diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index baff1db72..2acfb8d6a 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -143,13 +143,14 @@ jobs: if: steps.cached-poetry-dependencies.outputs.cache-hit != 'true' run: poetry install --no-interaction --only main --extras rag - - name: Propose relevant file to issues - run: | - poetry run patchwork ResolveIssue --log debug \ - --patched_api_key=${{ secrets.PATCHED_API_KEY }} \ - --github_api_key=${{ secrets.SCM_GITHUB_KEY }} \ - --issue_url=https://github.com/patched-codes/patchwork/issues/20 \ - --disable_telemetry +# disabled because this currently takes too long +# - name: Resolve issue +# run: | +# poetry run patchwork ResolveIssue --log debug \ +# --patched_api_key=${{ secrets.PATCHED_API_KEY }} \ +# --github_api_key=${{ secrets.SCM_GITHUB_KEY }} \ +# --issue_url=https://github.com/patched-codes/patchwork/issues/1039 \ +# --disable_telemetry main-test: runs-on: ubuntu-latest diff --git a/patchwork/common/client/llm/aio.py b/patchwork/common/client/llm/aio.py index cdb9714c3..fa8691193 100644 --- a/patchwork/common/client/llm/aio.py +++ b/patchwork/common/client/llm/aio.py @@ -1,13 +1,21 @@ from __future__ import annotations +import os + from openai.types.chat import ( ChatCompletion, ChatCompletionMessageParam, + ChatCompletionToolChoiceOptionParam, + ChatCompletionToolParam, completion_create_params, ) from typing_extensions import Dict, Iterable, List, Optional, Union +from patchwork.common.client.llm.anthropic import AnthropicLlmClient +from patchwork.common.client.llm.google import GoogleLlmClient +from patchwork.common.client.llm.openai_ import OpenAiLlmClient from patchwork.common.client.llm.protocol import NOT_GIVEN, LlmClient, NotGiven +from patchwork.common.constants import DEFAULT_PATCH_URL from patchwork.logger import logger @@ -29,10 +37,43 @@ def get_models(self) -> set[str]: def is_model_supported(self, model: str) -> bool: return any(client.is_model_supported(model) for client in self.__clients) - def is_prompt_supported(self, messages: Iterable[ChatCompletionMessageParam], model: str) -> int: + def is_prompt_supported( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ) -> int: for client in self.__clients: if client.is_model_supported(model): - return client.is_prompt_supported(messages, model) + return client.is_prompt_supported( + messages=messages, + model=model, + frequency_penalty=frequency_penalty, + logit_bias=logit_bias, + logprobs=logprobs, + max_tokens=max_tokens, + n=n, + presence_penalty=presence_penalty, + response_format=response_format, + stop=stop, + temperature=temperature, + tools=tools, + tool_choice=tool_choice, + top_logprobs=top_logprobs, + top_p=top_p, + ) return -1 def truncate_messages( @@ -56,6 +97,8 @@ def chat_completion( response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, ) -> ChatCompletion: @@ -74,6 +117,8 @@ def chat_completion( response_format, stop, temperature, + tools, + tool_choice, top_logprobs, top_p, ) @@ -82,3 +127,33 @@ def chat_completion( f"Model {model} is not supported by {client_names} clients. " f"Please ensure that the respective API keys are correct." ) + + @staticmethod + def create_aio_client(inputs) -> "AioLlmClient" | None: + clients = [] + + patched_key = inputs.get("patched_api_key") + if patched_key is not None: + client = OpenAiLlmClient(patched_key, DEFAULT_PATCH_URL) + clients.append(client) + + openai_key = inputs.get("openai_api_key") or os.environ.get("OPENAI_API_KEY") + if openai_key is not None: + client_args = {key[len("client_") :]: value for key, value in inputs.items() if key.startswith("client_")} + client = OpenAiLlmClient(openai_key, **client_args) + clients.append(client) + + google_key = inputs.get("google_api_key") + if google_key is not None: + client = GoogleLlmClient(google_key) + clients.append(client) + + anthropic_key = inputs.get("anthropic_api_key") + if anthropic_key is not None: + client = AnthropicLlmClient(anthropic_key) + clients.append(client) + + if len(clients) == 0: + return None + + return AioLlmClient(*clients) diff --git a/patchwork/common/client/llm/anthropic.py b/patchwork/common/client/llm/anthropic.py index 583cdcc0c..081445c67 100644 --- a/patchwork/common/client/llm/anthropic.py +++ b/patchwork/common/client/llm/anthropic.py @@ -5,11 +5,13 @@ from functools import lru_cache from anthropic import Anthropic -from anthropic.types import Message, TextBlockParam +from anthropic.types import Message, MessageParam, TextBlockParam from openai.types.chat import ( ChatCompletion, ChatCompletionMessage, ChatCompletionMessageParam, + ChatCompletionToolChoiceOptionParam, + ChatCompletionToolParam, completion_create_params, ) from openai.types.chat.chat_completion import Choice, CompletionUsage @@ -81,6 +83,119 @@ def __get_model_limit(self, model: str) -> int: return 100_000 - safety_margin return 200_000 - safety_margin + def __adapt_input_messages(self, messages: Iterable[ChatCompletionMessageParam]) -> list[MessageParam]: + new_messages = [] + for message in messages: + if message.get("role") == "system": + if system is NOT_GIVEN: + system = list() + system.append(TextBlockParam(text=message.get("content"), type="text")) + elif message.get("role") == "tool": + new_messages.append( + dict( + role="user", + content=[ + dict( + type="tool_result", + tool_use_id=message.get("tool_call_id"), + content=message.get("content"), + ) + ], + ) + ) + elif message.get("role") == "assistant" and len(message.get("tool_calls", [])) > 0: + tool_calls = message["tool_calls"] + tool_calls_as_content = [ + dict( + type="tool_use", + id=tool_call["id"], + name=tool_call["function"]["name"], + input=json.loads(tool_call["function"]["arguments"]), + ) + for tool_call in tool_calls + ] + new_messages.append( + dict( + role="assistant", + content=[ + *tool_calls_as_content, + ], + ) + ) + else: + new_messages.append(message) + + return new_messages + + def __adapt_chat_completion_request( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ): + system: Union[str, Iterable[TextBlockParam]] | NotGiven = NOT_GIVEN + adapted_messages = self.__adapt_input_messages(messages) + default_max_token = 1000 + + if tool_choice is not NOT_GIVEN: + # openai tool choice to anthropic tool choice mapping: + # openai : none, auto, required , required + # anthropic: NA , auto, any , tool + if isinstance(tool_choice, str): + if tool_choice == "required": + tool_choice = dict(type="any") + elif tool_choice == "none": + tool_choice = NOT_GIVEN + else: + tool_choice = dict(type=tool_choice) + else: + tool_choice_type = tool_choice.get("type") + if tool_choice_type == "required": + if tool_choice.get("function") is not None: + tool_choice["type"] = "tool" + tool_choice["name"] = tool_choice["function"]["name"] + else: + tool_choice["type"] = "any" + elif tool_choice_type == "none": + tool_choice = NOT_GIVEN + + input_kwargs = dict( + messages=adapted_messages, + system=system, + max_tokens=default_max_token if max_tokens is None or max_tokens is NOT_GIVEN else max_tokens, + model=model, + stop_sequences=[stop] if isinstance(stop, str) else stop, + temperature=temperature, + tools=[tool.get("function") for tool in tools if tool.get("function") is not None], + tool_choice=tool_choice, + top_p=top_p, + ) + + if response_format is not NOT_GIVEN and response_format.get("type") == "json_schema": + input_kwargs["tool_choice"] = dict(type="tool", name="response_format") + if input_kwargs.get("tools") is NOT_GIVEN: + input_kwargs["tools"] = list() + response_format_tool = dict( + name="response_format", + description="The response format to use", + input_schema=response_format["json_schema"]["schema"], + ) + input_kwargs["tools"] = [*input_kwargs["tools"], response_format_tool] + + return NotGiven.remove_not_given(input_kwargs) + @lru_cache(maxsize=None) def get_models(self) -> set[str]: return self.