mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-02 11:50:37 +08:00
294 lines
12 KiB
Python
294 lines
12 KiB
Python
import copy
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import json
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import logging
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from collections import OrderedDict
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from typing import List, Tuple
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import yaml
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from jinja2 import Environment, StrictUndefined
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from yaml import SafeLoader
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from pr_agent.algo.ai_handler import AiHandler
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from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models, \
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find_line_number_of_relevant_line_in_file, clip_tokens
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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, try_fix_json, try_fix_yaml, load_yaml
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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.servers.help import actions_help_text, bot_help_text
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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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"""
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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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args (list, optional): List of arguments passed to the PRReviewer class. Defaults to None.
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"""
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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 = AiHandler()
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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_security": get_settings().pr_reviewer.require_security_review,
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"require_focused": get_settings().pr_reviewer.require_focused_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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}
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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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"""
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Review the pull request and generate feedback.
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"""
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if self.is_auto and not get_settings().pr_reviewer.automatic_review:
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logging.info(f'Automatic review is disabled {self.pr_url}')
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return None
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logging.info(f'Reviewing PR: {self.pr_url} ...')
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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)
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logging.info('Preparing PR review...')
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pr_comment = self._prepare_pr_review()
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if get_settings().config.publish_output:
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logging.info('Pushing PR review...')
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self.git_provider.publish_comment(pr_comment)
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self.git_provider.remove_initial_comment()
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if get_settings().pr_reviewer.inline_code_comments:
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logging.info('Pushing inline code comments...')
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self._publish_inline_code_comments()
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async def _prepare_prediction(self, model: str) -> None:
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"""
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Prepare the 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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None
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"""
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logging.info('Getting PR diff...')
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self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model)
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logging.info('Getting AI prediction...')
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self.prediction = await self._get_prediction(model)
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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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if get_settings().config.verbosity_level >= 2:
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logging.info(f"\nSystem prompt:\n{system_prompt}")
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logging.info(f"\nUser prompt:\n{user_prompt}")
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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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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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# Move 'Security concerns' key to 'PR Analysis' section for better display
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pr_feedback = data.get('PR Feedback', {})
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security_concerns = pr_feedback.get('Security concerns')
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if security_concerns is not None:
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del pr_feedback['Security concerns']
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if type(security_concerns) == bool and security_concerns == False:
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data.setdefault('PR Analysis', {})['Security concerns'] = 'No security concerns found'
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else:
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data.setdefault('PR Analysis', {})['Security concerns'] = security_concerns
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#
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if 'Code feedback' in pr_feedback:
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code_feedback = pr_feedback['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 pr_feedback['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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# 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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data = OrderedDict(data)
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data.update({'Incremental PR Review': {
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"⏮️ Review for commits since previous PR-Agent review": f"Starting from commit {last_commit_url}"}})
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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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user = self.git_provider.get_user_id()
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# Add help text if not in CLI mode
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if not get_settings().get("CONFIG.CLI_MODE", False):
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markdown_text += "\n### How to use\n"
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if user and '[bot]' not in user:
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markdown_text += bot_help_text(user)
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else:
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markdown_text += actions_help_text
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# Log markdown response if verbosity level is high
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if get_settings().config.verbosity_level >= 2:
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logging.info(f"Markdown response:\n{markdown_text}")
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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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review_text = self.prediction.strip()
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review_text = review_text.removeprefix('```yaml').rstrip('`')
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try:
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data = yaml.load(review_text, Loader=SafeLoader)
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except Exception as e:
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logging.error(f"Failed to parse AI prediction: {e}")
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data = try_fix_yaml(review_text)
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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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logging.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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