hmo
cd530c2463
事故根因(2026-07-21): hermes gateway /v1/chat/completions 非透传, 每个请求创建带工具的agent会话。一次603288重评螺旋35分钟/44次 terminal调用/输入153k token, 客户端超时后服务端空转, 重试叠加 新会话自我DDoS。 - llm_client 重写: OCG直连为主(key运行时从hermes config.yaml ocg-key6读取, 不落盘), gateway兜底(agent模式仅应急) - REASSESS_MODEL: pro -> flash (A/B实测新prompt下质量差距微弱, flash快40%) - prompt输出纪律: 【建议仓位】不可省略(非买入写'不新建仓'), 禁止structured_data/XML/JSON块, 禁止寒暄开场白 - batch main 双通道预检(全挂才退出)
490 lines
20 KiB
Python
490 lines
20 KiB
Python
#!/usr/bin/env python3
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"""batch_reassess.py — 批量补全12维(九维矩阵)LLM分析（逐只处理，间隔防限流）
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用法:
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python3 batch_reassess.py # 所有缺分析/过期的 active 策略
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python3 batch_reassess.py --type holding # 只处理持仓策略
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python3 batch_reassess.py --type watchlist # 只处理自选策略
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python3 batch_reassess.py --type holding --today # 持仓每日刷新（今早未评过的强制重评）
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python3 batch_reassess.py --code XXXXXX # 单只
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流程：收集最新数据 → 调LLM(gateway)写12维分析+策略 → 保存到DB
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"""
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import sys, json, subprocess, sqlite3, re, time, os
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from datetime import datetime
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# ── 共享 LLM 客户端 + DB 工具（profile-scripts 硬链到同目录）──
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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sys.path.insert(0, "/home/hmo/MoFin")
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from llm_client import call_llm, REASSESS_MODEL, gateway_alive, ocg_alive
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from mofin_db import snapshot_strategy_history
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DB = "/home/hmo/MoFin/data/mofin.db"
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COOLDOWN_HOURS = 1
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STALE_HOURS = 20 # 分析超过20小时视为过期，需要重评
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def has_llm_analysis(code):
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"""检查是否为LLM生成的12维分析（>500字）"""
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT LENGTH(full_analysis) FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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conn.close()
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return r and r[0] and r[0] > 500
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def in_cooldown(code):
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"""冷却期检查"""
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT reassessed_at FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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conn.close()
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if not r or not r[0]:
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return False
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try:
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last = datetime.fromisoformat(r[0])
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diff = (datetime.now() - last).total_seconds() / 3600
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return diff < COOLDOWN_HOURS
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except:
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return False
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def analysis_stale(code, force_today=False):
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"""分析是否过期（>STALE_HOURS 或 force_today 时今早4点前未重评）"""
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT reassessed_at FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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conn.close()
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if not r or not r[0]:
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return True
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try:
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last = datetime.fromisoformat(r[0])
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if force_today:
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today4am = datetime.now().replace(hour=4, minute=0, second=0, microsecond=0)
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return last < today4am
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return (datetime.now() - last).total_seconds() / 3600 > STALE_HOURS
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except:
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return True
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def get_portfolio():
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"""从 portfolio_summary 读实时现金/总资产（不再硬编码）"""
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try:
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT cash, total_assets FROM portfolio_summary WHERE id=1").fetchone()
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conn.close()
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if r and r[1]:
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return int(r[0] or 0), int(r[1])
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except Exception:
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pass
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return 0, 0
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def collect_data(code):
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"""收集最新数据（含完整策略原文）"""
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data = {"code": code}
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# 从DB读策略（含 full_analysis / changelog_json / position_advice）
