import copy import json import logging from collections import OrderedDict from typing import Tuple, List from jinja2 import Environment, StrictUndefined from pr_agent.algo.ai_handler import AiHandler from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models from pr_agent.algo.token_handler import TokenHandler from pr_agent.algo.utils import convert_to_markdown, try_fix_json from pr_agent.config_loader import settings from pr_agent.git_providers import get_git_provider from pr_agent.git_providers.git_provider import get_main_pr_language, IncrementalPR from pr_agent.servers.help import actions_help_text, bot_help_text class PRReviewer: """ The PRReviewer class is responsible for reviewing a pull request and generating feedback using an AI model. """ def __init__(self, pr_url: str, cli_mode: bool = False, is_answer: bool = False, args: list = None): """ Initialize the PRReviewer object with the necessary attributes and objects to review a pull request. Args: pr_url (str): The URL of the pull request to be reviewed. cli_mode (bool, optional): Indicates whether the review is being done in command-line interface mode. Defaults to False. is_answer (bool, optional): Indicates whether the review is being done in answer mode. Defaults to False. args (list, optional): List of arguments passed to the PRReviewer class. Defaults to None. """ self.parse_args(args) self.git_provider = get_git_provider()(pr_url, incremental=self.incremental) self.main_language = get_main_pr_language( self.git_provider.get_languages(), self.git_provider.get_files() ) self.pr_url = pr_url self.is_answer = is_answer if self.is_answer and not self.git_provider.is_supported("get_issue_comments"): raise Exception(f"Answer mode is not supported for {settings.config.git_provider} for now") self.ai_handler = AiHandler() self.patches_diff = None self.prediction = None self.cli_mode = cli_mode answer_str, question_str = self._get_user_answers() self.vars = { "title": self.git_provider.pr.title, "branch": self.git_provider.get_pr_branch(), "description": self.git_provider.get_pr_description(), "language": self.main_language, "diff": "", # empty diff for initial calculation "require_score": settings.pr_reviewer.require_score_review, "require_tests": settings.pr_reviewer.require_tests_review, "require_security": settings.pr_reviewer.require_security_review, "require_focused": settings.pr_reviewer.require_focused_review, 'num_code_suggestions': settings.pr_reviewer.num_code_suggestions, 'question_str': question_str, 'answer_str': answer_str, } self.token_handler = TokenHandler( self.git_provider.pr, self.vars, settings.pr_review_prompt.system, settings.pr_review_prompt.user ) def parse_args(self, args: List[str]) -> None: """ Parse the arguments passed to the PRReviewer class and set the 'incremental' attribute accordingly. Args: args: A list of arguments passed to the PRReviewer class. Returns: None """ is_incremental = False if args and len(args) >= 1: arg = args[0] if arg == "-i": is_incremental = True self.incremental = IncrementalPR(is_incremental) async def review(self) -> None: """ Review the pull request and generate feedback. """ logging.info('Reviewing PR...') if settings.config.publish_output: self.git_provider.publish_comment("Preparing review...", is_temporary=True) await retry_with_fallback_models(self._prepare_prediction) logging.info('Preparing PR review...') pr_comment = self._prepare_pr_review() if settings.config.publish_output: logging.info('Pushing PR review...') self.git_provider.publish_comment(pr_comment) self.git_provider.remove_initial_comment() if settings.pr_reviewer.inline_code_comments: logging.info('Pushing inline code comments...') self._publish_inline_code_comments() async def _prepare_prediction(self, model: str) -> None: """ Prepare the AI prediction for the pull request review. Args: model: A string representing the AI model to be used for the prediction. Returns: None """ logging.info('Getting PR diff...') self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model) logging.info('Getting AI prediction...') self.prediction = await self._get_prediction(model) async def _get_prediction(self, model: str) -> str: """ Generate an AI prediction for the pull request review. Args: model: A string representing the AI model to be used for the prediction. Returns: A