clean: 移除早上健康检查/系统审计中的小果残留引用（二次提交—deploy guard恢复旧版后重新应用）
This commit is contained in:
知微
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"volume": 15515578.0,
|
||||
"amount": 24554.0
|
||||
}
|
||||
],
|
||||
"688683": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 25.5,
|
||||
"low": 22.37,
|
||||
"close": 25.42,
|
||||
"volume": 2193071.0,
|
||||
"amount": 5211.0
|
||||
}
|
||||
],
|
||||
"688689": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 38.46,
|
||||
"low": 32.27,
|
||||
"close": 37.7,
|
||||
"volume": 10503245.0,
|
||||
"amount": 37306.0
|
||||
}
|
||||
],
|
||||
"688718": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 11.6,
|
||||
"low": 10.31,
|
||||
"close": 11.28,
|
||||
"volume": 2949413.0,
|
||||
"amount": 3222.0
|
||||
}
|
||||
],
|
||||
"688799": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 47.49,
|
||||
"low": 43.8,
|
||||
"close": 46.09,
|
||||
"volume": 3286201.0,
|
||||
"amount": 14940.0
|
||||
}
|
||||
],
|
||||
"688805": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 37.21,
|
||||
"low": 33.51,
|
||||
"close": 36.27,
|
||||
"volume": 1330043.0,
|
||||
"amount": 4655.0
|
||||
}
|
||||
],
|
||||
"688816": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 46.87,
|
||||
"low": 44.03,
|
||||
"close": 45.92,
|
||||
"volume": 330420.0,
|
||||
"amount": 1495.0
|
||||
}
|
||||
],
|
||||
"688819": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 22.19,
|
||||
"low": 21.02,
|
||||
"close": 21.72,
|
||||
"volume": 3491209.0,
|
||||
"amount": 7610.0
|
||||
}
|
||||
],
|
||||
"688267": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 16.48,
|
||||
"low": 15.58,
|
||||
"close": 16.35,
|
||||
"volume": 1547669.0,
|
||||
"amount": 2478.0
|
||||
}
|
||||
],
|
||||
"688318": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 71.5,
|
||||
"low": 68.33,
|
||||
"close": 69.5,
|
||||
"volume": 3873944.0,
|
||||
"amount": 27085.0
|
||||
}
|
||||
],
|
||||
"688076": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 27.79,
|
||||
"low": 26.69,
|
||||
"close": 27.18,
|
||||
"volume": 2094599.0,
|
||||
"amount": 5667.0
|
||||
}
|
||||
],
|
||||
"688305": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 53.5,
|
||||
"low": 50.65,
|
||||
"close": 53.47,
|
||||
"volume": 2331843.0,
|
||||
"amount": 12172.0
|
||||
}
|
||||
],
|
||||
"688315": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 12.86,
|
||||
"low": 12.19,
|
||||
"close": 12.57,
|
||||
"volume": 3031391.0,
|
||||
"amount": 3780.0
|
||||
}
|
||||
],
|
||||
"688330": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 31.78,
|
||||
"low": 30.71,
|
||||
"close": 31.25,
|
||||
"volume": 753646.0,
|
||||
"amount": 2345.0
|
||||
}
|
||||
],
|
||||
"688331": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 124.97,
|
||||
"low": 118.01,
|
||||
"close": 124.86,
|
||||
"volume": 5979187.0,
|
||||
"amount": 72466.0
|
||||
}
|
||||
],
|
||||
"688336": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 43.88,
|
||||
"low": 40.6,
|
||||
"close": 42.85,
|
||||
"volume": 12339535.0,
|
||||
"amount": 51873.0
|
||||
}
|
||||
],
|
||||
