import copy import logging from typing import Optional from jinja2 import Environment, StrictUndefined from pr_agent.algo.ai_handler import AiHandler from pr_agent.algo.pr_processing import get_pr_diff from pr_agent.algo.token_handler import TokenHandler from pr_agent.config_loader import settings from pr_agent.git_providers import get_git_provider class PRQuestions: def __init__(self, pr_url: str, question_str: str, installation_id: Optional[int] = None): self.git_provider = get_git_provider()(pr_url, installation_id) self.main_pr_language = self.git_provider.get_main_pr_language( self.git_provider.get_languages(), self.git_provider.get_files() ) self.installation_id = installation_id self.ai_handler = AiHandler() self.question_str = question_str self.vars = { "title": self.git_provider.pr.title, "branch": self.git_provider.get_pr_branch(), "description": self.git_provider.pr.body, "language": self.main_pr_language, "diff": "", # empty diff for initial calculation "questions": self.question_str, } self.token_handler = TokenHandler(self.git_provider.pr, self.vars, settings.pr_questions_prompt.system, settings.pr_questions_prompt.user) self.patches_diff = None self.prediction = None async def answer(self): logging.info('Answering a PR question...') if settings.config.publish_review: self.git_provider.publish_comment("Preparing answer...", is_temporary=True) logging.info('Getting PR diff...') self.patches_diff = get_pr_diff(self.git_provider, self.token_handler) logging.info('Getting AI prediction...') self.prediction = await self._get_prediction() logging.info('Preparing answer...') pr_comment = self._prepare_pr_answer() if settings.config.publish_review: logging.info('Pushing answer...') self.git_provider.publish_comment(pr_comment) self.git_provider.remove_initial_comment() return "" async def _get_prediction(self): variables = copy.deepcopy(self.vars) variables["diff"] = self.patches_diff # update diff environment = Environment(undefined=StrictUndefined) system_prompt = environment.from_string(settings.pr_questions_prompt.system).render(variables) user_prompt = environment.from_string(settings.pr_questions_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}") model = settings.config.model 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_answer(self) -> str: answer_str = f"Question: {self.question_str}\n\n" answer_str += f"Answer:\n{self.prediction.strip()}\n\n" if settings.config.verbosity_level >= 2: logging.info(f"answer_str:\n{answer_str}") return answer_str