mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-02 11:50:37 +08:00
405 lines
20 KiB
Python
405 lines
20 KiB
Python
import copy
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import datetime
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from collections import OrderedDict
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from functools import partial
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from typing import List, Tuple
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from jinja2 import Environment, StrictUndefined
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from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
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from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
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from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
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from pr_agent.algo.token_handler import TokenHandler
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from pr_agent.algo.utils import convert_to_markdown, load_yaml, ModelType
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from pr_agent.config_loader import get_settings
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from pr_agent.git_providers import get_git_provider
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from pr_agent.git_providers.git_provider import IncrementalPR, get_main_pr_language
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from pr_agent.log import get_logger
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from pr_agent.servers.help import HelpMessage
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class PRReviewer:
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"""
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The PRReviewer class is responsible for reviewing a pull request and generating feedback using an AI model.
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"""
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def __init__(self, pr_url: str, is_answer: bool = False, is_auto: bool = False, args: list = None,
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ai_handler: partial[BaseAiHandler,] = LiteLLMAIHandler):
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"""
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Initialize the PRReviewer object with the necessary attributes and objects to review a pull request.
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Args:
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pr_url (str): The URL of the pull request to be reviewed.
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is_answer (bool, optional): Indicates whether the review is being done in answer mode. Defaults to False.
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is_auto (bool, optional): Indicates whether the review is being done in automatic mode. Defaults to False.
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ai_handler (BaseAiHandler): The AI handler to be used for the review. Defaults to None.
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args (list, optional): List of arguments passed to the PRReviewer class. Defaults to None.
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"""
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self.args = args
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self.parse_args(args) # -i command
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self.git_provider = get_git_provider()(pr_url, incremental=self.incremental)
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self.main_language = get_main_pr_language(
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self.git_provider.get_languages(), self.git_provider.get_files()
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)
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self.pr_url = pr_url
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self.is_answer = is_answer
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self.is_auto = is_auto
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if self.is_answer and not self.git_provider.is_supported("get_issue_comments"):
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raise Exception(f"Answer mode is not supported for {get_settings().config.git_provider} for now")
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self.ai_handler = ai_handler()
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self.patches_diff = None
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self.prediction = None
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answer_str, question_str = self._get_user_answers()
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self.vars = {
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"title": self.git_provider.pr.title,
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"branch": self.git_provider.get_pr_branch(),
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"description": self.git_provider.get_pr_description(),
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"language": self.main_language,
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"diff": "", # empty diff for initial calculation
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"require_score": get_settings().pr_reviewer.require_score_review,
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"require_tests": get_settings().pr_reviewer.require_tests_review,
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"require_focused": get_settings().pr_reviewer.require_focused_review,
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"require_estimate_effort_to_review": get_settings().pr_reviewer.require_estimate_effort_to_review,
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'num_code_suggestions': get_settings().pr_reviewer.num_code_suggestions,
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'question_str': question_str,
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'answer_str': answer_str,
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"extra_instructions": get_settings().pr_reviewer.extra_instructions,
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"commit_messages_str": self.git_provider.get_commit_messages(),
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"custom_labels": "",
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"enable_custom_labels": get_settings().config.enable_custom_labels,
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}
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self.token_handler = TokenHandler(
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self.git_provider.pr,
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self.vars,
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get_settings().pr_review_prompt.system,
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get_settings().pr_review_prompt.user
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)
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def parse_args(self, args: List[str]) -> None:
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"""
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Parse the arguments passed to the PRReviewer class and set the 'incremental' attribute accordingly.
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Args:
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args: A list of arguments passed to the PRReviewer class.
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Returns:
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None
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"""
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is_incremental = False
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if args and len(args) >= 1:
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arg = args[0]
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if arg == "-i":
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is_incremental = True
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self.incremental = IncrementalPR(is_incremental)
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async def run(self) -> None:
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try:
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if self.incremental.is_incremental and not self._can_run_incremental_review():
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return None
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if isinstance(self.args, list) and self.args and self.args[0] == 'auto_approve':
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get_logger().info(f'Auto approve flow PR: {self.pr_url} ...')