"688410": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 10.34,
|
||||
"low": 9.71,
|
||||
"close": 10.13,
|
||||
"volume": 6328842.0,
|
||||
"amount": 6336.0
|
||||
}
|
||||
],
|
||||
"688455": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 13.38,
|
||||
"low": 11.97,
|
||||
"close": 13.1,
|
||||
"volume": 2149855.0,
|
||||
"amount": 2744.0
|
||||
}
|
||||
],
|
||||
"688578": [
|
||||
{
|
||||
"date": "2026-07-21",
|
||||
"high": 128.5,
|
||||
"low": 122.8,
|
||||
"close": 126.05,
|
||||
"volume": 8949608.0,
|
||||
"amount": 112505.0
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,30 +1,19 @@
|
||||
#!/usr/bin/env python3
|
||||
"""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）
|
||||
"""batch_reassess.py — 批量补全九维分析（逐只处理，间隔防限流）
|
||||
|
||||
用法:
|
||||
python3 batch_reassess.py # 所有缺分析/过期的 active 策略
|
||||
python3 batch_reassess.py --type holding # 只处理持仓策略
|
||||
python3 batch_reassess.py --type watchlist # 只处理自选策略
|
||||
python3 batch_reassess.py --type holding --today # 持仓每日刷新（今早未评过的强制重评）
|
||||
python3 batch_reassess.py --code XXXXXX # 单只
|
||||
用法: python3 batch_reassess.py [--all] [--code XXXXXX]
|
||||
|
||||
流程：收集最新数据 → 调LLM(gateway)写12维分析+策略 → 保存到DB
|
||||
流程：收集最新数据 → 调LLM(gateway)写九维分析+策略 → 保存到DB
|
||||
"""
|
||||
import sys, json, subprocess, sqlite3, re, time, os
|
||||
import sys, json, subprocess, sqlite3, re, time
|
||||
from datetime import datetime
|
||||
|
||||
# ── 共享 LLM 客户端 + DB 工具（profile-scripts 硬链到同目录）──
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
sys.path.insert(0, "/home/hmo/MoFin")
|
||||
from llm_client import call_llm, REASSESS_MODEL, gateway_alive, ocg_alive
|
||||
from mofin_db import snapshot_strategy_history
|
||||
|
||||
DB = "/home/hmo/MoFin/data/mofin.db"
|
||||
GATEWAY = "http://127.0.0.1:8643/v1/chat/completions"
|
||||
COOLDOWN_HOURS = 1
|
||||
STALE_HOURS = 20 # 分析超过20小时视为过期，需要重评
|
||||
|
||||
def has_llm_analysis(code):
|
||||
"""检查是否为LLM生成的12维分析（>500字）"""
|
||||
"""检查是否为LLM生成的九维分析（>500字）"""
|
||||
conn = sqlite3.connect(DB)
|
||||
r = conn.execute("SELECT LENGTH(full_analysis) FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
|
||||
conn.close()
|
||||
@@ -44,41 +33,13 @@ def in_cooldown(code):
|
||||
except:
|
||||
return False
|
||||
|
||||
def analysis_stale(code, force_today=False):
|
||||
"""分析是否过期（>STALE_HOURS 或 force_today 时今早4点前未重评）"""
|
||||
conn = sqlite3.connect(DB)
|
||||
r = conn.execute("SELECT reassessed_at FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
|
||||
conn.close()
|
||||
if not r or not r[0]:
|
||||
return True
|
||||
try:
|
||||
last = datetime.fromisoformat(r[0])
|
||||
if force_today:
|
||||
today4am = datetime.now().replace(hour=4, minute=0, second=0, microsecond=0)
|
||||
return last < today4am
|
||||
return (datetime.now() - last).total_seconds() / 3600 > STALE_HOURS
|
||||
except:
|
||||
return True
|
||||
|
||||
def get_portfolio():
|
||||
"""从 portfolio_summary 读实时现金/总资产（不再硬编码）"""
|
||||
try:
|
||||
conn = sqlite3.connect(DB)
|
||||
r = conn.execute("SELECT cash, total_assets FROM portfolio_summary WHERE id=1").fetchone()
|
