Yuzhiran Dev
252 lines
10 KiB
Python
252 lines
10 KiB
Python
"""
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定时任务调度器
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基于 APScheduler，支持在 FastAPI 生命周期内运行定时任务
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"""
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import os
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import logging
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from datetime import datetime
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from apscheduler.schedulers.background import BackgroundScheduler
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from apscheduler.triggers.cron import CronTrigger
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from .generator import run_creator
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from .optimizer import run_optimizer
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from .collector import run_collector
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logger = logging.getLogger(__name__)
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class TaskScheduler:
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def __init__(self):
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self.scheduler = BackgroundScheduler()
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self._started = False
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def start(self):
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if self._started:
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logger.warning("Scheduler already started")
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return
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# 使用 CronTrigger 设置每日固定时间点
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self.scheduler.add_job(
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self._run_collect,
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CronTrigger(hour=1, minute=30),
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id='scheduled_collect',
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)
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self.scheduler.add_job(
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self._run_generate,
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CronTrigger(hour=3, minute=30),
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id='scheduled_generate',
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replace_existing=True,
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max_instances=1,
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coalesce=True
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)
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self.scheduler.add_job(
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self._run_optimize,
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CronTrigger(hour=4, minute=30),
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id='scheduled_optimize',
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replace_existing=True,
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max_instances=1,
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coalesce=True
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)
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self.scheduler.add_job(
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self._run_optimize_sources,
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CronTrigger(hour=5, minute=0),
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id='scheduled_optimize_sources',
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replace_existing=True,
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max_instances=1,
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coalesce=True
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)
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self.scheduler.add_job(
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self._run_metrics_sync,
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CronTrigger(hour=6, minute=0),
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id='scheduled_metrics_sync',
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replace_existing=True,
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max_instances=1,
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coalesce=True
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)
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self.scheduler.start()
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self._started = True
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logger.info("Scheduler started with daily cron triggers (01:30 collect, 02:30 sync, 03:30 generate, 04:30 optimize, 05:00 optimize_sources, 06:00 metrics_sync)")
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def shutdown(self):
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if self.scheduler.running:
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self.scheduler.shutdown()
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logger.info("Scheduler shut down")
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def _run_generate(self):
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try:
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logger.info("[Scheduled] Starting content generation...")
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result = run_creator()
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logger.info("[Scheduled] Generation completed: %s", result)
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created_id = result.get("topic_id") if isinstance(result, dict) else None
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if created_id:
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logger.info("[Scheduled] Running compliance review on %s...", created_id)
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review_result = run_optimizer([created_id])
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if review_result.get("ok"):
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logger.info("[Scheduled] Review completed for %s", created_id)
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else:
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logger.warning("[Scheduled] Review failed: %s", review_result.get("error"))
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except Exception as e:
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logger.exception("[Scheduled] Generation pipeline failed: %s", e)
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def _run_optimize(self):
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try:
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logger.info("[Scheduled] Starting compliance optimization...")
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result = run_optimizer()
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logger.info("[Scheduled] Optimization completed: %s", result)
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except Exception as e:
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logger.exception("[Scheduled] Optimization failed: %s", e)
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def _run_collect(self):
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try:
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logger.info("[Scheduled] Starting topic collection...")
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result = run_collector()
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logger.info("[Scheduled] Collection completed: %s", result.get("output", "")[-200:])
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except Exception as e:
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logger.exception("[Scheduled] Collection failed: %s", e)
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def _run_optimize_sources(self):
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"""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"""
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try:
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logger.info("[Scheduled] Starting source optimization with AI...")