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self.auto_approve_logic()
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return None
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get_logger().info(f'Reviewing PR: {self.pr_url} ...')
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relevant_configs = {'pr_reviewer': dict(get_settings().pr_reviewer),
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'config': dict(get_settings().config)}
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get_logger().debug("Relevant configs", configs=relevant_configs)
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if get_settings().config.publish_output:
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self.git_provider.publish_comment("Preparing review...", is_temporary=True)
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await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO)
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if not self.prediction:
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self.git_provider.remove_initial_comment()
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return None
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pr_review = self._prepare_pr_review()
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get_logger().debug(f"PR output", review=pr_review)
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if get_settings().config.publish_output:
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previous_review_comment = self._get_previous_review_comment()
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# publish the review
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if get_settings().pr_reviewer.persistent_comment and not self.incremental.is_incremental:
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self.git_provider.publish_persistent_comment(pr_review,
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initial_header="## PR Review",
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update_header=True)
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else:
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self.git_provider.publish_comment(pr_review)
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self.git_provider.remove_initial_comment()
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if previous_review_comment:
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self._remove_previous_review_comment(previous_review_comment)
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if get_settings().pr_reviewer.inline_code_comments:
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self._publish_inline_code_comments()
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except Exception as e:
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get_logger().error(f"Failed to review PR: {e}")
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async def _prepare_prediction(self, model: str) -> None:
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self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model)
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if self.patches_diff:
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get_logger().debug(f"PR diff", diff=self.patches_diff)
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self.prediction = await self._get_prediction(model)
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else:
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get_logger().error(f"Error getting PR diff")
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self.prediction = None
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async def _get_prediction(self, model: str) -> str:
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"""
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Generate an AI prediction for the pull request review.
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Args:
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model: A string representing the AI model to be used for the prediction.
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Returns:
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A string representing the AI prediction for the pull request review.
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"""
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variables = copy.deepcopy(self.vars)
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variables["diff"] = self.patches_diff # update diff
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environment = Environment(undefined=StrictUndefined)
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system_prompt = environment.from_string(get_settings().pr_review_prompt.system).render(variables)
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user_prompt = environment.from_string(get_settings().pr_review_prompt.user).render(variables)
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response, finish_reason = await self.ai_handler.chat_completion(
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model=model,
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temperature=0.2,
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system=system_prompt,
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user=user_prompt
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)
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get_logger().debug(f"\nAI response:\n{response}")
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return response
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def _prepare_pr_review(self) -> str:
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"""
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Prepare the PR review by processing the AI prediction and generating a markdown-formatted text that summarizes
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the feedback.
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"""
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data = load_yaml(self.prediction.strip())
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if 'code_feedback' in data:
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code_feedback = data['code_feedback']
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# Filter out code suggestions that can be submitted as inline comments
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if get_settings().pr_reviewer.inline_code_comments:
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del data['code_feedback']
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else:
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for suggestion in code_feedback:
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if ('relevant_file' in suggestion) and (not suggestion['relevant_file'].startswith('``')):
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suggestion['relevant_file'] = f"``{suggestion['relevant_file']}``"
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if 'relevant_line' not in suggestion:
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suggestion['relevant_line'] = ''
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relevant_line_str = suggestion['relevant_line'].split('\n')[0]
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# removing '+'
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suggestion['relevant_line'] = relevant_line_str.lstrip('+').strip()
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# try to add line numbers link to code suggestions
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if hasattr(self.git_provider, 'generate_link_to_relevant_line_number'):
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link = self.git_provider.generate_link_to_relevant_line_number(suggestion)
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if link:
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suggestion['relevant_line'] = f"[{suggestion['relevant_line']}]({link})"
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else:
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pass
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# Add incremental review section
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if self.incremental.is_incremental:
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last_commit_url = f"{self.git_provider.get_pr_url()}/commits/" \
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f"{self.git_provider.incremental.first_new_commit_sha}"
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last_commit_msg = self.incremental.commits_range[0].commit.message if self.incremental.commits_range else ""
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incremental_review_markdown_text = f"Starting from commit {last_commit_url}"
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if last_commit_msg:
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replacement = last_commit_msg.splitlines(keepends=False)[0].replace('_', r'\_')
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incremental_review_markdown_text += f" \n_({replacement})_"
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data = OrderedDict(data)
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data.update({'Incremental PR Review': {
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"⏮️ Review for commits since previous PR-Agent review": incremental_review_markdown_text}})
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data.move_to_end('Incremental PR Review', last=False)
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markdown_text = convert_to_markdown(data, self.git_provider.is_supported("gfm_markdown"))
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# Add help text if gfm_markdown is supported
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if self.git_provider.is_supported("gfm_markdown") and get_settings().pr_reviewer.enable_help_text:
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markdown_text += "<hr>\n\n<details> <summary><strong>✨ Review tool usage guide:</strong></summary><hr> \n\n"
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markdown_text += HelpMessage.get_review_usage_guide()
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markdown_text += "\n</details>\n"
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# Add custom labels from the review prediction (effort, security)
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self.set_review_labels(data)
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if markdown_text == None or len(markdown_text) == 0:
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markdown_text = ""
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return markdown_text
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def _publish_inline_code_comments(self) -> None:
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"""
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Publishes inline comments on a pull request with code suggestions generated by the AI model.
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"""
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if get_settings().pr_reviewer.num_code_suggestions == 0:
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return
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data = load_yaml(self.prediction.strip(),
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keys_fix_yaml=["estimated_effort_to_review_[1-5]:", "security_concerns:", "possible_issues:",
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"relevant_file:", "relevant_line:", "suggestion:"])
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comments: List[str] = []
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for suggestion in data.get('PR Feedback', {}).get('Code feedback', []):
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relevant_file = suggestion.get('relevant_file', '').strip()
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relevant_line_in_file = suggestion.get('relevant_line', '').strip()
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content = suggestion.get('suggestion', '')
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if not relevant_file or not relevant_line_in_file or not content:
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get_logger().info("Skipping inline comment with missing file/line/content")
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continue
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if self.git_provider.is_supported("create_inline_comment"):
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comment = self.git_provider.create_inline_comment(content, relevant_file, relevant_line_in_file)
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if comment:
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comments.append(comment)
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else:
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self.git_provider.publish_inline_comment(content, relevant_file, relevant_line_in_file)
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if comments:
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self.git_provider.publish_inline_comments(comments)
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def _get_user_answers(self) -> Tuple[str, str]:
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"""
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Retrieves the question and answer strings from the discussion messages related to a pull request.
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Returns:
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A tuple containing the question and answer strings.
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"""
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question_str = ""
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answer_str = ""
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if self.is_answer:
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discussion_messages = self.git_provider.get_issue_comments()
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for message in discussion_messages.reversed:
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if "Questions to better understand the PR:" in message.body:
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question_str = message.body
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elif '/answer' in message.body:
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answer_str = message.body
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if answer_str and question_str:
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break
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return question_str, answer_str
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def _get_previous_review_comment(self):
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"""
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Get the previous review comment if it exists.
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"""
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try:
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if get_settings().pr_reviewer.remove_previous_review_comment and hasattr(self.git_provider, "get_previous_review"):
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return self.git_provider.get_previous_review(
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full=not self.incremental.is_incremental,
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incremental=self.incremental.is_incremental,
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)
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except Exception as e:
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get_logger().exception(f"Failed to get previous review comment, error: {e}")
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def _remove_previous_review_comment(self, comment):
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"""
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Remove the previous review comment if it exists.