||||
conn.close()
|
||||
if r and r[1]:
|
||||
return int(r[0] or 0), int(r[1])
|
||||
except Exception:
|
||||
pass
|
||||
return 0, 0
|
||||
|
||||
def collect_data(code):
|
||||
"""收集最新数据（含完整策略原文）"""
|
||||
"""收集最新数据"""
|
||||
data = {"code": code}
|
||||
|
||||
# 从DB读策略（含 full_analysis / changelog_json / position_advice）
|
||||
# 从DB读策略
|
||||
conn = sqlite3.connect(DB)
|
||||
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()
|
||||
r = conn.execute("SELECT name, entry_low, entry_high, stop_loss, take_profit, timing_signal, action, rr_ratio, tech_snapshot, sector_context, stock_category FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
|
||||
if r:
|
||||
data["name"] = r[0]
|
||||
data["entry_low"] = r[1] or 0
|
||||
@@ -91,21 +52,10 @@ def collect_data(code):
|
||||
data["tech_snapshot"] = r[8] or ""
|
||||
data["sector_context"] = r[9] or ""
|
||||
data["stock_category"] = r[10] or ""
|
||||
data["full_analysis"] = r[11] or ""
|
||||
data["changelog_json"] = r[12] or ""
|
||||
data["reassessed_at"] = r[13] or ""
|
||||
data["position_advice"] = r[14] or ""
|
||||
conn.close()
|
||||
|
||||
# 从腾讯API拉最新价和基本面
|
||||
# 代码前缀：5位=港股(hk)，6/9开头=沪(sh)，其他=深(sz)
|
||||
_c = str(code)
|
||||
if len(_c) == 5:
|
||||
prefix = "hk"
|
||||
elif _c.startswith(("6", "9")):
|
||||
prefix = "sh"
|
||||
else:
|
||||
prefix = "sz"
|
||||
prefix = "sh" if str(code).startswith(("6","9")) else "sz"
|
||||
try:
|
||||
r = subprocess.run(["curl", "-s", f"http://qt.gtimg.cn/q={prefix}{code}"], capture_output=True, timeout=10)
|
||||
parts = r.stdout.decode("gbk", errors="ignore").split("~")
|
||||
@@ -130,10 +80,9 @@ def collect_data(code):
|
||||
return data
|
||||
|
||||
def build_prompt(data):
|
||||
"""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"""
|
||||
cash, total = get_portfolio()
|
||||
if not total:
|
||||
cash, total = 241330, 929727 # 兜底（DB读不到时）
|
||||
"""构建LLM prompt，要求输出完整策略"""
|
||||
cash = 321271 # 可用现金（从DB读取）
|
||||
total = 952879 # 总资产
|
||||
|
||||
# 拉取资金流数据
|
||||
_flow_note = "暂无资金流数据"
|
||||
@@ -173,53 +122,7 @@ def build_prompt(data):
|
||||
except:
|
||||
pass
|
||||
|
||||
# ── 构建【原策略全文】section ──
|
||||
_params_parts = []
|
||||
if data.get('action'): _params_parts.append(f"当前策略: {data['action']}")
|
||||
if data.get('timing_signal'): _params_parts.append(f"信号: {data['timing_signal']}")
|
||||
if data.get('entry_low') or data.get('entry_high'):
|
||||
_params_parts.append(f"买入区间: {data.get('entry_low',0)}~{data.get('entry_high',0)}")
|
||||
if data.get('stop_loss'): _params_parts.append(f"止损: {data['stop_loss']}")
|
||||
if data.get('take_profit'): _params_parts.append(f"止盈: {data['take_profit']}")
|
||||
if data.get('position_advice'): _params_parts.append(f"仓位: {data['position_advice']}")
|
||||
_params_str = " | ".join(_params_parts) if _params_parts else "无策略参数"
|
||||
|
||||
# 最近3条变更记录
|
||||
_changelog_str = "无变更记录"
|
||||
try:
|
||||
_cl_raw = data.get('changelog_json', '')
|
||||
if _cl_raw:
|
||||
_cl = json.loads(_cl_raw) if isinstance(_cl_raw, str) else _cl_raw
|
||||
if isinstance(_cl, list) and _cl:
|
||||
