mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-03 04:10:49 +08:00
84 lines
3.6 KiB
Python
84 lines
3.6 KiB
Python
import copy
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import json
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import logging
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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.algo.utils import convert_to_markdown
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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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from pr_agent.git_providers.git_provider import get_main_pr_language
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class PRDescription:
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def __init__(self, pr_url: str):
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self.git_provider = get_git_provider()(pr_url)
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self.main_pr_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.ai_handler = AiHandler()
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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_description(),
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"language": self.main_pr_language,
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"diff": "", # empty diff for initial calculation
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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_description_prompt.system,
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settings.pr_description_prompt.user)
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self.patches_diff = None
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self.prediction = None
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async def describe(self):
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logging.info('Generating a PR description...')
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if settings.config.publish_review:
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self.git_provider.publish_comment("Preparing pr description...", is_temporary=True)
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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_title, pr_body = 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_description(pr_title, pr_body)
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self.git_provider.remove_initial_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_description_prompt.system).render(variables)
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user_prompt = environment.from_string(settings.pr_description_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):
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data = json.loads(self.prediction)
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pr_body = ""
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# for key, value in data.items():
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# markdown_text += f"## {key}\n\n"
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# markdown_text += f"{value}\n\n"
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title = data['PR Title']
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del data['PR Title']
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for key, value in data.items():
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pr_body += f"{key}:\n"
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if 'walkthrough' in key.lower():
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pr_body += f"{value}\n"
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else:
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pr_body += f"**{value}**\n\n___\n"
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if settings.config.verbosity_level >= 2:
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logging.info(f"title:\n{title}\n{pr_body}")
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return title, pr_body
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