a4417f1fd7", size = 328963, upload-time = "2026-01-09T11:20:09.278Z" }, ] [[package]] From 7fdd9ded6e136f3bfd5f579cc5dc6365af1551bf Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Sun, 18 Jan 2026 14:56:02 +0000 Subject: [PATCH 136/136] Initial plan