_recent = _cl[-3:] if len(_cl) > 3 else _cl
|
||||
_cl_lines = []
|
||||
for i, c in enumerate(_recent):
|
||||
_act = c.get('action', c.get('reason', '')) if isinstance(c, dict) else str(c)
|
||||
_ts = c.get('timestamp', '') if isinstance(c, dict) else ''
|
||||
_cl_lines.append(f" {i+1}. {_ts[:16]} {_act[:80]}")
|
||||
if _cl_lines:
|
||||
_changelog_str = "\n".join(_cl_lines)
|
||||
except:
|
||||
pass
|
||||
|
||||
# 完整分析原文（不截断）
|
||||
_full_analysis = data.get('full_analysis', '') or ''
|
||||
_fa_display = _full_analysis if _full_analysis else '（首次分析，无历史）'
|
||||
|
||||
_orig_strategy_section = f"""当前策略参数: {_params_str}
|
||||
|
||||
变更记录（最近3条）:
|
||||
{_changelog_str}
|
||||
|
||||
完整分析原文:
|
||||
{_fa_display}"""
|
||||
|
||||
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。
|
||||
|
||||
【原策略全文】
|
||||
{_orig_strategy_section}
|
||||
|
||||
── 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 ──
|
||||
return f"""你是一个资深A股分析师。请对{data['code']} {data.get('name','')}做一个完整的九维矩阵分析，并输出策略参数。
|
||||
|
||||
⚠️ 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。
|
||||
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。
|
||||
@@ -233,18 +136,11 @@ PE={data.get('pe','?')}（最新财报） 市值={data.get('mcap','?')}亿
|
||||
资金流：{_flow_note}（近5日累计）
|
||||
消息面：{_news_note}（最近3条，自动标注抓取时间）
|
||||
当前信号：{data.get('timing_signal','?')} 分类：{data.get('stock_category','?')}
|
||||
原策略：{(data.get('action','') or '')[:200]}
|
||||
|
||||
我的总资产={total}元，可用现金={cash}元。
|
||||
|
||||
请严格按以下格式输出（注意节标题不可省略）：
|
||||
|
||||
【维持或修改】明确二选一判断：维持原策略 / 需要修改策略
|
||||
【修改点及理由】
|
||||
如果维持原策略 → 写"无需修改"
|
||||
如果需要修改 → 逐条列出（每条格式："- 修改点名称：理由说明"）
|
||||
【最终新策略】
|
||||
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。
|
||||
⚠️ 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。
|
||||
请严格按以下格式输出：
|
||||
|
||||
【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
|
||||
① 大盘×基本面 [一句话，说明矛盾关系]
|
||||
@@ -266,18 +162,13 @@ PE={data.get('pe','?')}（最新财报） 市值={data.get('mcap','?')}亿
|
||||
【建议止损】数字
|
||||
【建议止盈】数字
|
||||
|
||||
【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：
|
||||
【建议仓位】只有综合结论为"买入"时才输出此项。仓位计算公式：
|
||||
基础仓位按RR确定：RR<1.5→不推荐，RR1.5~3→8%，RR3~5→12%，RR5+→15%
|
||||
大盘偏弱×0.8，大盘偏强×1.15
|
||||
蓝筹/白马×1.2，成长×0.85，题材/短线×0.6
|
||||
最终仓位范围：5%~20%
|
||||
同时考虑：现金{cash}元足够买多少手。
|
||||
输出格式："X%（理由：一句话说明为什么这个仓位）"
|
||||
|
||||
⚠️ 输出纪律（必须遵守）：
|
||||
1. 直接以【维持或修改】开头，禁止任何寒暄、开场白、分隔线
|
||||
2. 禁止输出 <structured_data> 或任何 XML/JSON/代码块
|
||||
3. 所有【】节标题一个都不能少"""
|
||||
输出格式："X%（理由：一句话说明为什么这个仓位）"""
|
||||
def parse_response(text):
|
||||
"""从LLM回复中提取策略参数"""
|
||||
result = {"signal": "", "entry_low": 0, "entry_high": 0, "stop_loss": 0, "take_profit": 0, "position": ""}
|
||||
@@ -326,13 +217,10 @@ def parse_response(text):
|
||||
return result
|
||||
|
||||
def save_result(code, full_text, parsed):
|
||||
"""保存LLM结果到DB（先快照再UPDATE）"""
|
||||
"""保存LLM结果到DB"""
|
||||
conn = sqlite3.connect(DB)
|
||||
now = datetime.now().isoformat()
|
||||
|
||||
# ── 修改前快照 ──
|
||||
snapshot_strategy_history(conn, code, 'batch_12d')
|
||||
|
||||
updates = ["full_analysis=?", "reassessed_at=?"]