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT name, entry_low, entry_high, stop_loss, take_profit, timing_signal, action, rr_ratio, tech_snapshot, sector_context, stock_category, full_analysis, changelog_json, reassessed_at, position_advice FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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if r:
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data["name"] = r[0]
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data["entry_low"] = r[1] or 0
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data["entry_high"] = r[2] or 0
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data["stop_loss"] = r[3] or 0
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data["take_profit"] = r[4] or 0
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data["timing_signal"] = r[5] or ""
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data["action"] = r[6] or ""
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data["rr_ratio"] = r[7] or 0
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data["tech_snapshot"] = r[8] or ""
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data["sector_context"] = r[9] or ""
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data["stock_category"] = r[10] or ""
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data["full_analysis"] = r[11] or ""
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data["changelog_json"] = r[12] or ""
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data["reassessed_at"] = r[13] or ""
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data["position_advice"] = r[14] or ""
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conn.close()
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# 从腾讯API拉最新价和基本面
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# 代码前缀：5位=港股(hk)，6/9开头=沪(sh)，其他=深(sz)
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_c = str(code)
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if len(_c) == 5:
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prefix = "hk"
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elif _c.startswith(("6", "9")):
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prefix = "sh"
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else:
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prefix = "sz"
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try:
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r = subprocess.run(["curl", "-s", f"http://qt.gtimg.cn/q={prefix}{code}"], capture_output=True, timeout=10)
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parts = r.stdout.decode("gbk", errors="ignore").split("~")
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data["price"] = float(parts[3]) if len(parts) > 3 and parts[3] else 0
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data["pe"] = parts[39] if len(parts) > 39 and parts[39] else ""
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data["mcap"] = parts[44] if len(parts) > 44 and parts[44] else ""
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data["change_pct"] = parts[32] if len(parts) > 32 and parts[32] else "0"
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except:
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data["price"] = 0
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# 大盘
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try:
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conn = sqlite3.connect(DB)
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mr = conn.execute("SELECT structure FROM macro_context_log ORDER BY id DESC LIMIT 1").fetchone()
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if mr and mr[0]:
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s = json.loads(mr[0])
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data["macro"] = s.get("description", "大盘震荡")
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conn.close()
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except:
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data["macro"] = "大盘震荡"
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return data
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def build_prompt(data):
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"""构建LLM prompt，先审阅原策略再结合实时数据输出修改判断+九维矩阵分析"""
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cash, total = get_portfolio()
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if not total:
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cash, total = 241330, 929727 # 兜底（DB读不到时）
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# 拉取资金流数据
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_flow_note = "暂无资金流数据"
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try:
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import sqlite3 as _sq, json as _j
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_db = _sq.connect("/home/hmo/MoFin/data/mofin.db")
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_fr = _db.execute("SELECT cache_json FROM capital_flow_cache ORDER BY id DESC LIMIT 1").fetchone()
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if _fr and _fr[0]:
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_fc = _j.loads(_fr[0])
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_stocks = _fc.get("stocks", {})
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_s = _stocks.get(data['code'], {})
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if _s and _s.get("analysis"):
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_a = _s["analysis"]
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_net = _a.get("net_flow", 0)
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_main = _a.get("main_force", 0)
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_retail = _a.get("retail_flow", 0)
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_trend = _a.get("trend", "中性")
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_flow_note = f"净流入{_net:.0f}万 主力{_main:.0f}万 散户{_retail:.0f}万 趋势{_trend}"
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_db.close()
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except:
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pass