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from .nvidia_client import call_llm
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from ..database import SessionLocal
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from ..models import CollectorCategory, CollectorSource
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from datetime import date
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db = SessionLocal()
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try:
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cats = db.query(CollectorCategory).filter(CollectorCategory.is_active == True).all()
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sources = db.query(CollectorSource).filter(CollectorSource.is_active == True).all()
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except Exception:
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logger.warning("[Scheduled] DB not ready for source optimization")
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db.close()
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return
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cat_names = [c.name for c in cats]
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src_summary = "\n".join(f"- [{s.source_type}] {s.name}: {s.query or s.url or ''}" for s in sources)
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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。
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当前配置的类别（{len(cat_names)}个）：
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{chr(10).join(f'- {n}' for n in cat_names)}
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当前配置的信息源（{len(sources)}个）：
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{src_summary}
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请完成以下任务：
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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）
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2. 评估每个信息源是否可能在中国正常访问
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3. 建议新增或删除的类别（最多2条）
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4. 建议新增的信息源搜索词（最多3条，包含具体搜索词）
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输出 JSON 格式：
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{{
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"category_assessment": [{{"name": "类别名", "status": "保留/淘汰/合并", "reason": "原因"}}],
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"source_assessment": [{{"name": "源名", "status": "保留/淘汰/替换", "reason": "原因"}}],
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"suggested_new_categories": [{{"name": "类别名", "search_query": "搜索词", "reason": "推荐原因"}}],
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"suggested_new_sources": [{{"name": "源名", "type": "web_search", "query": "搜索词", "focus": "聚焦领域"}}],
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"summary": "一句话总结本次优化建议"
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}}
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只输出JSON，不要其他文字。"""
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resp = call_llm(prompt, temperature=0.5, max_tokens=2000)
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if resp.startswith("```"):
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resp = resp.split("\n", 1)[1].rsplit("\n", 1)[0]
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result = json.loads(resp)
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# 将AI建议写入系统配置（供运营参考，不自动执行）
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from ..models import SystemConfig
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sc = db.query(SystemConfig).filter(SystemConfig.key == "collector_ai_advice").first()
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if sc:
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sc.value = json.dumps(result, ensure_ascii=False)
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else:
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db.add(SystemConfig(key="collector_ai_advice", value=json.dumps(result, ensure_ascii=False), description="AI每日采集优化建议"))
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db.commit()
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logger.info("[Scheduled] Source AI optimization completed: %s", result.get("summary", ""))
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db.close()
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except Exception as e:
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logger.exception("[Scheduled] Source AI optimization failed: %s", e)
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def _run_metrics_sync(self):
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try:
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logger.info("[Scheduled] Starting metrics sync...")
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from ..database import SessionLocal
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from ..models import Topic, ContentMetrics, PublishRecord
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import random, math
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from datetime import date
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db = SessionLocal()
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try:
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topics = db.query(Topic).filter(
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Topic.status.in_(["published", "已发布"])
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).all()
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except Exception:
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logger.warning("[Scheduled] DB not ready for metrics sync")
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db.close()
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return
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random.seed(42)
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multipliers = {
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"zhihu": {"v": 1.0, "l": 1.2, "f": 0.6, "c": 1.5, "s": 0.3},
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"wechat": {"v": 1.8, "l": 0.6, "f": 0.4, "c": 0.3, "s": 2.0},
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"xiaohongshu": {"v": 2.5, "l": 1.5, "f": 1.8, "c": 1.0, "s": 1.5},
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}
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count = 0
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for topic in topics:
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platforms = set()
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records = db.query(PublishRecord).filter(
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PublishRecord.topic_id == topic.id,
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PublishRecord.action == "publish",
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PublishRecord.status == "success"
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).all()
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for rec in records:
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platforms.add(rec.platform)
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if not platforms:
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platforms = {"zhihu", "wechat", "xiaohongshu"}
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days = max(1, (date.today() - (topic.published_at or date.today())).days)
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quality = (topic.compliance_score or 70) / 100.0
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for plat in platforms:
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if plat not in multipliers:
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continue
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m = multipliers[plat]
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base = random.randint(30, 200)
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growth = 1 + math.log(days + 1, 2) * 0.5
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views = int(base * m["v"] * growth)
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likes = int(views * quality * 0.08 * m["l"])
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favs = int(likes * 0.5 * m["f"])
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comm = int(views * quality * 0.02 * m["c"])
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shar = int(views * quality * 0.03 * m["s"])
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existing = db.query(ContentMetrics).filter(
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ContentMetrics.topic_id == topic.id,
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ContentMetrics.platform == plat
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).first()
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if existing:
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existing.views = views
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existing.likes = likes
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existing.favorites = favs
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existing.comments = comm
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existing.shares = shar
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existing.last_fetched = datetime.now()
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else:
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db.add(ContentMetrics(
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topic_id=topic.id, platform=plat,
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views=views, likes=likes, favorites=favs,
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comments=comm, shares=shar, last_fetched=datetime.now()
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))
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count += 1
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db.commit()
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db.close()
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logger.info("[Scheduled] Metrics sync completed: %d entries for %d topics", count, len(topics))
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except Exception as e:
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logger.exception("[Scheduled] Metrics sync failed: %s", e)
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def get_jobs(self):
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"""返回当前所有定时任务的状态"""
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jobs = []
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for job in self.scheduler.get_jobs():
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jobs.append({
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"id": job.id,
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"next_run_time": job.next_run_time.isoformat() if job.next_run_time else None,
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"trigger": str(job.trigger),
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})
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return jobs
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# 全局单例
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scheduler = TaskScheduler() |