__definitely_allowed_models.union(set(f"{self.__allowed_model_prefix}*")) @@ -88,16 +203,49 @@ def get_models(self) -> set[str]: def is_model_supported(self, model: str) -> bool: return model in self.__definitely_allowed_models or model.startswith(self.__allowed_model_prefix) - def is_prompt_supported(self, messages: Iterable[ChatCompletionMessageParam], model: str) -> int: + def is_prompt_supported( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ) -> int: model_limit = self.__get_model_limit(model) - token_count = 0 - for message in messages: - message_token_count = self.client.count_tokens(message.get("content")) - token_count = token_count + message_token_count - if token_count > model_limit: - return -1 - - return model_limit - token_count + input_kwargs = self.__adapt_chat_completion_request( + messages=messages, + model=model, + frequency_penalty=frequency_penalty, + logit_bias=logit_bias, + logprobs=logprobs, + max_tokens=max_tokens, + n=n, + presence_penalty=presence_penalty, + response_format=response_format, + stop=stop, + temperature=temperature, + tools=tools, + tool_choice=tool_choice, + top_logprobs=top_logprobs, + top_p=top_p, + ) + count_token_input_kwargs = { + k: v + for k, v in input_kwargs.items() + if k in {"messages", "model", "system", "tool_choice", "tools", "beta"} + } + message_token_count = self.client.beta.messages.count_tokens(**count_token_input_kwargs) + return model_limit - message_token_count.input_tokens def truncate_messages( self, messages: Iterable[ChatCompletionMessageParam], model: str @@ -117,38 +265,28 @@ def chat_completion( response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, ) -> ChatCompletion: - system: Union[str, Iterable[TextBlockParam]] | NotGiven = NOT_GIVEN - other_messages = [] - for message in messages: - if message.get("role") == "system": - if system is NOT_GIVEN: - system = list() - system.append(TextBlockParam(text=message.get("content"), type="text")) - else: - other_messages.append(message) - - default_max_token = 1000 - input_kwargs = dict( - messages=other_messages, - system=system, - max_tokens=default_max_token if max_tokens is None or max_tokens is NOT_GIVEN else max_tokens, + input_kwargs = self.__adapt_chat_completion_request( + messages=messages, model=model, - stop_sequences=[stop] if isinstance(stop, str) else stop, + frequency_penalty=frequency_penalty, + logit_bias=logit_bias, + logprobs=logprobs, + max_tokens=max_tokens, + n=n, + presence_penalty=presence_penalty, + response_format=response_format, + stop=stop, temperature=temperature, + tools=tools, + tool_choice=tool_choice, + top_logprobs=top_logprobs, top_p=top_p, ) - if response_format is not NOT_GIVEN and response_format.get("type") == "json_schema": - input_kwargs["tool_choice"] = dict(type="tool", name="response_format") - input_kwargs["tools"] = [ - dict( - name="response_format", - description="The response format to use", - input_schema=response_format["json_schema"]["schema"], - ) - ] - response = self.client.messages.create(**NotGiven.remove_not_given(input_kwargs)) + response = self.client.messages.create(**input_kwargs) return _anthropic_to_openai_response(model, response) diff --git a/patchwork/common/client/llm/google.py b/patchwork/common/client/llm/google.py index 6949135c5..80884451e 100644 --- a/patchwork/common/client/llm/google.py +++ b/patchwork/common/client/llm/google.py @@ -16,6 +16,8 @@ from openai.types.chat import ( ChatCompletionMessage, ChatCompletionMessageParam, + ChatCompletionToolChoiceOptionParam, + ChatCompletionToolParam, completion_create_params, ) from openai.types.chat.chat_completion import ChatCompletion, Choice @@ -55,7 +57,24 @@ def get_models(self) -> set[str]: def is_model_supported(self, model: str) -> bool: return model in self.get_models() - def is_prompt_supported(self, messages: Iterable[ChatCompletionMessageParam], model: str) -> int: + def is_prompt_supported( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ) -> int: system, chat = self.__openai_messages_to_google_messages(messages) gen_model = generativeai.GenerativeModel(model_name=model, system_instruction=system) try: @@ -96,9 +115,11 @@ def chat_completion( max_tokens: Optional[int] | NotGiven = NOT_GIVEN, n: Optional[int] | NotGiven = NOT_GIVEN, presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, - response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + response_format: str | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, ) -> ChatCompletion: diff --git a/patchwork/common/client/llm/openai_.py b/patchwork/common/client/llm/openai_.py index 1ce603f0a..6573ee24e 100644 --- a/patchwork/common/client/llm/openai_.py +++ b/patchwork/common/client/llm/openai_.py @@ -7,6 +7,8 @@ from openai.types.chat import ( ChatCompletion, ChatCompletionMessageParam, + ChatCompletionToolChoiceOptionParam, + ChatCompletionToolParam, completion_create_params, ) from typing_extensions import Dict, Iterable, List, Optional, Union @@ -29,7 +31,7 @@ def _cached_list_models_from_openai(api_key): class OpenAiLlmClient(LlmClient): __MODEL_LIMITS = { "gpt-3.5-turbo": 16_385, - "gpt-4 ": 8_192, + "gpt-4": 8_192, "gpt-4-turbo": 8_192, "o1-mini": 128_000, "gpt-4o-mini": 128_000, @@ -61,7 +63,24 @@ def is_model_supported(self, model: str) -> bool: def __get_model_limits(self, model: str) -> int: return self.__MODEL_LIMITS.get(model, 128_000) - def is_prompt_supported(self, messages: Iterable[ChatCompletionMessageParam], model: str) -> int: + def is_prompt_supported( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ) -> int: # might not implement model endpoint if self.