""" 定时任务调度器 基于 APScheduler，支持在 FastAPI 生命周期内运行定时任务 """ import os import sys import logging from datetime import datetime from pathlib import Path from apscheduler.schedulers.background import BackgroundScheduler from apscheduler.triggers.cron import CronTrigger from .generator import run_creator from .optimizer import run_optimizer from .collector import run_collector logger = logging.getLogger(__name__) class TaskScheduler: def __init__(self): self.scheduler = BackgroundScheduler() self._started = False def start(self): if self._started: logger.warning("Scheduler already started") return # 使用 CronTrigger 设置每日固定时间点 self.scheduler.add_job( self._run_collect, CronTrigger(hour=1, minute=30), id='scheduled_collect', ) self.scheduler.add_job( self._run_fetch_trends, CronTrigger(hour=3, minute=0), id='scheduled_fetch_trends', replace_existing=True, max_instances=1, coalesce=True ) self.scheduler.add_job( self._run_generate, CronTrigger(hour=3, minute=30), id='scheduled_generate', replace_existing=True, max_instances=1, coalesce=True ) self.scheduler.add_job( self._run_optimize, CronTrigger(hour=4, minute=30), id='scheduled_optimize', replace_existing=True, max_instances=1, coalesce=True ) self.scheduler.add_job( self._run_optimize_sources, CronTrigger(hour=5, minute=0), id='scheduled_optimize_sources', replace_existing=True, max_instances=1, coalesce=True ) self.scheduler.add_job( self._run_metrics_sync, CronTrigger(hour=6, minute=0), id='scheduled_metrics_sync', replace_existing=True, max_instances=1, coalesce=True ) self.scheduler.start() self._started = True logger.info("Scheduler started: 01:30 collect, 03:00 trends, 03:30 generate, 04:30 review, 05:00 optimize_sources, 06:00 metrics_sync") def shutdown(self): if self.scheduler.running: self.scheduler.shutdown() logger.info("Scheduler shut down") def _run_fetch_trends(self): """定时刷新热点趋势（百度/微博/知乎实时热搜 + LLM补充）""" try: logger.info("[Scheduled] Fetching hot trends...") import subprocess result = subprocess.run( [sys.executable, str(Path(__file__).parent.parent.parent.parent / "scripts" / "trends.py")], capture_output=True, text=True, timeout=120 ) if result.returncode == 0: for line in result.stdout.strip().split("\n"): if line.strip(): logger.info("[Trends] %s", line.strip()) logger.info("[Scheduled] Trends refreshed successfully") else: logger.warning("[Scheduled] Trends refresh failed: %s", result.stderr[-500:]) except Exception as e: logger.exception("[Scheduled] Trends refresh error: %s", e) def _run_generate(self): try: logger.info("[Scheduled] Starting content generation...") result = run_creator() logger.info("[Scheduled] Generation completed: %s", result) created_id = result.get("topic_id") if isinstance(result, dict) else None if created_id: logger.info("[Scheduled] Running compliance review on %s...", created_id) review_result = run_optimizer([created_id]) if review_result.get("ok"): logger.info("[Scheduled] Review completed for %s", created_id) else: logger.warning("[Scheduled] Review failed: %s", review_result.get("error")) except Exception as e: logger.exception("[Scheduled] Generation pipeline failed: %s", e) def _run_optimize(self): try: logger.info("[Scheduled] Starting compliance review...") result = run_optimizer() logger.info("[Scheduled] Review completed: %s", result) except Exception as e: logger.exception("[Scheduled] Review failed: %s", e) def _run_collect(self): try: logger.info("[Scheduled] Starting topic collection...") result = run_collector() logger.info("[Scheduled] Collection completed: %s", result.get("output", "")[-200:]) except Exception as e: logger.exception("[Scheduled] Collection failed: %s", e) def _run_optimize_sources(self): """AI自动优化采集类别与信息源：对比市场热点和当前配置，给出调整建议""" try: logger.info("[Scheduled] Starting source optimization with AI...") from .nvidia_client import call_llm from ..database import SessionLocal from ..models import CollectorCategory, CollectorSource from datetime import date db = SessionLocal() try: cats = db.query(CollectorCategory).filter(CollectorCategory.is_active == True).all() sources = db.query(CollectorSource).filter(CollectorSource.is_active == True).all() except Exception: logger.warning("[Scheduled] DB not ready for source optimization") db.close() return cat_names = [c.name for c in cats] src_summary = "\n".join(f"- [{s.source_type}] {s.name}: {s.query or s.url or ''}" for s in sources) prompt = f"""你是一个内容策略分析师。