import copy from functools import partial from jinja2 import Environment, StrictUndefined from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler 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.config_loader import get_settings from pr_agent.git_providers import get_git_provider from pr_agent.git_providers.git_provider import get_main_pr_language from pr_agent.log import get_logger class PRInformationFromUser: def __init__(self, pr_url: str, args: list = None, ai_handler: partial[BaseAiHandler,] = LiteLLMAIHandler): self.git_provider = get_git_provider()(pr_url) self.main_pr_language = get_main_pr_language( self.git_provider.get_languages(), self.git_provider.get_files() ) self.ai_handler = ai_handler() self.ai_handler.main_pr_language = self.main_pr_language 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_pr_language, "diff": "", # empty diff for initial calculation "commit_messages_str": self.git_provider.get_commit_messages(), } self.token_handler = TokenHandler(self.git_provider.pr, self.vars, get_settings().pr_information_from_user_prompt.system, get_settings().pr_information_from_user_prompt.user) self.patches_diff = None self.prediction = None async def run(self): get_logger().info('Generating question to the user...') if get_settings().config.publish_output: self.git_provider.publish_comment("Preparing questions...", is_temporary=True) await retry_with_fallback_models(self._prepare_prediction) get_logger().info('Preparing questions...') pr_comment = self._prepare_pr_answer() if get_settings().config.publish_output: get_logger().info('Pushing questions...') self.git_provider.publish_comment(pr_comment) self.git_provider.remove_initial_comment() return "" async def _prepare_prediction(self, model): get_logger().info('Getting PR diff...') self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model) get_logger().info('Getting AI prediction...') self.prediction = await self._get_prediction(model) async def _get_prediction(self, model: str): variables = copy.deepcopy(self.vars) variables["diff"] = self.patches_diff # update diff environment = Environment(undefined=StrictUndefined) system_prompt = environment.from_string(get_settings().pr_information_from_user_prompt.system).render(variables) user_prompt = environment.from_string(get_settings().pr_information_from_user_prompt.user).render(variables) if get_settings().config.verbosity_level >= 2: get_logger().info(f"\nSystem prompt:\n{system_prompt}") get_logger().info(f"\nUser prompt:\n{user_prompt}") response, finish_reason = await self.ai_handler.chat_completion( model=model, temperature=get_settings().config.temperature, system=system_prompt, user=user_prompt) return response def _prepare_pr_answer(self) -> str: model_output = self.prediction.strip() if get_settings().config.verbosity_level >= 2: get_logger().info(f"answer_str:\n{model_output}") answer_str = f"{model_output}\n\n Please respond to the questions above in the following format:\n\n" +\ "\n>/answer\n>1) ...\n>2) ...\n>...\n" return answer_str