diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/BUILD b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/BUILD new file mode 100644 index 0000000000..eafb9a9a95 --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/BUILD @@ -0,0 +1 @@ +poetry_requirements(name="poetry", module_mapping={"google-genai": ["google"]}) diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/README.md b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/README.md new file mode 100644 index 0000000000..4f58b0057c --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/README.md @@ -0,0 +1,31 @@ +# LlamaIndex Postprocessor Integration: Google Rerankers + +Integrating llama-index with [Google rerankers](https://cloud.google.com/generative-ai-app-builder/docs/ranking#genappbuilder_rank-python). + +It is essential to have a project in Google Cloud Platform (GCP) and loads its credentials as explained in [here](https://google-auth.readthedocs.io/en/master/reference/google.oauth2.service_account.html). + +## Sample Usage + +```python +from llama_index.core import VectorStoreIndex, SimpleDirectoryReader +from llama_index.postprocessor.google_rerank import GoogleRerank + + +documents = SimpleDirectoryReader("./data/paul_graham/").load_data() +index = VectorStoreIndex.from_documents(documents=documents) +reranker = GoogleRerank( + top_n=3, + model_id="semantic-ranker-512-003", +) +query_engine = index.as_query_engine( + similarity_top_k=10, + node_postprocessors=[reranker], +) +response = query_engine.query( + "What did Sam Altman do in this essay?", +) + +print(response) + +print(response.source_nodes) +``` diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/BUILD b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/BUILD new file mode 100644 index 0000000000..2e35f081cd --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/BUILD @@ -0,0 +1,6 @@ +python_sources() + +resource( + name="py_typed", + source="py.typed", +) diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/__init__.py b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/__init__.py new file mode 100644 index 0000000000..9173d6d15c --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/__init__.py @@ -0,0 +1,3 @@ +from llama_index.postprocessor.google_rerank.base import GoogleRerank + +__all__ = ["GoogleRerank"] diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/base.py b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/base.py new file mode 100644 index 0000000000..ecd168e5a8 --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/llama_index/postprocessor/google_rerank/base.py @@ -0,0 +1,141 @@ +import os +import json +from enum import Enum +from typing import Any, List, Optional + +from llama_index.core.bridge.pydantic import Field, PrivateAttr +from llama_index.core.callbacks import CBEventType, EventPayload +from llama_index.core.instrumentation import get_dispatcher +from llama_index.core.instrumentation.events.rerank import ( + ReRankEndEvent, + ReRankStartEvent, +) +from llama_index.core.postprocessor.types import BaseNodePostprocessor +from llama_index.core.schema import MetadataMode, NodeWithScore, QueryBundle + +from google.oauth2 import service_account +from google.cloud import discoveryengine_v1 as discoveryengine + + +GOOGLE_SERVICE_ACCOUNT_INFO = json.load(open("google-service-account.json")) +GOOGLE_CREDENTIALS = service_account.Credentials.from_service_account_info( + GOOGLE_SERVICE_ACCOUNT_INFO +) + + +dispatcher = get_dispatcher(__name__) + + +class Models(str, Enum): + SEMANTIC_RERANK_512_003 = "semantic-ranker-512-003" + + +class GoogleRerank(BaseNodePostprocessor): + top_n: int = Field(default=2, description="Top N nodes to return.") + rerank_model_name: str = Field( + default=Models.SEMANTIC_RERANK_512_003.value, + description="The modelId of the VertexAI model to use.", + ) + _client: discoveryengine.RankServiceClient = PrivateAttr() + _ranking_config: str = PrivateAttr() + + def __init__( + self, + top_n: int = 2, + rerank_model_name: str = Models.SEMANTIC_RERANK_512_003.value, + client: Optional[discoveryengine.RankServiceClient] = None, + ranking_config: Optional[Any] = "default_ranking_config", + **kwargs: Any, + ): + super().__init__(**kwargs) + self.top_n = top_n + self.rerank_model_name = rerank_model_name + + if client: + self._client = client + else: + self._client = discoveryengine.RankServiceClient( + credentials=GOOGLE_CREDENTIALS + ) + + self._ranking_config = self._client.ranking_config_path( + project=GOOGLE_SERVICE_ACCOUNT_INFO["project_id"], + location="global", + ranking_config=ranking_config, + ) + + @classmethod + def class_name(cls) -> str: + return "GoogleRerank" + + def _postprocess_nodes( + self, + nodes: List[NodeWithScore], + query_bundle: Optional[QueryBundle] = None, + ) -> List[NodeWithScore]: + if dispatcher: + dispatcher.event( + ReRankStartEvent( + query=query_bundle, + nodes=nodes, + top_n=self.top_n, + model_name=self.rerank_model_name, + ) + ) + + if query_bundle is None: + raise ValueError("Missing query bundle in extra info.") + if len(nodes) == 0: + return [] + + with self.callback_manager.event( + CBEventType.RERANKING, + payload={ + EventPayload.NODES: nodes, + EventPayload.MODEL_NAME: self.rerank_model_name, + EventPayload.QUERY_STR: query_bundle.query_str, + EventPayload.TOP_K: self.top_n, + }, + ) as event: + + # Prepare the text sources for Google Reranker + text_sources = [] + for index, node in enumerate(nodes): + text_sources.append( + discoveryengine.RankingRecord( + id=str(index), + content=node.node.get_content(metadata_mode=MetadataMode.EMBED), + ), + ) + # change top_n if the number of nodes is less than top_n + if len(nodes) < self.top_n: + self.top_n = len(nodes) + + try: + request = discoveryengine.RankRequest( + ranking_config=self._ranking_config, + model=self.rerank_model_name, + top_n=self.top_n, + query=query_bundle.query_str, + records=text_sources, + ) + response = self._client.rank(request=request) + + results = response.records + except Exception as e: + raise RuntimeError(f"Failed to invoke VertexAI model: {e}") + + new_nodes = [] + for result in results: + index = int(result.id) + relevance_score = result.score + new_node_with_score = NodeWithScore( + node=nodes[index].node, + score=relevance_score, + ) + new_nodes.append(new_node_with_score) + + event.on_end(payload={EventPayload.NODES: new_nodes}) + + dispatcher.event(ReRankEndEvent(nodes=new_nodes)) + return new_nodes diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/poetry.lock b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/poetry.lock new file mode 100644 index 0000000000..e577fd5e93 --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/poetry.lock @@ -0,0 +1,4954 @@ +# This file 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true +exclude = ["_static", "build", "examples", "notebooks", "venv"] +ignore_missing_imports = true +python_version = "3.8" + +[tool.poetry] +authors = ["Marco Domenico Cirillo "] +description = "llama-index postprocessor googlr rerank integration" +exclude = ["**/BUILD"] +license = "MIT" +name = "llama-index-postprocessor-google-rerank" +readme = "README.md" +version = "0.1.0" + +[tool.poetry.dependencies] +google-cloud-discoveryengine = "^0.13.8" +llama-index-core = "^0.12.0" +python = ">=3.9,<4.0" + +[tool.poetry.group.dev.dependencies] +ipython = "8.10.0" +jupyter = "^1.0.0" +mypy = "0.991" +pre-commit = "3.2.0" +pylint = "2.15.10" +pytest = "7.2.1" +pytest-mock = "3.11.1" +ruff = "0.0.292" +tree-sitter-languages = "^1.8.0" +types-Deprecated = ">=0.1.0" +types-PyYAML = "^6.0.12.12" +types-protobuf = "^4.24.0.4" +types-redis = "4.5.5.0" +types-requests = "2.28.11.8" +types-setuptools = "67.1.0.0" + +[tool.poetry.group.dev.dependencies.black] +extras = ["jupyter"] +version = "<=23.9.1,>=23.7.0" + +[tool.poetry.group.dev.dependencies.codespell] +extras = ["toml"] +version = ">=v2.2.6" + +[[tool.poetry.packages]] +include = "llama_index/" diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/BUILD b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/BUILD new file mode 100644 index 0000000000..eb6148790b --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/BUILD @@ -0,0 +1,3 @@ +python_tests( + interpreter_constraints=[">=3.10"], +) diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/__init__.py b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/test_google_rerank.py b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/test_google_rerank.py new file mode 100644 index 0000000000..a5dc9b991c --- /dev/null +++ b/llama-index-integrations/postprocessor/llama-index-postprocessor-google-rerank/tests/test_google_rerank.py @@ -0,0 +1,64 @@ +from unittest import TestCase, mock + +from llama_index.core.postprocessor.types import ( + BaseNodePostprocessor, + NodeWithScore, + QueryBundle, +) +from llama_index.core.schema import TextNode +from llama_index.postprocessor.google_rerank import GoogleRerank + + +class TestGoogleRerank(TestCase): + def test_class(self): + names_of_base_classes = [b.__name__ for b in GoogleRerank.__mro__] + self.assertIn(BaseNodePostprocessor.__name__, names_of_base_classes) + + def test_bedrock_rerank(self): + exp_rerank_response = { + "records": [ + { + "id": "2", + "score": 0.9, + }, + { + "id": "3", + "score": 0.8, + }, + ] + } + + input_nodes = [ + NodeWithScore(node=TextNode(id_="1", text="first 1")), + NodeWithScore(node=TextNode(id_="2", text="first 2")), + NodeWithScore(node=TextNode(id_="3", text="last 1")), + NodeWithScore(node=TextNode(id_="4", text="last 2")), + ] + + expected_nodes = [ + NodeWithScore(node=TextNode(id_="3", text="last 1"), score=0.9), + NodeWithScore(node=TextNode(id_="4", text="last 2"), score=0.8), + ] + + reranker = GoogleRerank() + + with mock.patch.object( + reranker._client, "rerank", return_value=exp_rerank_response + ): + query_bundle = QueryBundle(query_str="last") + + actual_nodes = reranker.postprocess_nodes( + input_nodes, query_bundle=query_bundle + ) + + self.assertEqual(len(actual_nodes), len(expected_nodes)) + for actual_node_with_score, expected_node_with_score in zip( + actual_nodes, expected_nodes + ): + self.assertEqual( + actual_node_with_score.node.get_content(), + expected_node_with_score.node.get_content(), + ) + self.assertAlmostEqual( + actual_node_with_score.score, expected_node_with_score.score + )