mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-01 19:30:40 +08:00
68 lines
3.0 KiB
Python
68 lines
3.0 KiB
Python
import copy
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import logging
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from typing import Optional
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from jinja2 import Environment, StrictUndefined
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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
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from pr_agent.algo.token_handler import TokenHandler
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from pr_agent.config_loader import settings
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from pr_agent.git_providers import get_git_provider
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class PRQuestions:
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def __init__(self, pr_url: str, question_str: str, installation_id: Optional[int] = None):
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self.git_provider = get_git_provider()(pr_url, installation_id)
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self.main_pr_language = self.git_provider.get_main_pr_language()
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self.installation_id = installation_id
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self.ai_handler = AiHandler()
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self.question_str = question_str
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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.pr.body,
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"language": self.git_provider.get_main_pr_language(),
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"diff": "", # empty diff for initial calculation
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"questions": self.question_str,
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}
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self.token_handler = TokenHandler(self.git_provider.pr,
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self.vars,
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settings.pr_questions_prompt.system,
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settings.pr_questions_prompt.user)
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self.patches_diff = None
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self.prediction = None
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async def answer(self):
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logging.info('Answering a PR question...')
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self.git_provider.publish_comment("Preparing answer...")
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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)
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logging.info('Getting AI prediction...')
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self.prediction = await self._get_prediction()
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logging.info('Preparing answer...')
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pr_comment = self._prepare_pr_answer()
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if settings.config.publish_review:
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logging.info('Pushing answer...')
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self.git_provider.publish_comment(pr_comment)
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return ""
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async def _get_prediction(self):
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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(settings.pr_questions_prompt.system).render(variables)
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user_prompt = environment.from_string(settings.pr_questions_prompt.user).render(variables)
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if 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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model = settings.config.model
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response, finish_reason = await self.ai_handler.chat_completion(model=model, temperature=0.2,
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system=system_prompt, user=user_prompt)
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return response
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def _prepare_pr_answer(self) -> str:
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answer_str = f"Questions: {self.question_str}\n\n"
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answer_str += f"Answer: {self.prediction.strip()}\n\n"
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return answer_str
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