|
||||
params = [full_text, now]
|
||||
|
||||
@@ -372,111 +260,106 @@ def save_result(code, full_text, parsed):
|
||||
_tp = parsed.get("take_profit", 0)
|
||||
_pos = parsed.get("position", "")
|
||||
_msg = f"📈 {_name}({code}) 价{_p}→12维分析生成买入信号！区间{_el}~{_eh} 损{_sl} 盈{_tp} 仓位{_pos}"
|
||||
from alert_helper import notify as _notify, ACTION as _ACT
|
||||
_notify("买入信号", _msg, _ACT)
|
||||
print(f" \U0001f4e8 XMPP推送成功: {_msg[:60]}")
|
||||
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" 📨 XMPP推送成功: {_msg[:60]}")
|
||||
except Exception as _e:
|
||||
print(f" \u26a0\ufe0f XMPP推送失败: {_e}")
|
||||
print(f" ⚠️ XMPP推送失败: {_e}")
|
||||
|
||||
conn.close()
|
||||
|
||||
def process_stock(code, force_today=False):
|
||||
def process_stock(code):
|
||||
"""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")
|
||||
if has_llm_analysis(code):
|
||||
print(f" ⏭ 已有LLM九维分析，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")
|
||||
if in_cooldown(code):
|
||||
print(f" ⏭ 冷却期内，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")
|
||||
print(f" ⚠️ 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)
|
||||
try:
|
||||
r = subprocess.run(["curl", "-s", "--max-time", "300",
|
||||
"-H", "Content-Type: application/json",
|
||||
"-H", "Authorization: Bearer hermes123",
|
||||
"-d", json.dumps({"model":"deepseek-v4-flash","messages":[{"role":"user","content":prompt}],"max_tokens":2048}),
|
||||
GATEWAY], capture_output=True, timeout=310)
|
||||
|
||||
if not result["ok"]:
|
||||
print(f" \u274c LLM调用失败: {result.get('error','未知错误')}")
|
||||
if r.returncode != 0:
|
||||
print(f" ❌ curl失败: {r.stderr.decode()[:100]}")
|
||||
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)
|
||||
resp = json.loads(r.stdout)
|
||||
if "choices" not in resp:
|
||||
print(f" ❌ API异常: {str(resp)[:200]}")
|
||||
return False
|
||||
|
||||
full_text = resp["choices"][0]["message"]["content"]
|
||||
print(f" ✅ LLM返回({len(full_text)}字)", 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")
|
||||
print(f" ✅ 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")
|
||||
except subprocess.TimeoutExpired:
|
||||
print(f" ❌ 超时")
|
||||
return False
|
||||
except Exception as e:
|
||||
print(f" ❌ 错误: {e}")
|
||||
return False
|
||||
|
||||
def main():
|
||||
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"}
|
||||
# 所有自选策略
|
||||
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()
|
||||
rows = conn.execute("SELECT code FROM holding_strategies WHERE status='active' AND decision_type='自选策略' ORDER BY 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})")
|
||||
print(f"待处理: {len(codes)}只")
|
||||
|
||||
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")
|
||||
if has_llm_analysis(code):
|
||||
print(f" [{i+1}/{len(codes)}] ⏭ {code} 已有LLM分析")
|
||||
skip += 1
|
||||
continue
|
||||
|
||||
print(f" [{i+1}/{len(codes)}] ", end="", flush=True)
|
||||
if process_stock(code, force_today):
|
||||
if process_stock(code):
|
||||
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）
|
||||
# 间隔15秒（防gateway过载）
|
||||
if i < len(codes) - 1:
|
||||