__is_not_openai_url(): return 1 @@ -95,6 +114,8 @@ def chat_completion( response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, ) -> ChatCompletion: @@ -110,6 +131,8 @@ def chat_completion( response_format=response_format, stop=stop, temperature=temperature, + tools=tools, + tool_choice=tool_choice, top_logprobs=top_logprobs, top_p=top_p, ) diff --git a/patchwork/common/client/llm/protocol.py b/patchwork/common/client/llm/protocol.py index ff02b685a..51d0da1fc 100644 --- a/patchwork/common/client/llm/protocol.py +++ b/patchwork/common/client/llm/protocol.py @@ -3,6 +3,8 @@ from openai.types.chat import ( ChatCompletion, ChatCompletionMessageParam, + ChatCompletionToolChoiceOptionParam, + ChatCompletionToolParam, completion_create_params, ) from typing_extensions import Any, Dict, Iterable, List, Optional, Protocol, Union @@ -32,7 +34,24 @@ def get_models(self) -> set[str]: def is_model_supported(self, model: str) -> bool: ... - def is_prompt_supported(self, messages: Iterable[ChatCompletionMessageParam], model: str) -> int: + def is_prompt_supported( + self, + messages: Iterable[ChatCompletionMessageParam], + model: str, + frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, + logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, + logprobs: Optional[bool] | NotGiven = NOT_GIVEN, + max_tokens: Optional[int] | NotGiven = NOT_GIVEN, + n: Optional[int] | NotGiven = NOT_GIVEN, + presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, + response_format: dict | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, + stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, + temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, + top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, + top_p: Optional[float] | NotGiven = NOT_GIVEN, + ) -> int: ... def truncate_messages( @@ -112,6 +131,8 @@ def chat_completion( response_format: str | completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, + tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, + tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, ) -> ChatCompletion: diff --git a/patchwork/common/multiturn_strategy/__init__.py b/patchwork/common/multiturn_strategy/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/patchwork/common/multiturn_strategy/analyze_implement.py b/patchwork/common/multiturn_strategy/analyze_implement.py new file mode 100644 index 000000000..3686eaec6 --- /dev/null +++ b/patchwork/common/multiturn_strategy/analyze_implement.py @@ -0,0 +1,93 @@ +from __future__ import annotations + +import random +import string +from abc import abstractmethod +from collections import defaultdict +from enum import Enum, auto + +import chevron +from openai.types.chat import ChatCompletionMessageParam + +from patchwork.common.client.llm.protocol import LlmClient +from patchwork.common.multiturn_strategy.multiturn_strategy import MultiturnStrategy +from patchwork.common.tools import Tool + + +class STAGE(Enum): + ANALYSIS = auto() + IMPLEMENT = auto() + + +class AnalyzeImplementStrategy(MultiturnStrategy): + def __init__( + self, + tool_set: dict[str, Tool], + llm_client: LlmClient, + initial_template_data: dict[str, str], + analysis_prompt_template: str, + implementation_prompt_template: str, + **kwargs, + ): + super().__init__(tool_set=tool_set, **kwargs) + self.llm_client = llm_client + self.template_data = initial_template_data + self.analysis_prompt_template = analysis_prompt_template + self.implementation_prompt_template = implementation_prompt_template + self._reset() + + def _reset(self): + self._stage = STAGE.ANALYSIS + self.run_count = 0 + self.stage_run_counts = defaultdict(int) + + def __run_prompt(self, messages: list[ChatCompletionMessageParam]) -> list[ChatCompletionMessageParam]: + input_kwargs = dict( + messages=messages, + model="claude-3-5-sonnet-latest", + tools=self.get_tools_spec(), + max_tokens=8096, + ) + is_prompt_safe = self.llm_client.is_prompt_supported(**input_kwargs) + if is_prompt_safe < 0: + raise ValueError("The subsequent prompt is not supported, due to large size.") + response = self.llm_client.chat_completion(**input_kwargs) + new_messages = [choice.message.to_dict() for choice in response.choices] + messages.extend(new_messages) + return messages + + def __render_prompt(self, prompt: str) -> str: + chevron.render.__globals__["_html_escape"] = lambda string: string + return chevron.render( + template=prompt, + data=self.template_data, + partials_path=None, + partials_ext="".join(random.choices(string.ascii_uppercase + string.digits, k=32)), + partials_dict=dict(), + ) + + def run_initial_prompt(self) -> list[ChatCompletionMessageParam]: + initial_prompt = self.__render_prompt(self.analysis_prompt_template) + messages = [dict(role="user", content=initial_prompt)] + return self.__run_prompt(messages) + + def run_subsequent_prompt(self, messages: list[ChatCompletionMessageParam]) -> list[ChatCompletionMessageParam]: + last_message = messages[-1] + if self._stage == STAGE.ANALYSIS: + possible_analysis_message = self.extract_analysis_message(last_message) + if possible_analysis_message is not None: + self._stage = STAGE.IMPLEMENT + self.template_data["analysis_results"] = possible_analysis_message + implement_prompt = self.__render_prompt(self.implementation_prompt_template) + messages = [dict(role="user", content=implement_prompt)] + return self.__run_prompt(messages) + + if last_message.get("tool_calls") is not None: + tool_messages = self.execute_tools(last_message) + messages.extend(tool_messages) + messages.append(dict(role="user", content=f"Continue with the {self._stage.name.upper()} stage.")) + return self.__run_prompt(messages) + + @abstractmethod + def extract_analysis_message(self, message: ChatCompletionMessageParam) -> dict[str, str]: + pass diff --git a/patchwork/common/multiturn_strategy/multiturn_strategy.py b/patchwork/common/multiturn_strategy/multiturn_strategy.py new file mode 100644 index 000000000..70094fb67 --- /dev/null +++ b/patchwork/common/multiturn_strategy/multiturn_strategy.py @@ -0,0 +1,74 @@ +from __future__ import annotations + +import json +import logging +import sys +from abc import ABC, abstractmethod +from json import JSONDecodeError + +from openai.types.chat.chat_completion_message import ChatCompletionMessage +from openai.types.chat.chat_completion_message_param import ChatCompletionMessageParam +from openai.types.chat.chat_completion_tool_param import ChatCompletionToolParam + +from patchwork.common.tools import Tool + + +class MultiturnStrategy(ABC): + def __init__(self, tool_set: dict[str, Tool], limit: int | None = None, *args, **kwargs): + self.tool_set = tool_set + self.limit = limit + self.run_count = 0 + + def get_tools_spec(self) -> list[ChatCompletionToolParam]: + return [ + dict( + type="function", + function={"name": k, **v.json_schema}, + ) + for k, v in self.tool_set.items() + ] + + @abstractmethod + def run_initial_prompt(self) -> tuple[ChatCompletionMessage, list[ChatCompletionMessageParam]]: + pass + + @abstractmethod + def run_subsequent_prompt(self, messages: list[ChatCompletionMessageParam]) -> list[ChatCompletionMessageParam]: + pass + + def is_stop(self, messages: list[ChatCompletionMessageParam]) -> bool: + return False + + def execute_tools(self, last_message: ChatCompletionMessageParam) -> list[ChatCompletionMessageParam]: + rv = [] + for tool_call in last_message.get("tool_calls", []): + tool_name_to_use = tool_call.get("function", {}).get("name") + tool_to_use = self.tool_set.get(tool_name_to_use, None) + if tool_to_use is None: + logging.info("LLM just used an non-existent tool!") + continue + + logging.info(f"Running tool: {tool_name_to_use}") + try: + tool_arguments = tool_call.get("function", {}).get("arguments", "{}") + tool_kwargs = json.loads(tool_arguments) + tool_output = tool_to_use.execute(**tool_kwargs) + except JSONDecodeError: + tool_output = "Arguments must be passed through a valid JSON object" + + rv.append({"tool_call_id": tool_call.get("id", ""), "role": "tool", "content": tool_output}) + + return rv + + def execute(self, limit: int | None = None) -> None: + messages = self.run_initial_prompt() + try: + for i in range(limit or self.limit or sys.maxsize): + self.run_count = i + 1 + if self.is_stop(messages): + break + messages = self.run_subsequent_prompt(messages) + except Exception as e: + logging.error(e) + finally: + self.run_count = 0 diff --git a/patchwork/common/tools/__init__.py b/patchwork/common/tools/__init__.py new file mode 100644 index 000000000..e813cb9d9 --- /dev/null +++ b/patchwork/common/tools/__init__.py @@ -0,0 +1,9 @@ +from patchwork.common.tools.bash_tool import BashTool +from patchwork.common.tools.code_edit_tools import CodeEditTool +from patchwork.common.tools.tool import Tool + +__all__ = [ + "Tool", + "CodeEditTool", + "BashTool", +] diff --git a/patchwork/common/tools/bash_tool.py b/patchwork/common/tools/bash_tool.py new file mode 100644 index 000000000..cd6c51fa9 --- /dev/null +++ b/patchwork/common/tools/bash_tool.py @@ -0,0 +1,53 @@ +from __future__ import annotations + +import subprocess +from pathlib import Path + +from patchwork.common.tools.tool import Tool + + +class BashTool(Tool, tool_name="bash"): + def __init__(self, path: str): + super().__init__() + self.path = Path(path) + self.modified_files = [] + + @property + def json_schema(self) -> dict: + return { + "name": "bash", + "description": """Run commands in a bash shell + +* When invoking this tool, the contents of the "command" parameter does NOT need to be XML-escaped. +* You don't have access to the internet via this tool. +* You do have access to a mirror of common linux and python packages via apt and pip. +* State is persistent across command calls and discussions with the user. +* To inspect a particular line range of a file, e.g. lines 10-25, try 'sed -n 10,25p /path/to/the/file'. +* Please avoid commands that may produce a very large amount of output. +* Please run long lived commands in the background, e.g. 'sleep 10 &' or start a server in the background.""", + "input_schema": { + "type": "object", + "properties": {"command": {"type": "string", "description": "The bash command to run."}}, + "required": ["command"], + }, + } + + def execute( + self, + command: str | None = None, + *args, + **kwargs, + ) -> str: + """Execute editor commands on files in the repository.""" + if command is None: + return f"Error: `command` parameter must be set and cannot be empty" + + try: + result = subprocess.run( + command, shell=True, cwd=self.path, capture_output=True, text=True, timeout=60 # Add timeout for safety + ) + return result.stdout if result.returncode == 0 else f"Error: {result.stderr}" + except subprocess.TimeoutExpired: + return "Error: Command timed out after 60 seconds" + except Exception as e: + return f"Error: {str(e)}" diff --git a/patchwork/common/tools/code_edit_tools.py b/patchwork/common/tools/code_edit_tools.py new file mode 100644 index 000000000..6f3b7658d --- /dev/null +++ b/patchwork/common/tools/code_edit_tools.py @@ -0,0 +1,178 @@ +from __future__ import annotations + +import os +from pathlib import Path +from typing import Literal + +from patchwork.common.tools.tool import Tool + + +class CodeEditTool(Tool, tool_name="code_edit_tool"): + def __init__(self, path: str): + super().__init__() + self.repo_path = Path(path) + self.modified_files = set() + + @property + def json_schema(self) -> dict: + return { + "name": "code_edit_tool", + "description": """Custom editing tool for viewing, creating and editing files + +* State is persistent across command calls and discussions with the user +* If `path` is a file, `view` displays the result of applying `cat -n`. If `path` is a directory, `view` lists non-hidden files and directories up to 2 levels deep +* The `create` command cannot be used if the specified `path` already exists as a file +* If a `command` generates a long output, it will be truncated and marked with `` +* The `undo_edit` command will revert the last edit made to the file at `path` + +Notes for using the `str_replace` command: +* The `old_str` parameter should match EXACTLY one or more consecutive lines from the original file. Be mindful of whitespaces! +* If the `old_str` parameter is not unique in the file, the replacement will not be performed. Make sure to include enough context in `old_str` to make it unique +* The `new_str` parameter should contain the edited lines that should replace the `old_str`""", + "input_schema": { + "type": "object", + "properties": { + "command": { + "type": "string", + "enum": ["view", "create", "str_replace", "insert", "undo_edit"], + "description": "The commands to run. Allowed options are: `view`, `create`, `str_replace`, `insert`, `undo_edit`.", + }, + "file_text": { + "description": "Required parameter of `create` command, with the content of the file to be created.", + "type": "string", + }, + "insert_line": { + "description": "Required parameter of `insert` command. The `new_str` will be inserted AFTER the line `insert_line` of `path`.", + "type": "integer", + }, + "new_str": { + "description": "Required parameter of `str_replace` command containing the new string. Required parameter of `insert` command containing the string to insert.", + "type": "string", + }, + "old_str": { + "description": "Required parameter of `str_replace` command containing the string in `path` to replace.", + "type": "string", + }, + "path": { + "description": "Absolute path to file or directory, e.g. `/repo/file.py` or `/repo`.", + "type": "string", + }, + "view_range": { + "description": "Optional parameter of `view` command when `path` points to a file. If none is given, the full file is shown. If provided, the file will be shown in the indicated line number range, e.g. [11, 12] will show lines 11 and 12. Indexing at 1 to start. Setting `[start_line, -1]` shows all lines from `start_line` to the end of the file.", + "items": {"type": "integer"}, + "type": "array", + }, + }, + "required": ["command", "path"], + }, + } + + def execute( + self, + command: Literal["view", "create", "str_replace", "insert"] | None = None, + file_text: str = "", + insert_line: int | None = None, + new_str: str = "", + old_str: str | None = None, + path: str | None = None, + view_range: list[int] | None = None, + *args, + **kwargs, + ) -> str: + """Execute editor commands on files in the repository.""" + required_dict = dict(command=command, path=path) + missing_required = {k for k, v in required_dict.items() if v is None} + if len(missing_required) > 0: + return f"Error: `{'` and `'.join(missing_required)}` parameters must be set and cannot be empty" + + try: + if command == "view": + result = self.__view(path, view_range) + elif command == "create": + result = self.__create(file_text, path) + elif command == "str_replace": + result = self.__str_replace(new_str, old_str, path) + elif command == "insert": + result = self.__insert(insert_line, new_str, path) + else: + return f"Error: Unknown action {command}" + + if command in {"create", "str_replace", "insert"}: + self.modified_files.update({path.lstrip("/")}) + + return result + + except Exception as e: + return f"Error: {str(e)}" + + @property + def tool_records(self): + return dict(modified_files=[{"path": file} for file in self.modified_files]) + + def __get_abs_path(self, path: str): + abs_path = (self.repo_path / path.lstrip("/")).resolve() + if not abs_path.is_relative_to(self.repo_path): + raise ValueError(f"Path {path} contains illegal path traversal") + + return abs_path + + def __view(self, path, view_range): + abs_path = self.