Codex
117 lines
4.7 KiB
Python
117 lines
4.7 KiB
Python
from __future__ import annotations
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import logging
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from datetime import date
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from typing import Optional
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from sqlalchemy.orm import Session
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from app.agent.report_writer import ReportWriter
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from app.core.config import Settings
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from app.core.timezone import beijing_today
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from app.db.repository import AgentRepository
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from app.integrations.github_client import GitHubHotProjectClient
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from app.integrations.news_search_client import NewsSearchClient
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from app.llm.grok_client import GrokIntelligenceClient
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from app.schemas.agent import RunResponse, SignalItem
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logger = logging.getLogger(__name__)
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class AgentRunner:
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"""Coordinates source collection, persistence, and report writing."""
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def __init__(self, db: Session, settings: Settings) -> None:
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self.repo = AgentRepository(db)
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self.db = db
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self.github = GitHubHotProjectClient(settings)
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self.news = NewsSearchClient(settings)
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self.grok = GrokIntelligenceClient(settings)
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self.writer = ReportWriter(settings.report_dir)
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def run_daily(self, run_date: Optional[date] = None) -> RunResponse:
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# Runner统一编排候选采集、模型研判和持久化，保证一次运行只有一种业务路径。
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current_date = run_date or beijing_today()
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request_payload = {
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"run_date": current_date.isoformat(),
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"mode": "grok_agent",
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}
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run = self.repo.create_run(request_payload=request_payload)
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logger.info("agent_run_started run_id=%s run_date=%s mode=grok_agent", run.id, current_date)
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try:
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topics = self.repo.list_enabled_topics()
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news_candidates = self.news.collect_ai_news(run_date=current_date)
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github_projects = self.github.collect_hot_projects(run_date=current_date)
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result = self.grok.collect_daily_intelligence(
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topics=topics,
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news_candidates=news_candidates,
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github_projects=github_projects,
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run_date=current_date,
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)
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signal_items = self._compose_run_signals(
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news_candidates=news_candidates,
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github_projects=github_projects,
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model_signals=result.signals,
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)
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signals = self.repo.save_signals(run=run, items=signal_items)
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report_path = self.writer.write_daily_report(current_date, result.report_markdown)
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self.repo.save_report(
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run=run,
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title=result.title,
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content_md=result.report_markdown,
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file_path=str(report_path),
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)
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self.repo.mark_run_complete(
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run=run,
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raw_response={
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"mode": "grok_agent",
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"topic_count": len(topics),
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"news_candidate_count": len(news_candidates),
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"github_project_count": len(github_projects),
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"model_signal_count": len(result.signals),
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"saved_signal_count": len(signal_items),
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"model": self.grok.settings.llm_model,
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"model_response": result.raw_response,
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},
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)
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self.db.commit()
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logger.info(
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"agent_run_completed run_id=%s signals=%s report_path=%s",
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run.id,
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len(signals),
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report_path,
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)
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return RunResponse(run_id=run.id, status=run.status, report_path=str(report_path))
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except Exception as exc:
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self.repo.mark_run_failed(run=run, error=str(exc))
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self.db.commit()
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logger.exception("agent_run_failed run_id=%s error=%s", run.id, exc)
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raise
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def _compose_run_signals(
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self,
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news_candidates: list[SignalItem],
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github_projects: list[SignalItem],
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model_signals: list[SignalItem],
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) -> list[SignalItem]:
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# 入库清单以采集候选为准，模型同链接结果只增强摘要和重要度，避免日报模型漏选导致信号消失。
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model_by_url = {item.source_url: item for item in model_signals}
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composed = []
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for candidate in [*news_candidates, *github_projects]:
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model_item = model_by_url.get(candidate.source_url)
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if model_item is None:
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composed.append(candidate)
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continue
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composed.append(
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candidate.model_copy(
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update={
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"topic": model_item.topic,
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"summary": model_item.summary,
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"importance": model_item.importance,
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"entities": model_item.entities or candidate.entities,
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}
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)
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)
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return composed
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