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# 拉取近期消息面
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_news_note = "暂无近期消息"
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try:
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import sqlite3 as _sq
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_db = _sq.connect("/home/hmo/MoFin/data/mofin.db")
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_nr = _db.execute(
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"SELECT summary, overall_sentiment, created_at FROM signal_news "
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"WHERE (code=? OR sector LIKE ?) AND overall_sentiment IN ('利好','利空') "
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"ORDER BY id DESC LIMIT 3",
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(data['code'], f'%{data.get("name","")[:4]}%')
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).fetchall()
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if _nr:
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_news_note = " | ".join([f"{r[2][:10]} {r[1]} {r[0][:40]}" for r in _nr])
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_db.close()
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except:
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pass
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# ── 构建【原策略全文】section ──
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_params_parts = []
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if data.get('action'): _params_parts.append(f"当前策略: {data['action']}")
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if data.get('timing_signal'): _params_parts.append(f"信号: {data['timing_signal']}")
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if data.get('entry_low') or data.get('entry_high'):
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_params_parts.append(f"买入区间: {data.get('entry_low',0)}~{data.get('entry_high',0)}")
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if data.get('stop_loss'): _params_parts.append(f"止损: {data['stop_loss']}")
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if data.get('take_profit'): _params_parts.append(f"止盈: {data['take_profit']}")
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if data.get('position_advice'): _params_parts.append(f"仓位: {data['position_advice']}")
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_params_str = " | ".join(_params_parts) if _params_parts else "无策略参数"
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# 最近3条变更记录
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_changelog_str = "无变更记录"
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try:
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_cl_raw = data.get('changelog_json', '')
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if _cl_raw:
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_cl = json.loads(_cl_raw) if isinstance(_cl_raw, str) else _cl_raw
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if isinstance(_cl, list) and _cl:
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_recent = _cl[-3:] if len(_cl) > 3 else _cl
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_cl_lines = []
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for i, c in enumerate(_recent):
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_act = c.get('action', c.get('reason', '')) if isinstance(c, dict) else str(c)
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_ts = c.get('timestamp', '') if isinstance(c, dict) else ''
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_cl_lines.append(f" {i+1}. {_ts[:16]} {_act[:80]}")
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if _cl_lines:
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_changelog_str = "\n".join(_cl_lines)
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except:
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pass
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# 完整分析原文（不截断）
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_full_analysis = data.get('full_analysis', '') or ''
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_fa_display = _full_analysis if _full_analysis else '（首次分析，无历史）'
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_orig_strategy_section = f"""当前策略参数: {_params_str}
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变更记录（最近3条）:
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{_changelog_str}
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完整分析原文:
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{_fa_display}"""
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return f"""你是一个资深A股分析师。请先审阅以下【原策略全文】，判断是否需要修改策略，然后做出完整的九维矩阵分析。
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【原策略全文】
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{_orig_strategy_section}
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── 以上是已有的策略，以下是当前实时数据，请结合两者做出判断 ──
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⚠️ 重要：以下9个维度不是独立分析的，你必须交叉对比后给出综合结论。
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例如：如果消息面利好但资金流在流出，说明利好可能是出货；如果基本面强但技术面破位，说明估值可能还没到底。
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当前数据（以下数据均来自实时API，每条标注时间窗口，禁止使用模型内部训练数据）：
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大盘：{data.get('macro','震荡')}（当日实时）
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最新价：{data.get('price',0)} 涨跌：{data.get('change_pct','0')}%（当日实时）
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PE={data.get('pe','?')}（最新财报） 市值={data.get('mcap','?')}亿
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行业：{data.get('sector_context','?')}（当日实时）
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技术面：{data.get('tech_snapshot','')[:300]}（MA=5/10/20/60日 支撑阻力=近20日 量价=当日+近5日趋势）
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资金流：{_flow_note}（近5日累计）
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消息面：{_news_note}（最近3条，自动标注抓取时间）
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当前信号：{data.get('timing_signal','?')} 分类：{data.get('stock_category','?')}