__get_abs_path(path) + if not abs_path.exists(): + return f"Error: Path {path} does not exist" + + if abs_path.is_file(): + with open(abs_path, "r") as f: + content = f.read() + + if view_range: + lines = content.splitlines() + start, end = view_range + content = "\n".join(lines[start - 1 : end]) + return content + elif abs_path.is_dir(): + result = [] + for root, dirs, files in os.walk(abs_path): + level = root[len(str(abs_path)) :].count(os.sep) + if level <= 2: + for d in dirs: + result.append(d) + for f in files: + result.append(f) + return "\n".join(result) + + def __create(self, file_text, path): + abs_path = self.__get_abs_path(path) + if abs_path.exists(): + return f"Error: File {path} already exists" + abs_path.parent.mkdir(parents=True, exist_ok=True) + abs_path.write_text(file_text) + return f"File created successfully at: {path}" + + def __str_replace(self, new_str, old_str, path): + abs_path = self.__get_abs_path(path) + if not abs_path.exists(): + return f"Error: File {path} does not exist" + if not abs_path.is_file(): + return f"Error: File {path} is not a file" + content = abs_path.read_text() + occurrences = content.count(old_str) + if occurrences != 1: + return f"Error: Found {occurrences} occurrences of old_str, expected exactly 1" + new_content = content.replace(old_str, new_str) + with open(abs_path, "w") as f: + f.write(new_content) + return "Replacement successful" + + def __insert(self, insert_line, new_str, path): + abs_path = self.__get_abs_path(path) + if not abs_path.is_file(): + return f"Error: File {path} does not exist or is not a file" + + lines = abs_path.read_text().splitlines(keepends=True) + if insert_line is None or insert_line < 1 or insert_line > len(lines): + return f"Error: Invalid insert line {insert_line}" + + lines.insert(insert_line, new_str + "\n") + abs_path.write_text("".join(lines)) + return "Insert successful" diff --git a/patchwork/common/tools/tool.py b/patchwork/common/tools/tool.py new file mode 100644 index 000000000..ad7e62989 --- /dev/null +++ b/patchwork/common/tools/tool.py @@ -0,0 +1,41 @@ +from abc import ABC, abstractmethod +from typing import Type + + +class Tool(ABC): + __internal_map: dict[str, Type["Tool"]] = dict() + + def __init_subclass__(cls, tool_name=None, **kwargs): + cls_name = tool_name or cls.__name__ + if cls_name in cls.__internal_map.keys(): + raise ValueError(f"Duplicate subclass name for class {cls.__name__}: {cls_name}") + cls.name = cls_name + Tool.__internal_map[cls_name] = cls + + @property + @abstractmethod + def json_schema(self) -> dict: + ... + + @abstractmethod + def execute(self, *args, **kwargs) -> str: + ... + + @staticmethod + def get_tools(**kwargs) -> dict[str, "Tool"]: + rv = dict() + for k, v in Tool.__internal_map.items(): + try: + rv[k] = v(**kwargs) + except Exception as e: + continue + + return rv + + @staticmethod + def get_description(tooling: "ToolProtocol") -> str: + return tooling.json_schema.get("description", "") + + @staticmethod + def get_parameters(tooling: "ToolProtocol") -> str: + return ", ".join(tooling.json_schema.get("required", [])) diff --git a/patchwork/common/utils/filter_paths.py b/patchwork/common/utils/filter_paths.py index 928e5a609..d511350fe 100644 --- a/patchwork/common/utils/filter_paths.py +++ b/patchwork/common/utils/filter_paths.py @@ -35,7 +35,9 @@ class PathFilter: - def __init__(self, base_path: str | Path = Path.cwd(), ignored_groks: set[str] | None = None, max_depth: int = -1): + def __init__( + self, *, base_path: str | Path = Path.cwd(), ignored_groks: set[str] | None = None, max_depth: int = -1 + ): self.base_path = Path(base_path) self.max_depth = max_depth self.__ignored_groks = ignored_groks if ignored_groks is not None else set() @@ -59,6 +61,12 @@ def __get_gitignore_ignored_groks(self) -> set[str]: return ignored_groks def get_grok_ignored(self, file_to_test: str | Path) -> str | None: + """ + Get the grok string that causes the file to be ignored + + :param file_to_test: file to test if it is ignored because of depth level + :return: Grok string if the file is ignored else None + """ file = Path(file_to_test) paths_to_test = [file] + list(file.parents) for ignored_grok in self.__ignored_groks: @@ -68,10 +76,17 @@ def get_grok_ignored(self, file_to_test: str | Path) -> str | None: return None def get_depth_ignored(self, file_to_test: str | Path) -> int | None: - file = Path(file_to_test) + """ + Get depth of file that causes the file to be ignored. + + :param file_to_test: file to test if it is ignored because of depth level + :return: Depth of file if the file is ignored else None. + """ if self.max_depth == -1: return None + file = Path(file_to_test) + try: file_depth = len(file.relative_to(self.base_path).parts) except ValueError: diff --git a/patchwork/patchflows/GenerateDiagram/GenerateDiagram.py b/patchwork/patchflows/GenerateDiagram/GenerateDiagram.py index 0062d5f4d..b59b95ee1 100644 --- a/patchwork/patchflows/GenerateDiagram/GenerateDiagram.py +++ b/patchwork/patchflows/GenerateDiagram/GenerateDiagram.py @@ -1,19 +1,15 @@ -import json from pathlib import Path + import yaml from patchwork.common.utils.step_typing import validate_steps_with_inputs from patchwork.step import Step -from patchwork.steps import ( - LLM, - CallCode2Prompt, - ModifyCode, - PR -) +from patchwork.steps import LLM, PR, CallCode2Prompt, ModifyCode _DEFAULT_INPUT_FILE = Path(__file__).parent / "defaults.yml" _DEFAULT_PROMPT_JSON = Path(__file__).parent / "default_prompt.json" + class GenerateDiagram(Step): def __init__(self, inputs): super().__init__(inputs) @@ -21,7 +17,7 @@ def __init__(self, inputs): final_inputs = yaml.safe_load(_DEFAULT_INPUT_FILE.read_text()) if final_inputs is None: final_inputs = {} - + final_inputs.update(inputs) final_inputs["prompt_id"] = "GenerateDiagram" @@ -33,7 +29,7 @@ def __init__(self, inputs): final_inputs["branch_prefix"] = f"{self.__class__.__name__.lower()}-" validate_steps_with_inputs( - set(final_inputs.keys()).union({"prompt_values","files_to_patch"}), LLM, CallCode2Prompt,ModifyCode,PR + set(final_inputs.keys()).union({"prompt_values", "files_to_patch"}), LLM, CallCode2Prompt, ModifyCode, PR ) self.base_path = final_inputs["base_path"] @@ -41,7 +37,7 @@ def __init__(self, inputs): def run(self): outputs = CallCode2Prompt(self.inputs).run() - outputs['uri'] = self.base_path + outputs["uri"] = self.base_path self.inputs["response_partitions"] = {"patch": ["```", "\n", "```"]} self.inputs["files_to_patch"] = self.inputs["prompt_values"] = [outputs] outputs = LLM(self.inputs).run() diff --git a/patchwork/patchflows/GenerateUnitTests/GenerateUnitTests.py b/patchwork/patchflows/GenerateUnitTests/GenerateUnitTests.py index c344d3030..b82abe294 100644 --- a/patchwork/patchflows/GenerateUnitTests/GenerateUnitTests.py +++ b/patchwork/patchflows/GenerateUnitTests/GenerateUnitTests.py @@ -1,19 +1,15 @@ -import json from pathlib import Path + import yaml from patchwork.common.utils.step_typing import validate_steps_with_inputs from patchwork.step import Step -from patchwork.steps import ( - LLM, - CallCode2Prompt, - ModifyCode, - PR -) +from patchwork.steps import LLM, PR, CallCode2Prompt, ModifyCode _DEFAULT_INPUT_FILE = Path(__file__).parent / "defaults.yml" _DEFAULT_PROMPT_JSON = Path(__file__).parent / "default_prompt.json" + class GenerateUnitTests(Step): def __init__(self, inputs): super().