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