169 lines
7.0 KiB
Python
169 lines
7.0 KiB
Python
"""AI 自动复盘日报：汇总当日盘面，生成图文日报（markdown），落库并可推送。
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数据全部来自中台（sector_daily / fund_flow_daily / sentiment_daily / dragon_tiger / stock_metrics），
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AI 点评与明日策略复用 ai.py（有 key 走大模型，无 key 规则降级）。
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"""
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from __future__ import annotations
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import datetime as dt
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from sqlalchemy import select, func
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import ai
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import llm
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import notifier
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from db import get_session
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from models import (SectorDaily, FundFlowDaily, SentimentDaily, DragonTiger,
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StockMetric, DailyReport)
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def _gather(date=None):
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with get_session() as s:
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d = (dt.date.fromisoformat(date) if date
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else s.execute(select(func.max(SectorDaily.date))).scalar())
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if not d:
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return None
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secs = s.execute(select(SectorDaily).where(SectorDaily.date == d)
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.order_by(SectorDaily.pct.desc())).scalars().all()
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flows = s.execute(select(FundFlowDaily).where(FundFlowDaily.date == d)
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.order_by(FundFlowDaily.net.desc())).scalars().all()
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senti = s.execute(select(SentimentDaily).where(SentimentDaily.date == d)).scalar_one_or_none()
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lhb = s.execute(select(DragonTiger).where(DragonTiger.date == d)
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.order_by(DragonTiger.net.desc()).limit(6)).scalars().all()
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mdate = s.execute(select(func.max(StockMetric.date))).scalar()
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gainers = streak = []
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if mdate:
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gainers = s.execute(select(StockMetric).where(StockMetric.date == mdate)
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.order_by(StockMetric.pct.desc()).limit(8)).scalars().all()
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streak = s.execute(select(StockMetric).where(StockMetric.date == mdate, StockMetric.up_streak >= 3)
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.order_by(StockMetric.up_streak.desc(), StockMetric.ret5.desc()).limit(8)).scalars().all()
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return {
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"date": d, "senti": senti, "secs": secs, "flows": flows, "lhb": lhb,
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"gainers": [(x.name, x.code, x.pct) for x in gainers],
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"streak": [(x.name, x.up_streak, x.ret5) for x in streak],
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}
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def _build_markdown(g):
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d = g["date"]
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s = g["senti"]
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secs, flows, lhb = g["secs"], g["flows"], g["lhb"]
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parts = [f"# {d} 收盘复盘日报\n"]
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# 一、市场温度
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if s:
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ratio = (s.up / max(1, s.up + s.down)) * 100
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mood = "赚钱效应较好" if s.up > s.down * 1.5 else ("情绪偏弱" if s.down > s.up else "多空分歧")
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parts.append("## 一、市场温度")
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parts.append(f"- 涨跌家数：上涨 **{s.up}** / 下跌 **{s.down}** / 平盘 {s.flat}（上涨占比 {ratio:.0f}%）")
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parts.append(f"- 涨停 **{s.limit_up}** 家 / 跌停 **{s.limit_down}** 家")
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parts.append(f"- 综合判断：{mood}\n")
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# 二、板块表现
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if secs:
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top = secs[:6]
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bot = secs[-4:]
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parts.append("## 二、板块表现")
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parts.append("- 领涨：" + "，".join(f"{x.name}({x.pct:+.2f}%)" for x in top))
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parts.append("- 领跌：" + "，".join(f"{x.name}({x.pct:+.2f}%)" for x in bot) + "\n")
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# 三、资金流向
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if flows:
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parts.append("## 三、资金流向（主力净额）")
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parts.append("- 净流入前列：" + "，".join(f"{x.name}({x.net:+.1f}亿)" for x in flows[:6]))
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parts.append("- 净流出前列：" + "，".join(f"{x.name}({x.net:+.1f}亿)" for x in flows[-4:][::-1]) + "\n")
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# 四、强势梯队
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if g["streak"]:
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parts.append("## 四、强势梯队（连涨）")
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parts.append("、".join(f"{n}（{k}连阳, 5日{r:+.1f}%）" for n, k, r in g["streak"]) + "\n")
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# 五、龙虎榜焦点
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if lhb:
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parts.append("## 五、龙虎榜焦点（净买额）")
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parts.append("、".join(f"{n}({v:+.2f}亿)" for n, v in [(x.name, x.net) for x in lhb]) + "\n")
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return "\n".join(parts)
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def generate(date=None, push=False):
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"""生成（或重生成）某日复盘日报。默认最新交易日。"""
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g = _gather(date)
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if not g:
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return {"ok": False, "msg": "暂无入库数据，请先到数据中台入库"}
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d = g["date"]
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body = _build_markdown(g)
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# AI 综合点评 + 明日策略（复用 ai.py）
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rv = ai.review_daily_comment(d.isoformat())
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st = ai.today_strategy()
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source = "llm" if (rv.get("source") == "llm" or st.get("source") == "llm") else "rule"
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body += "\n## 六、AI 综合点评\n" + (rv.get("text", "") if rv.get("ok") else "")
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body += "\n\n## 七、明日策略\n" + (st.get("text", "") if st.get("ok") else "")
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title = f"{d} 收盘复盘日报"
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with get_session() as s:
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row = s.get(DailyReport, d)
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if row:
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row.source, row.title, row.content = source, title, body
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else:
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row = DailyReport(date=d, source=source, title=title, content=body)
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s.add(row)
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s.commit()
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result = {"ok": True, "date": d.isoformat(), "source": source, "title": title, "content": body}
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if push and notifier.any_enabled():
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try:
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# 推送精简版（情绪 + 领涨 + AI 点评首段）
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brief = _push_brief(g, rv)
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res = notifier.notify("【Blackdata】" + title, brief)
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with get_session() as s:
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r2 = s.get(DailyReport, d)
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if r2:
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r2.pushed = True
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s.commit()
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result["push"] = res
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except Exception as e:
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result["push"] = {"error": repr(e)[:120]}
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return result
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def _push_brief(g, rv):
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s = g["senti"]
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lines = [f"{g['date']} 收盘复盘"]
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if s:
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lines.append(f"涨{s.up}/跌{s.down}，涨停{s.limit_up}/跌停{s.limit_down}")
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if g["secs"]:
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lines.append("领涨：" + "、".join(f"{x.name}({x.pct:+.1f}%)" for x in g["secs"][:4]))
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if g["flows"]:
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lines.append("吸金：" + "、".join(x.name for x in g["flows"][:4]))
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txt = (rv.get("text") or "").strip().split("\n")[0]
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if txt:
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lines.append("点评：" + txt[:80])
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return "\n".join(lines)
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def latest():
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with get_session() as s:
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row = s.execute(select(DailyReport).order_by(DailyReport.date.desc())).scalars().first()
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if not row:
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return {"ok": False, "msg": "暂无日报，请先生成"}
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return {"ok": True, "date": row.date.isoformat(), "source": row.source,
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"title": row.title, "content": row.content, "pushed": row.pushed}
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def get_by_date(date):
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with get_session() as s:
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row = s.get(DailyReport, dt.date.fromisoformat(date))
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if not row:
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return {"ok": False, "msg": "该日无日报"}
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return {"ok": True, "date": row.date.isoformat(), "source": row.source,
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"title": row.title, "content": row.content, "pushed": row.pushed}
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def history(limit=30):
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with get_session() as s:
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rows = s.execute(select(DailyReport).order_by(DailyReport.date.desc()).limit(limit)).scalars().all()
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return {"list": [{"date": r.date.isoformat(), "source": r.source,
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"title": r.title, "pushed": r.pushed} for r in rows]}
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