string representing the AI prediction for the pull request review. """ variables = copy.deepcopy(self.vars) variables["diff"] = self.patches_diff # update diff environment = Environment(undefined=StrictUndefined) system_prompt = environment.from_string(settings.pr_review_prompt.system).render(variables) user_prompt = environment.from_string(settings.pr_review_prompt.user).render(variables) if settings.config.verbosity_level >= 2: logging.info(f"\nSystem prompt:\n{system_prompt}") logging.info(f"\nUser prompt:\n{user_prompt}") response, finish_reason = await self.ai_handler.chat_completion( model=model, temperature=0.2, system=system_prompt, user=user_prompt ) return response def _prepare_pr_review(self) -> str: """ Prepare the PR review by processing the AI prediction and generating a markdown-formatted text that summarizes the feedback. """ review = self.prediction.strip() try: data = json.loads(review) except json.decoder.JSONDecodeError: data = try_fix_json(review) # Move 'Security concerns' key to 'PR Analysis' section for better display if 'PR Feedback' in data and 'Security concerns' in data['PR Feedback']: val = data['PR Feedback']['Security concerns'] del data['PR Feedback']['Security concerns'] data['PR Analysis']['Security concerns'] = val # Filter out code suggestions that can be submitted as inline comments if settings.config.git_provider != 'bitbucket' and settings.pr_reviewer.inline_code_comments and 'Code suggestions' in data['PR Feedback']: data['PR Feedback']['Code suggestions'] = [ d for d in data['PR Feedback']['Code suggestions'] if any(key not in d for key in ('relevant file', 'relevant line in file', 'suggestion content')) ] if not data['PR Feedback']['Code suggestions']: del data['PR Feedback']['Code suggestions'] # Add incremental review section if self.incremental.is_incremental: last_commit_url = f"{self.git_provider.get_pr_url()}/commits/{self.git_provider.incremental.first_new_commit_sha}" data = OrderedDict(data) data.update({'Incremental PR Review': { "⏮️ Review for commits since previous PR-Agent review": f"Starting from commit {last_commit_url}"}}) data.move_to_end('Incremental PR Review', last=False) markdown_text = convert_to_markdown(data) user = self.git_provider.get_user_id() # Add help text if not in CLI mode if not self.cli_mode: markdown_text += "\n### How to use\n" if user and '[bot]' not in user: markdown_text += bot_help_text(user) else: markdown_text += actions_help_text # Log markdown response if verbosity level is high if settings.config.verbosity_level >= 2: logging.info(f"Markdown response:\n{markdown_text}") return markdown_text def _publish_inline_code_comments(self) -> None: """ Publishes inline comments on a pull request with code suggestions generated by the AI model. """ if settings.pr_reviewer.num_code_suggestions == 0: return review = self.prediction.strip() try: data = json.loads(review) except json.decoder.JSONDecodeError: data = try_fix_json(review) comments: List[str] = [] for suggestion in data.get('PR Feedback', {}).get('Code suggestions', []): relevant_file = suggestion.get('relevant file', '').strip() relevant_line_in_file = suggestion.get('relevant line in file', '').strip() content = suggestion.get('suggestion content', '') if not relevant_file or not relevant_line_in_file or not content: logging.info("Skipping inline comment with missing file/line/content") continue if self.git_provider.is_supported("create_inline_comment"): comment = self.git_provider.create_inline_comment(content, relevant_file, relevant_line_in_file) if comment: comments.append(comment) else: self.git_provider.publish_inline_comment(content, relevant_file, relevant_line_in_file) if comments: self.git_provider.publish_inline_comments(comments) def _get_user_answers(self) -> Tuple[str, str]: """ Retrieves the question and answer strings from the discussion messages related to a pull request. Returns: A tuple containing the question and answer strings. """ question_str = "" answer_str = "" if self.is_answer: discussion_messages = self.git_provider.get_issue_comments() for message in reversed(discussion_messages): if "Questions to better understand the PR:" in message.body: question_str = message.body elif '/answer' in message.body: answer_str = message.body if answer_str and question_str: break return question_str, answer_str