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我的总资产={total}元，可用现金={cash}元。
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请严格按以下格式输出（注意节标题不可省略）：
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【维持或修改】明确二选一判断：维持原策略 / 需要修改策略
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【修改点及理由】
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如果维持原策略 → 写"无需修改"
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如果需要修改 → 逐条列出（每条格式："- 修改点名称：理由说明"）
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【最终新策略】
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用自然语言输出完整的最终策略全文（200-400字），自包含核心交易逻辑、买入区间价格、止损价、止盈价、仓位比例、风险提示。
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⚠️ 本段不要使用【综合结论】【买入区间】等标签——用自然语言描述即可。
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【交叉分析】用2-3句话说明哪些维度出现矛盾/共振，最关键的信号是什么
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① 大盘×基本面 [一句话，说明矛盾关系]
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② 大盘×消息面 [一句话]
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③ 大盘×技术面 [一句话]
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④ 大盘×资金面 [一句话]
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⑤ 行业×基本面 [一句话]
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⑥ 行业×消息面 [一句话]
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⑦ 行业×技术面 [一句话]
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⑧ 行业×资金面 [一句话]
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⑨ 个股×基本面 [一句话]
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⑩ 个股×消息面 [一句话]
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⑪ 个股×技术面 [一句话]
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⑫ 个股×资金面 [一句话]
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【综合结论】（买入/关注/观望/卖出）
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【操作建议】具体操作建议
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【买入区间】最低价~最高价
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【建议止损】数字
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【建议止盈】数字
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【建议仓位】⚠️不可省略。综合结论非"买入"时写"不新建仓"；为"买入"时按以下公式：
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基础仓位按RR确定：RR<1.5→不推荐，RR1.5~3→8%，RR3~5→12%，RR5+→15%
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大盘偏弱×0.8，大盘偏强×1.15
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蓝筹/白马×1.2，成长×0.85，题材/短线×0.6
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最终仓位范围：5%~20%
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同时考虑：现金{cash}元足够买多少手。
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输出格式："X%（理由：一句话说明为什么这个仓位）"
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⚠️ 输出纪律（必须遵守）：
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1. 直接以【维持或修改】开头，禁止任何寒暄、开场白、分隔线
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2. 禁止输出 <structured_data> 或任何 XML/JSON/代码块
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3. 所有【】节标题一个都不能少"""
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def parse_response(text):
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"""从LLM回复中提取策略参数"""
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result = {"signal": "", "entry_low": 0, "entry_high": 0, "stop_loss": 0, "take_profit": 0, "position": ""}
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# 信号
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sl = [l for l in text.split("\n") if "综合结论" in l]
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if sl:
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for kw in ["买入","关注","观望","卖出"]:
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if kw in sl[0]:
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result["signal"] = kw
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break
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# 买入区间
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zl = [l for l in text.split("\n") if "买入区间" in l]
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if zl:
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nums = re.findall(r'[\d.]+', zl[0])
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if len(nums) >= 2:
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result["entry_low"] = float(nums[0])
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result["entry_high"] = float(nums[1])
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# 止损
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for l in text.split("\n"):
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if "建议止损" in l:
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nums = re.findall(r'[\d.]+', l)
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if nums: result["stop_loss"] = float(nums[0])
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# 止盈
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for l in text.split("\n"):
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if "建议止盈" in l:
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nums = re.findall(r'[\d.]+', l)
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if nums: result["take_profit"] = float(nums[0])
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# 仓位：只有买入信号才需要，提取百分比数字
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result["position"] = ""
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if result["signal"] == "买入":
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for l in text.split("\n"):
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if "建议仓位" in l:
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nums = re.findall(r'[\d.]+', l)
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for n in nums:
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f = float(n)
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if 1 <= f <= 30: # 合理的仓位范围
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result["position"] = f"{f:.0f}%"
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break
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break
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return result
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def save_result(code, full_text, parsed):