__init__(inputs) @@ -21,7 +17,7 @@ def __init__(self, inputs): final_inputs = yaml.safe_load(_DEFAULT_INPUT_FILE.read_text()) if final_inputs is None: final_inputs = {} - + final_inputs.update(inputs) final_inputs["prompt_id"] = "GenerateUnitTests" @@ -37,16 +33,16 @@ def __init__(self, inputs): final_inputs["branch_prefix"] = f"{self.__class__.__name__.lower()}-" validate_steps_with_inputs( - set(final_inputs.keys()).union({"prompt_values","files_to_patch"}), LLM, CallCode2Prompt,ModifyCode,PR + set(final_inputs.keys()).union({"prompt_values", "files_to_patch"}), LLM, CallCode2Prompt, ModifyCode, PR ) self.inputs = final_inputs def run(self): outputs = CallCode2Prompt(self.inputs).run() new_file_name = f"test_file.{self.inputs['test_file_extension']}" - new_file_path = Path(outputs['uri']).with_name(new_file_name) - Path(outputs['uri']).rename(new_file_path) - outputs['uri'] = str(new_file_path) + new_file_path = Path(outputs["uri"]).with_name(new_file_name) + Path(outputs["uri"]).rename(new_file_path) + outputs["uri"] = str(new_file_path) self.inputs["response_partitions"] = {"patch": ["```", "\n", "```"]} self.inputs["files_to_patch"] = self.inputs["prompt_values"] = [outputs] outputs = LLM(self.inputs).run() diff --git a/patchwork/patchflows/ResolveIssue/ResolveIssue.py b/patchwork/patchflows/ResolveIssue/ResolveIssue.py index 3ba28ea2e..22bef8101 100644 --- a/patchwork/patchflows/ResolveIssue/ResolveIssue.py +++ b/patchwork/patchflows/ResolveIssue/ResolveIssue.py @@ -5,123 +5,38 @@ from patchwork.common.utils.progress_bar import PatchflowProgressBar from patchwork.common.utils.step_typing import validate_steps_with_inputs from patchwork.step import Step -from patchwork.steps import ( - LLM, - PR, - CallLLM, - CommitChanges, - CreateIssueComment, - CreatePR, - ExtractModelResponse, - GenerateCodeRepositoryEmbeddings, - ModifyCode, - PreparePR, - PreparePrompt, - QueryEmbeddings, - ReadIssues, -) +from patchwork.steps import PR, FixIssue, ReadIssues _DEFAULT_INPUT_FILE = Path(__file__).parent / "defaults.yml" -_DEFAULT_PROMPT_JSON = Path(__file__).parent / "prompt.json" class ResolveIssue(Step): def __init__(self, inputs: dict): PatchflowProgressBar(self).register_steps( - CallLLM, - CommitChanges, - CreateIssueComment, - CreatePR, - ExtractModelResponse, - GenerateCodeRepositoryEmbeddings, - ModifyCode, - PreparePR, - PreparePrompt, - QueryEmbeddings, ReadIssues, + FixIssue, + PR, ) - final_inputs = yaml.safe_load(_DEFAULT_INPUT_FILE.read_text()) - - if final_inputs is None: - final_inputs = {} + final_inputs = yaml.safe_load(_DEFAULT_INPUT_FILE.read_text()) or dict() final_inputs.update(inputs) - if "prompt_template_file" not in final_inputs.keys(): - final_inputs["prompt_template_file"] = _DEFAULT_PROMPT_JSON - final_inputs["pr_title"] = f"PatchWork {self.__class__.__name__}" final_inputs["branch_prefix"] = f"{self.__class__.__name__.lower()}-" validate_steps_with_inputs( - set(final_inputs.keys()).union({"texts", "issue_text"}), - GenerateCodeRepositoryEmbeddings, + {"issue_description"}.union(final_inputs.keys()), ReadIssues, - QueryEmbeddings, - CreateIssueComment, + FixIssue, + PR, ) - self.fix_issue = bool(final_inputs.get("fix_issue", False)) self.inputs = final_inputs def run(self) -> dict: - outputs = GenerateCodeRepositoryEmbeddings(self.inputs).run() - self.inputs.update(outputs) - outputs = ReadIssues(self.inputs).run() + self.inputs["issue_description"] = outputs + outputs = FixIssue(self.inputs).run() self.inputs.update(outputs) - - self.inputs["texts"] = self.inputs.get("issue_body") or self.inputs.get("issue_title") - - outputs = QueryEmbeddings(self.inputs).run() - self.inputs.update(outputs) - - issue_list_text = "* " + "\n* ".join([result["path"] for result in self.inputs["embedding_results"]]) - self.inputs[ - "issue_text" - ] = f"""\ -The following files in the repository may be relevant to the issue: - ------- - -{issue_list_text} -""" - - outputs = CreateIssueComment(self.inputs).run() - self.inputs.update(outputs) - - if not self.fix_issue: - return self.inputs - - extracted_code_contexts = [] - # Call LLM to make necessary updates to files to resolve the issue - for result in self.inputs["embedding_results"]: - with open(result["path"], "r") as file: - file_content = file.read() - lines = file_content.splitlines(keepends=True) - extracted_code_contexts.append( - { - "uri": result["path"], - "startLine": 0, - "endLine": len(lines), - "affectedCode": file_content, - "messageText": self.inputs["texts"], - } - ) - - self.inputs["prompt_values"] = extracted_code_contexts - self.inputs["files_to_patch"] = extracted_code_contexts - self.inputs["prompt_id"] = "resolve_issue" - self.inputs["response_partitions"] = { - "patch": ["Fixed Code:", "```", "\n", "```"], - } - outputs = LLM(self.inputs).run() - self.inputs.update(outputs) - - # Modify code files with the suggested changes - outputs = ModifyCode(self.inputs).run() - self.inputs.update(outputs) - - # Commit changes and create PR self.inputs["pr_header"] = f'This pull request from patchwork fixes {self.inputs["issue_url"]}.' outputs = PR(self.inputs).run() self.inputs.update(outputs) diff --git a/patchwork/patchflows/__init__.py b/patchwork/patchflows/__init__.py index e5c59ec5b..3345dfec5 100644 --- a/patchwork/patchflows/__init__.py +++ b/patchwork/patchflows/__init__.py @@ -1,10 +1,19 @@ from .AutoFix.AutoFix import AutoFix from .DependencyUpgrade.DependencyUpgrade import DependencyUpgrade +from .GenerateDiagram.GenerateDiagram import GenerateDiagram from .GenerateDocstring.GenerateDocstring import GenerateDocstring from .GenerateREADME.GenerateREADME import GenerateREADME +from .GenerateUnitTests.GenerateUnitTests import GenerateUnitTests from .PRReview.PRReview import PRReview from .ResolveIssue.ResolveIssue import ResolveIssue -from .GenerateUnitTests.GenerateUnitTests import GenerateUnitTests -from .GenerateDiagram.GenerateDiagram import GenerateDiagram -__all__ = ["AutoFix", "DependencyUpgrade", "GenerateREADME", "PRReview", "ResolveIssue", "GenerateDocstring", "GenerateUnitTests","GenerateDiagram"] +__all__ = [ + "AutoFix", + "DependencyUpgrade", + "GenerateREADME", + "PRReview", + "ResolveIssue", + "GenerateDocstring", + "GenerateUnitTests", + "GenerateDiagram", +] diff --git a/patchwork/steps/CommitChanges/CommitChanges.py b/patchwork/steps/CommitChanges/CommitChanges.py index f21223fc4..3cd71c617 100644 --- a/patchwork/steps/CommitChanges/CommitChanges.py +++ b/patchwork/steps/CommitChanges/CommitChanges.py @@ -126,7 +126,7 @@ def __init__(self, inputs: dict): def __get_repo_tracked_modified_files(self, repo: Repo) -> set[Path]: repo_dir_path = Path(repo.working_tree_dir) - path_filter = PathFilter(repo.working_tree_dir) + path_filter = PathFilter(base_path=repo.working_tree_dir) repo_changed_files = set() for item in repo.index.diff(None): @@ -167,7 +167,7 @@ def run(self) -> dict: ): for modified_file in true_modified_files: repo.git.add(modified_file) - commit_with_msg(repo, f"Patched {modified_file}") + commit_with_msg(repo, f"Patched {modified_file.relative_to(repo_dir_path)}") return dict( base_branch=from_branch, diff --git a/patchwork/steps/FixIssue/FixIssue.py b/patchwork/steps/FixIssue/FixIssue.py new file mode 100644 index 000000000..cb2df70b3 --- /dev/null +++ b/patchwork/steps/FixIssue/FixIssue.py @@ -0,0 +1,127 @@ +import re +from pathlib import Path +from typing import Any, Optional + +from git import Repo +from openai.types.chat import ChatCompletionMessageParam + +from patchwork.common.client.llm.aio import AioLlmClient +from patchwork.common.client.llm.protocol import LlmClient +from patchwork.common.constants import TOKEN_URL +from patchwork.common.multiturn_strategy.analyze_implement import ( + STAGE, + AnalyzeImplementStrategy, +) +from patchwork.common.tools import CodeEditTool, Tool +from patchwork.logger import logger +from patchwork.step import Step +from patchwork.steps.FixIssue.typed import FixIssueInputs, FixIssueOutputs + + +class _ResolveIssue(AnalyzeImplementStrategy): + def __init__(self, repo_path: str, llm_client: LlmClient, issue_description: Any, **kwargs): + self.tool_set = Tool.get_tools(path=repo_path) + super().__init__( + llm_client=llm_client, + initial_template_data=dict(issue=issue_description), + analysis_prompt_template=""" +. + +I've uploaded a code repository in the current working directory (not in /tmp/inputs). + +Consider the following issue: + + +{{issue}} + + +Let's first explore and analyze the repository to understand where the issue is located. +Please analyze the repository structure and try to locate the specific files and code sections that need to be modified. + +1. First explore the repo structure +2. Identify the relevant files that likely need changes +3. Create and run a script to reproduce the error +4. Once you've confirmed the error, identify the specific code sections that need to be modified + +Provide your findings in this format: + +List the relevant files that need changes +The error reproduction script and its output +Description of the specific changes needed +""", + implementation_prompt_template=""" +. + +I've uploaded a code repository in the current working directory (not in /tmp/inputs). + +Based on our previous analysis: + + +{{analysis_results}} + + +Let's implement the necessary changes: + +1. Edit the sourcecode of the repo to resolve the issue +2. Rerun the reproduction script to confirm the error is fixed +3. Think about edge cases and make sure your fix handles them as well + +I've already taken care of all changes to any of the test files described in the PR. +This means you DON'T have to modify the testing logic or any of the tests in any way! + +Let me know when you're done by outputting .""", + tool_set=self.tool_set, + **kwargs, + ) + + def extract_analysis_message(self, message: ChatCompletionMessageParam) -> Optional[dict[str, str]]: + analysis_match = re.search(r"(.*?)", message.get("content"), re.DOTALL) + if not analysis_match: + return None + + content = analysis_match.group(1) + sections = dict() + for section in ["files", "error_reproduction", "changes_needed"]: + section_match = re.search(f"<{section}>(.*?)", content, re.DOTALL) + sections[section] = section_match.group(1).strip() if section_match else "" + return sections + + def is_stop(self, messages: list[ChatCompletionMessageParam]) -> bool: + if self._stage != STAGE.IMPLEMENT: + return False + last_message = messages[-1] + return "" in last_message.get("content") + + +class FixIssue(Step, input_class=FixIssueInputs, output_class=FixIssueOutputs): + def __init__(self, inputs): + super().__init__(inputs) + self.base_path = inputs.get("base_path") + if self.base_path is None: + repo = Repo(Path.cwd(), search_parent_directories=True) + self.base_path = repo.working_tree_dir + + llm_client = AioLlmClient.create_aio_client(inputs) + if llm_client is None: + raise ValueError( + f"Model API key not found.\n" + f'Please login at: "{TOKEN_URL}",\n' + "Please go to the Integration's tab and generate an API key.\n" + "Please copy the access token that is generated, " + "and add `--patched_api_key=` to the command line.\n" + "\n" + "If you are using an OpenAI API Key, please set `--openai_api_key=`.\n" + ) + + self.multiturn_llm_call = _ResolveIssue( + repo_path=self.base_path, + llm_client=llm_client, + issue_description=inputs["issue_description"], + ) + + def run(self): + self.multiturn_llm_call.execute(limit=100) + for tool in self.multiturn_llm_call.tool_set.values(): + if isinstance(tool, CodeEditTool): + return tool.tool_records + return dict() diff --git a/patchwork/steps/FixIssue/README.md b/patchwork/steps/FixIssue/README.md new file mode 100644 index 000000000..bb6bb8c57 --- /dev/null +++ b/patchwork/steps/FixIssue/README.md @@ -0,0 +1,57 @@ +# `FixIssue` Module Documentation + +This documentation provides an overview of the `FixIssue` module in the `patchwork/steps/FixIssue/` directory, detailing its purpose, inputs, and outputs for developers working with the code. + +## Overview + +The FixIssue module is part of a system aimed at automating the analysis and resolution of coding issues within a software repository. It leverages language model clients (such as OpenAI's API) to understand the code structure, identify problems, propose changes, and test them. The module defines input and output data structures and contains the main logic for analyzing and fixing code issues. + +## Components + +The module is divided into several components: + +- **typed.py**: Defines the input and output data structure types needed for the FixIssue step. +- **FixIssue.py**: Contains the main implementation logic to carry out issue analysis and resolution. +- **__init__.py**: Placeholder for package initialization, currently empty. + +## Inputs + +### FixIssueInputs + +Defined in `typed.py`, this structure specifies the necessary inputs for the module: + +- **Required** + - `issue_description` (str): A description of the coding issue to be resolved. + +- **Optional** (with conditions via `Annotated` attributes): + - `base_path` (str): The base path to the repository (marked as a path). + - `openai_api_key` (str): API key for OpenAI services. + - `anthropic_api_key` (str): API key for Anthropic services. + - `patched_api_key` (str): API key alternative, includes a message prompt if not present. + - `google_api_key` (str): API key for Google services. + +## Outputs + +### FixIssueOutputs + +Defined in `typed.py`, representing the output of the FixIssue step: + +- `modified_files` (List[Dict]): A list of modified files and their respective changes made by the tool. + +## Usage + +The typical usage involves defining inputs, initializing the `FixIssue` class, and executing the `run()` method to process the issue. This would be suitable for development automation tools or CI/CD pipelines that automatically resolve identified code issues. + +## Functions and Classes + +### _ResolveIssue + +A