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"""
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try:
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if get_settings().pr_reviewer.remove_previous_review_comment and comment:
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self.git_provider.remove_comment(comment)
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except Exception as e:
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get_logger().exception(f"Failed to remove previous review comment, error: {e}")
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def _can_run_incremental_review(self) -> bool:
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"""Checks if we can run incremental review according the various configurations and previous review"""
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# checking if running is auto mode but there are no new commits
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if self.is_auto and not self.incremental.first_new_commit_sha:
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get_logger().info(f"Incremental review is enabled for {self.pr_url} but there are no new commits")
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return False
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# checking if there are enough commits to start the review
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num_new_commits = len(self.incremental.commits_range)
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num_commits_threshold = get_settings().pr_reviewer.minimal_commits_for_incremental_review
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not_enough_commits = num_new_commits < num_commits_threshold
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# checking if the commits are not too recent to start the review
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recent_commits_threshold = datetime.datetime.now() - datetime.timedelta(
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minutes=get_settings().pr_reviewer.minimal_minutes_for_incremental_review
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)
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last_seen_commit_date = (
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self.incremental.last_seen_commit.commit.author.date if self.incremental.last_seen_commit else None
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)
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all_commits_too_recent = (
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last_seen_commit_date > recent_commits_threshold if self.incremental.last_seen_commit else False
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)
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# check all the thresholds or just one to start the review
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condition = any if get_settings().pr_reviewer.require_all_thresholds_for_incremental_review else all
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if condition((not_enough_commits, all_commits_too_recent)):
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get_logger().info(
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f"Incremental review is enabled for {self.pr_url} but didn't pass the threshold check to run:"
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f"\n* Number of new commits = {num_new_commits} (threshold is {num_commits_threshold})"
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f"\n* Last seen commit date = {last_seen_commit_date} (threshold is {recent_commits_threshold})"
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)
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return False
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return True
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def set_review_labels(self, data):
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if (get_settings().pr_reviewer.enable_review_labels_security or
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get_settings().pr_reviewer.enable_review_labels_effort):
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try:
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review_labels = []
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if get_settings().pr_reviewer.enable_review_labels_effort:
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estimated_effort = data['review']['estimated_effort_to_review_[1-5]']
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estimated_effort_number = int(estimated_effort.split(',')[0])
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if 1 <= estimated_effort_number <= 5: # 1, because ...
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review_labels.append(f'Review effort [1-5]: {estimated_effort_number}')
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if get_settings().pr_reviewer.enable_review_labels_security:
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security_concerns = data['review']['security_concerns'] # yes, because ...
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security_concerns_bool = 'yes' in security_concerns.lower() or 'true' in security_concerns.lower()
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if security_concerns_bool:
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review_labels.append('Possible security concern')
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current_labels = self.git_provider.get_pr_labels()
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if current_labels:
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current_labels_filtered = [label for label in current_labels if
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not label.lower().startswith('review effort [1-5]:') and not label.lower().startswith(
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'possible security concern')]
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else:
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current_labels_filtered = []
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if current_labels or review_labels:
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get_logger().debug(f"Current labels:\n{current_labels}")
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get_logger().info(f"Setting review labels:\n{review_labels + current_labels_filtered}")
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self.git_provider.publish_labels(review_labels + current_labels_filtered)
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except Exception as e:
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get_logger().error(f"Failed to set review labels, error: {e}")
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def auto_approve_logic(self):
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"""
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Auto-approve a pull request if it meets the conditions for auto-approval.
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"""
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if get_settings().pr_reviewer.enable_auto_approval:
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maximal_review_effort = get_settings().pr_reviewer.maximal_review_effort
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if maximal_review_effort < 5:
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current_labels = self.git_provider.get_pr_labels()
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for label in current_labels:
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if label.lower().startswith('review effort [1-5]:'):
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effort = int(label.split(':')[1].strip())
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if effort > maximal_review_effort:
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get_logger().info(
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f"Auto-approve error: PR review effort ({effort}) is higher than the maximal review effort "
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f"({maximal_review_effort}) allowed")
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self.git_provider.publish_comment(
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f"Auto-approve error: PR review effort ({effort}) is higher than the maximal review effort "
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f"({maximal_review_effort}) allowed")
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return
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is_auto_approved = self.git_provider.auto_approve()
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if is_auto_approved:
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get_logger().info("Auto-approved PR")
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self.git_provider.publish_comment("Auto-approved PR")
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else:
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get_logger().info("Auto-approval option is disabled")
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self.git_provider.publish_comment("Auto-approval option for PR-Agent is disabled. "
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"You can enable it via a [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/docs/REVIEW.md#auto-approval-1)") |