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"""保存LLM结果到DB（先快照再UPDATE）"""
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conn = sqlite3.connect(DB)
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now = datetime.now().isoformat()
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# ── 修改前快照 ──
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snapshot_strategy_history(conn, code, 'batch_12d')
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updates = ["full_analysis=?", "reassessed_at=?"]
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params = [full_text, now]
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if parsed["signal"]:
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updates.append("timing_signal=?")
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params.append(parsed["signal"])
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if parsed["entry_low"] > 0:
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updates.append("entry_low=?")
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params.append(parsed["entry_low"])
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if parsed["entry_high"] > 0:
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updates.append("entry_high=?")
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||
params.append(parsed["entry_high"])
|
||
if parsed["stop_loss"] > 0:
|
||
updates.append("stop_loss=?")
|
||
params.append(parsed["stop_loss"])
|
||
if parsed["take_profit"] > 0:
|
||
updates.append("take_profit=?")
|
||
params.append(parsed["take_profit"])
|
||
if parsed["position"]:
|
||
updates.append("position_advice=?")
|
||
params.append(parsed["position"])
|
||
|
||
params.append(code)
|
||
sql = f"UPDATE holding_strategies SET {', '.join(updates)} WHERE code=? AND status='active'"
|
||
conn.execute(sql, params)
|
||
conn.commit()
|
||
|
||
# 买入信号→推XMPP通知（在conn close前执行）
|
||
if parsed.get("signal") == "买入":
|
||
try:
|
||
_nr = conn.execute("SELECT name, price FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
|
||
_name = _nr[0] if _nr else code
|
||
_p = _nr[1] if _nr else 0
|
||
_el = parsed.get("entry_low", 0)
|
||
_eh = parsed.get("entry_high", 0)
|
||
_sl = parsed.get("stop_loss", 0)
|
||
_tp = parsed.get("take_profit", 0)
|
||
_pos = parsed.get("position", "")
|
||
_msg = f"\U0001f4c8 {_name}({code}) 价{_p}\u219212维分析生成买入信号！区间{_el}~{_eh} 损{_sl} 盈{_tp} 仓位{_pos}"
|
||
import urllib.request, json as _jj
|
||
_req = urllib.request.Request("http://127.0.0.1:5805/",
|
||
data=_jj.dumps({"body": _msg, "to": "hmo@yoin.fun", "type": "chat"}).encode(),
|
||
headers={"Content-Type": "application/json"})
|
||
urllib.request.urlopen(_req, timeout=5)
|
||
print(f" \U0001f4e8 XMPP推送成功: {_msg[:60]}")
|
||
except Exception as _e:
|
||
print(f" \u26a0\ufe0f XMPP推送失败: {_e}")
|
||
|
||
conn.close()
|
||
|
||
def process_stock(code, force_today=False):
|
||
"""处理单只股票"""
|
||
print(f"\n{'='*50}")
|
||
print(f"处理: {code}")
|
||
print(f"{'='*50}")
|
||
|
||
if in_cooldown(code):
|
||
print(f" \u23ed 冷却期内，跳过")
|
||
return False
|
||
|
||
# 有分析且未过期 \u2192 跳过（除非 force_today 且今早未评）
|
||
if has_llm_analysis(code) and not analysis_stale(code, force_today):
|
||
print(f" \u23ed 已有12维分析且未过期，跳过")
|
||
return False
|
||
|
||
print(f" 收集数据...", flush=True)
|
||
data = collect_data(code)
|
||
if not data.get("price"):
|
||
print(f" \u26a0\ufe0f 无价格数据，跳过")
|
||
return False
|
||
|
||
print(f" 调LLM生成九维分析...", flush=True)
|
||
prompt = build_prompt(data)
|
||
|
||
# ── 使用共享 LLM 客户端（替代 curl subprocess）──
|
||
result = call_llm(prompt, model=REASSESS_MODEL, max_tokens=4096)
|
||
|
||
if not result["ok"]:
|
||
print(f" \u274c LLM调用失败: {result.get('error','未知错误')}")
|
||
return False
|
||
|
||
full_text = result["content"]
|
||
print(f" \u2705 LLM返回({len(full_text)}字, {result['elapsed']:.1f}s, 尝试{result['attempts']}次)", flush=True)
|
||
|
||
parsed = parse_response(full_text)
|
||
print(f" 信号={parsed['signal']} 区间={parsed['entry_low']}~{parsed['entry_high']} 损={parsed['stop_loss']} 盈={parsed['take_profit']} 仓位={parsed['position']}")
|
||
|
||
save_result(code, full_text, parsed)
|
||
print(f" \u2705 已保存到DB")
|
||
return True
|
||
|
||
def main():
|
||
# ── 双通道预检：OCG直连 + hermes gateway 兜底，全挂才退出 ──
|
||
_ocg_ok = ocg_alive()
|
||
_gw_ok = gateway_alive()
|
||
if not _ocg_ok and not _gw_ok:
|
||
print("[FATAL] OCG上游与hermes gateway均不可用，退出")
|
||
sys.exit(1)
|
||
if not _ocg_ok:
|
||
print("[WARN] OCG直连不可用，将使用gateway兜底（agent运行时，较慢）")
|
||
if not _gw_ok:
|
||
print("[WARN] hermes gateway不可用，仅使用OCG直连")
|
||
|
||
codes = []
|
||
force_today = "--today" in sys.argv
|
||
dtype = None
|
||
if "--type" in sys.argv:
|
||
idx = sys.argv.index("--type")
|
||
dtype = sys.argv[idx + 1] # holding | watchlist | all
|
||
if "--code" in sys.argv:
|
||
idx = sys.argv.index("--code")
|
||
codes = [sys.argv[idx+1]]
|
||
else:
|
||
# 按类型筛选 active 策略
|
||
type_map = {"holding": "持仓策略", "watchlist": "自选策略"}
|
||
conn = sqlite3.connect(DB)
|
||
if dtype in type_map:
|
||
rows = conn.execute(
|
||
"SELECT code FROM holding_strategies WHERE status='active' AND decision_type=? ORDER BY code",
|
||
(type_map[dtype],)).fetchall()
|
||
else:
|
||
rows = conn.execute(
|
||
"SELECT code FROM holding_strategies WHERE status='active' ORDER BY decision_type, code").fetchall()
|
||
conn.close()
|
||
codes = [r[0] for r in rows]
|
||
|
||
print(f"待处理: {len(codes)}只 (type={dtype or 'all'}, force_today={force_today})")
|
||
|
||
ok = 0
|
||
fail = 0
|
||
skip = 0
|
||
for i, code in enumerate(codes):
|
||
if has_llm_analysis(code) and not analysis_stale(code, force_today):
|
||
print(f" [{i+1}/{len(codes)}] \u23ed {code} 已有12维分析且未过期")
|
||
skip += 1
|
||
continue
|
||
|
||
print(f" [{i+1}/{len(codes)}] ", end="", flush=True)
|
||
if process_stock(code, force_today):
|
||
ok += 1
|
||
else:
|
||
fail += 1
|
||
|
||
# 间隔8秒（pro model较重但gateway可承受；retry逻辑吸收瞬断）
|
||
if i < len(codes) - 1:
|
||
print(f" 等待8秒...", flush=True)
|
||
time.sleep(8)
|
||
|
||
print(f"\n{'='*50}")
|
||
print(f"完成: {ok}成功, {fail}失败, {skip}跳过")
|
||
print(f"{'='*50}")
|
||
|
||
if __name__ == "__main__":
|
||
main()
|