private class that extends `AnalyzeImplementStrategy`, implementing the logic to analyze and fix issues identified within a repository. It interacts with the codebase and uses language models for guidance. + +### FixIssue + +A `Step` subclass that orchestrates the setup of environment and execution of issue resolution based on the provided inputs. It initializes configurations, clients, and strategies, and runs the multiturn language model operation until the issue is resolved. + +## Conclusion + +The `FixIssue` module is a sophisticated tool designed for automated issue detection and correction in software repositories. It wraps around advanced language models to offer intelligent analysis and implementations, thereby enhancing the code maintenance process. diff --git a/patchwork/steps/FixIssue/__init__.py b/patchwork/steps/FixIssue/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/patchwork/steps/FixIssue/typed.py b/patchwork/steps/FixIssue/typed.py new file mode 100644 index 000000000..7c88e21b5 --- /dev/null +++ b/patchwork/steps/FixIssue/typed.py @@ -0,0 +1,39 @@ +from typing_extensions import Annotated, Dict, TypedDict, List + +from patchwork.common.constants import TOKEN_URL +from patchwork.common.utils.step_typing import StepTypeConfig + + +class __FixIssueRequiredInputs(TypedDict): + issue_description: str + + +class FixIssueInputs(__FixIssueRequiredInputs, total=False): + base_path: Annotated[str, StepTypeConfig(is_path=True)] + openai_api_key: Annotated[ + str, StepTypeConfig(is_config=True, or_op=["patched_api_key", "google_api_key", "anthropic_api_key"]) + ] + anthropic_api_key: Annotated[ + str, StepTypeConfig(is_config=True, or_op=["patched_api_key", "google_api_key", "openai_api_key"]) + ] + patched_api_key: Annotated[ + str, + StepTypeConfig( + is_config=True, + or_op=["openai_api_key", "google_api_key", "anthropic_api_key"], + msg=f"""\ +Model API key not found. +Please login at: "{TOKEN_URL}" +Please go to the Integration's tab and generate an API key. +Please copy the access token that is generated, and add `--patched_api_key=` to the command line. + +If you are using a OpenAI API Key, please set `--openai_api_key=`.""", + ), + ] + google_api_key: Annotated[ + str, StepTypeConfig(is_config=True, or_op=["patched_api_key", "openai_api_key", "anthropic_api_key"]) + ] + + +class FixIssueOutputs(TypedDict): + modified_files: List[Dict] diff --git a/patchwork/steps/ModifyCode/ModifyCode.py b/patchwork/steps/ModifyCode/ModifyCode.py index d8a2251d2..f7c6d7e4f 100644 --- a/patchwork/steps/ModifyCode/ModifyCode.py +++ b/patchwork/steps/ModifyCode/ModifyCode.py @@ -88,7 +88,7 @@ def run(self) -> dict: if new_code is None: continue - + replace_code_in_file(uri, start_line, end_line, new_code) modified_code_file = dict(path=uri, start_line=start_line, end_line=end_line, **extracted_response) modified_code_files.append(modified_code_file) diff --git a/patchwork/steps/PreparePrompt/PreparePrompt.py b/patchwork/steps/PreparePrompt/PreparePrompt.py index 6c71cf468..a9d78767a 100644 --- a/patchwork/steps/PreparePrompt/PreparePrompt.py +++ b/patchwork/steps/PreparePrompt/PreparePrompt.py @@ -6,14 +6,11 @@ from pathlib import Path import chevron -from chevron import render from patchwork.common.constants import PROMPT_TEMPLATE_FILE_KEY from patchwork.logger import logger from patchwork.step import Step, StepStatus -chevron.render.__globals__["_html_escape"] = lambda string: string - def _find_by_prompt_template_file(prompt_template_file: str | None, prompt_id: str | None) -> list[dict] | None: if prompt_template_file is None or prompt_id is None: @@ -79,6 +76,7 @@ def run(self) -> dict: return dict(prompts=[]) prompts = [] + chevron.render.__globals__["_html_escape"] = lambda string: string for prompt_value in self.prompt_values: dict_value = prompt_value if not isinstance(dict_value, dict): @@ -88,7 +86,7 @@ def run(self) -> dict: for prompt_part in self.prompt_template: prompt_instance = {} for key, value in prompt_part.items(): - new_value = render( + new_value = chevron.render( template=value, data=dict_value, partials_path=None, diff --git a/patchwork/steps/ReadIssues/ReadIssues.py b/patchwork/steps/ReadIssues/ReadIssues.py index 921880944..63abc3809 100644 --- a/patchwork/steps/ReadIssues/ReadIssues.py +++ b/patchwork/steps/ReadIssues/ReadIssues.py @@ -34,4 +34,11 @@ def run(self) -> dict: issue_title=self.issue.get("title"), issue_body=self.issue.get("body"), issue_comments=self.issue.get("comments"), + issue_description=f"""\ +Title: +{self.issue.get("title")} + +Description: +{self.issue.get("body")} +""" ) diff --git a/patchwork/steps/ReadIssues/typed.py b/patchwork/steps/ReadIssues/typed.py index 57ac86e95..285107a45 100644 --- a/patchwork/steps/ReadIssues/typed.py +++ b/patchwork/steps/ReadIssues/typed.py @@ -17,3 +17,4 @@ class ReadIssuesOutputs(TypedDict): issue_title: str issue_body: str issue_comments: List[str] + issue_description: str diff --git a/patchwork/steps/__init__.py b/patchwork/steps/__init__.py index bb043d8af..d74629a37 100644 --- a/patchwork/steps/__init__.py +++ b/patchwork/steps/__init__.py @@ -21,6 +21,7 @@ ExtractPackageManagerFile, ) from patchwork.steps.FilterBySimilarity.FilterBySimilarity import FilterBySimilarity +from patchwork.steps.FixIssue.FixIssue import FixIssue from patchwork.steps.GenerateCodeRepositoryEmbeddings.GenerateCodeRepositoryEmbeddings import ( GenerateCodeRepositoryEmbeddings, ) @@ -87,6 +88,7 @@ "ReadPRDiffs", "ReadPRDiffsPB", "ReadPRs", + "ResolveIssue", "ScanDepscan", "ScanSemgrep", "SimplifiedLLM", diff --git a/poetry.lock b/poetry.lock index 868c1bcce..7dfae3396 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 1.8.4 and should not be changed by hand. 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-content-hash = "d8957d36b5fe7654a7cc65bad793fc54f12a0af19715a41ac42db25b04f701fe" +content-hash = "2c95f1c29e3671017b5f9ccc2f4cf42eb11481d78ffafe36cbca25758c496eb2" diff --git a/pyproject.toml b/pyproject.toml index ca94854be..5728c0ae7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "patchwork-cli" -version = "0.0.78" +version = "0.0.79" description = "" authors = ["patched.codes"] license = "AGPL" @@ -41,7 +41,7 @@ requests = "~2.31.0" chardet = "~5.2.0" attrs = "~23.2.0" google-generativeai = "~0.8.1" -anthropic = "~0.34.2" +anthropic = "~0.40.0" rich = "~13.7.1" chevron = "~0.14.0" giturlparse = "~0.12.0" diff --git a/tests/steps/test_ReadIssues.py b/tests/steps/test_ReadIssues.py index 0fa560418..0e66b5e99 100644 --- a/tests/steps/test_ReadIssues.py +++ b/tests/steps/test_ReadIssues.py @@ -9,12 +9,12 @@ ( {"github_api_key": "key"}, "patchwork.common.client.scm.GithubClient.find_issue_by_url", - dict(title="", body="github pr body", comments=["nothing", "there"]), + dict(title="", body="github pr body", comments=["nothing", "there"], description="Title:\n\n\nDescription:\ngithub pr body\n"), ), ( {"gitlab_api_key": "key"}, "patchwork.common.client.scm.GitlabClient.find_issue_by_url", - dict(title="gitlab pr title", body="", comments=["something", "here"]), + dict(title="gitlab pr title", body="", comments=["something", "here"], description="Title:\ngitlab pr title\n\nDescription:\n\n"), ), ], )