分析当前中文互联网可持续生活领域的真实热点，与以下配置进行对比。 当前配置的类别（{len(cat_names)}个）： {chr(10).join(f'- {n}' for n in cat_names)} 当前配置的信息源（{len(sources)}个）： {src_summary} 请完成以下任务： 1. 评估每个类别是否仍符合2026年中国市场真实热点（基于你的知识） 2. 评估每个信息源是否可能在中国正常访问 3. 建议新增或删除的类别（最多2条） 4. 建议新增的信息源搜索词（最多3条，包含具体搜索词） 输出 JSON 格式： {{ "category_assessment": [{{"name": "类别名", "status": "保留/淘汰/合并", "reason": "原因"}}], "source_assessment": [{{"name": "源名", "status": "保留/淘汰/替换", "reason": "原因"}}], "suggested_new_categories": [{{"name": "类别名", "search_query": "搜索词", "reason": "推荐原因"}}], "suggested_new_sources": [{{"name": "源名", "type": "web_search", "query": "搜索词", "focus": "聚焦领域"}}], "summary": "一句话总结本次优化建议" }} 只输出JSON，不要其他文字。""" resp = call_llm(prompt, temperature=0.5, max_tokens=2000) if resp.startswith("```"): resp = resp.split("\n", 1)[1].rsplit("\n", 1)[0] result = json.loads(resp) # 将AI建议写入系统配置（供运营参考，不自动执行） from ..models import SystemConfig sc = db.query(SystemConfig).filter(SystemConfig.key == "collector_ai_advice").first() if sc: sc.value = json.dumps(result, ensure_ascii=False) else: db.add(SystemConfig(key="collector_ai_advice", value=json.dumps(result, ensure_ascii=False), description="AI每日采集优化建议")) db.commit() logger.info("[Scheduled] Source AI optimization completed: %s", result.get("summary", "")) db.close() except Exception as e: logger.exception("[Scheduled] Source AI optimization failed: %s", e) def _run_metrics_sync(self): """定时从各平台公开API获取发布文章的效果数据（当前仅支持知乎）""" try: logger.info("[Scheduled] Starting metrics sync (zhihu auto-fetch)...") from ..database import SessionLocal from ..models import Topic, ContentMetrics import re, requests as http_requests db = SessionLocal() try: topics = db.query(Topic).filter( Topic.status.in_(["published", "已发布"]) ).all() except Exception: logger.warning("[Scheduled] DB not ready for metrics sync") db.close() return ua = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36" count = 0 for topic in topics: platform_urls = topic.platform_urls or {} zhihu_url = platform_urls.get("zhihu", "") if not zhihu_url: continue m = re.search(r'zhuanlan\.zhihu\.com/p/(\d+)', zhihu_url) if not m: continue post_id = m.group(1) api_url = f"https://zhuanlan.zhihu.com/api/posts/{post_id}" try: resp = http_requests.get(api_url, headers={"User-Agent": ua}, timeout=10) if resp.status_code != 200: continue raw = resp.json() existing = db.query(ContentMetrics).filter( ContentMetrics.topic_id == topic.id, ContentMetrics.platform == "zhihu" ).first() metric_data = { "views": raw.get("voteup_count", raw.get("views_count", 0)), "likes": raw.get("voteup_count", 0), "favorites": raw.get("favorite_count", 0), "comments": raw.get("comment_count", raw.get("comments_count", 0)), "shares": raw.get("share_count", 0), "last_fetched": datetime.now(), "publish_url": zhihu_url, "data_snapshot": raw, } if existing: for k, v in metric_data.items(): setattr(existing, k, v) else: db.add(ContentMetrics(topic_id=topic.id, platform="zhihu", **metric_data)) count += 1 except Exception: continue if count: db.commit() logger.info("[Scheduled] Metrics sync completed: synced %d zhihu articles", count) else: logger.info("[Scheduled] Metrics sync: no zhihu articles to sync") db.close() except Exception as e: logger.exception("[Scheduled] Metrics sync failed: %s", e) def get_jobs(self): """返回当前所有定时任务的状态""" jobs = [] for job in self.scheduler.get_jobs(): jobs.append({ "id": job.id, "next_run_time": job.next_run_time.isoformat() if job.next_run_time else None, "trigger": str(job.trigger), }) return jobs # 全局单例 scheduler = TaskScheduler()