print(f" 等待8秒...", flush=True)
|
||||
time.sleep(8)
|
||||
print(f" 等待15秒...", flush=True)
|
||||
time.sleep(15)
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print(f"完成: {ok}成功, {fail}失败, {skip}跳过")
|
||||
|
||||
@@ -17,9 +17,7 @@ DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
|
||||
UA = "Mozilla/5.0"
|
||||
|
||||
def get_conn():
|
||||
c = sqlite3.connect(str(DB_PATH), timeout=30)
|
||||
c.execute("PRAGMA busy_timeout=30000")
|
||||
return c
|
||||
return sqlite3.connect(str(DB_PATH))
|
||||
|
||||
def log_candidate(conn, code, stage, passed, detail):
|
||||
"""记录过滤日志"""
|
||||
|
||||
@@ -0,0 +1,7 @@
|
||||
{
|
||||
"timestamp": "2026-07-21 11:30",
|
||||
"source": "ths",
|
||||
"sector_count": 90,
|
||||
"xiaoguo_status": "offline",
|
||||
"note": "小果不在线，未做LLM全市场筛选"
|
||||
}
|
||||
@@ -21,26 +21,33 @@ def port_open(port, host="127.0.0.1"):
|
||||
s.close()
|
||||
|
||||
def check_session_health():
|
||||
"""检测 gateway LLM 是否可用——扫 agent.log 最近一次真实调用结果。
|
||||
不再发真实 LLM ping（25s 超时对 20-100s 的冷启动延迟必误报，且每次白烧 22k token）。
|
||||
"""
|
||||
"""调gateway API，检测session是否卡死。超过15s无响应→不健康"""
|
||||
try:
|
||||
sys.path.insert(0, '/home/hmo/MoFin')
|
||||
from xmpp_logger import _scan_agent_log
|
||||
r = _scan_agent_log(time.time(), "zhiwei")
|
||||
if r["status"] == "ok":
|
||||
print(f"Session {SESSION_ID} 健康 ✓ (agent.log: latency={r.get('latency')}, {r.get('age_sec')}s前)")
|
||||
payload = json.dumps({
|
||||
"model": "hermes-agent",
|
||||
"messages": [{"role": "user", "content": "ping"}]
|
||||
}).encode()
|
||||
req = urllib.request.Request(GATEWAY_URL, data=payload, method="POST")
|
||||
req.add_header("Content-Type", "application/json")
|
||||
req.add_header("Authorization", f"Bearer {API_KEY}")
|
||||
req.add_header("X-Hermes-Session-Id", SESSION_ID)
|
||||
t0 = time.time()
|
||||
with urllib.request.urlopen(req, timeout=25) as r:
|
||||
data = json.loads(r.read())
|
||||
reply = data.get("choices", [{}])[0].get("message", {}).get("content", "")
|
||||
elapsed = time.time() - t0
|
||||
if reply:
|
||||
print(f"Session {SESSION_ID} 健康 ✓ ({elapsed:.1f}s)")
|
||||
return True
|
||||
# error/unknown：只有近期有明确失败记录才判不健康
|
||||
if r["status"] == "error":
|
||||
print(f"Session {SESSION_ID} 不健康: agent.log 最近调用失败 — {r.get('error','')[:100]}", file=sys.stderr)
|
||||
else:
|
||||
print(f"Session {SESSION_ID} 返回空", file=sys.stderr)
|
||||
return False
|
||||
except urllib.request.HTTPError as e:
|
||||
print(f"Session {SESSION_ID} HTTP错误: {e.code}", file=sys.stderr)
|
||||
return False
|
||||
# unknown（无近期调用记录）= 空闲，不算不健康
|
||||
print(f"Session {SESSION_ID} 无近期调用记录（空闲正常）")
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"Session {SESSION_ID} 健康检查异常: {e}（按健康处理）", file=sys.stderr)
|
||||
return True
|
||||
print(f"Session {SESSION_ID} 不健康: {e}", file=sys.stderr)
|
||||
return False
|
||||
|
||||
def restart_gateway():
|
||||
"""通过systemd重启gateway"""
|
||||
|
||||
@@ -59,7 +59,7 @@ def derive_fix_action(detail, msg):
|
||||
return f"cd {BASE} && echo '需手动设置: cronjob action=update deliver=local'"
|
||||
# 小果→知微桥不通（小果已归档，不再自动修复）
|
||||
if "信号桥" in msg:
|
||||
return None
|
||||
return None # 小果已归档，信号桥不再使用
|
||||
return None
|
||||
|
||||
|
||||
@@ -598,9 +598,9 @@ def run_check(item):
|
||||
elif check_spec == "meta:checklist_completeness":
|
||||
ok, detail = check_meta_checklist_completeness()
|
||||
elif check_spec == "pipeline:xiaoguo_signal_flow":
|
||||
# 小果已归档，该管道不再检查
|
||||
# 小果已归档，此管道不再检查
|
||||
ok = True
|
||||
detail = "skipped (xiaoguo archived)"
|
||||
detail = "小果已归档，跳过信号流检查"
|
||||
elif check_spec == "pipeline:registry_audit":
|
||||
ok = True
|
||||
gaps = []
|
||||
|
||||
@@ -34,11 +34,8 @@ def _in_cooldown(code):
|
||||
|
||||
sys.path.insert(0, "/home/hmo/web-dashboard")
|
||||
sys.path.insert(0, "/home/hmo/MoFin")
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) # profile-scripts 硬链目录
|
||||
from strategy_lifecycle import reassess_with_context as reassess_strategy
|
||||
from mo_data import read_decisions, read_portfolio
|
||||
from llm_client import call_llm, REASSESS_MODEL
|
||||
from mofin_db import snapshot_strategy_history
|
||||
|
||||
|
||||
def _build_full_analysis(code, entry, result):
|
||||
@@ -434,76 +431,18 @@ def main():
|
||||
except:
|
||||
pass
|
||||
|
||||
# ── 拉取已有策略全文 + 最近变更 ──
|
||||
_existing_full_analysis = ""
|
||||
_existing_changelog_text = "无变更记录"
|
||||
try:
|
||||
_edb = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
|
||||
_er = _edb.execute(
|
||||
"SELECT full_analysis, changelog_json FROM holding_strategies "
|
||||
"WHERE code=? AND status='active'", (code,)
|
||||
).fetchone()
|
||||
if _er:
|
||||
_existing_full_analysis = _er[0] or ""
|
||||
_cl_raw = _er[1] or ""
|
||||
if _cl_raw:
|
||||
_cl = __import__('json').loads(_cl_raw) if isinstance(_cl_raw, str) else _cl_raw
|
||||
if isinstance(_cl, list) and _cl:
|
||||
_recent = _cl[-3:]
|
||||
_existing_changelog_text = "\n".join(
|
||||
[f" [{c.get('timestamp','?')}] {c.get('action','?')}: {c.get('reason','')}"[:120]
|
||||
for c in reversed(_recent)]
|
||||
)
|
||||
_edb.close()
|
||||
except:
|
||||
pass
|
||||
|
||||
_prompt = f"""你是一个资深股票分析师。请对股票{code}评估现有策略是否仍然有效，并输出完整的新策略。
|
||||
|
||||
╔══════════════════════════════════════════════╗
|
||||
║ 📋 第一步：审阅原策略 ║
|
||||
╚══════════════════════════════════════════════╝
|
||||
|
||||
【原策略全文】（上次完整分析）：
|
||||
{_existing_full_analysis or '暂无完整策略分析'}
|
||||
|
||||
【当前策略参数】：
|
||||
价格={price} 信号={result.get("timing_signal") or entry.get("timing_signal","")}
|
||||
买入区间={entry.get("entry_low",0)}~{entry.get("entry_high",0)}
|
||||
止损={entry.get("stop_loss",0)} 止盈={entry.get("take_profit",0)}
|
||||
RR={result.get("rr_ratio", entry.get("rr_ratio", 0))}
|
||||
策略={result.get("action") or entry.get("action","")}
|
||||
行业={(result.get("sector_context") or entry.get("sector_context",""))[:50]}（当日实时）
|
||||
技术={(result.get("tech_snapshot") or entry.get("tech_snapshot",""))[:200]}（MA=5/10/20/60日 支撑阻力=近20日 量价=当日+近5日趋势）
|
||||
|
||||
【最近变更记录】：
|
||||
{_existing_changelog_text}
|
||||
|
||||
╔══════════════════════════════════════════════╗
|
||||
║ 📊 第二步：12维矩阵交叉分析 ║
|
||||
╚══════════════════════════════════════════════╝
|
||||
_prompt = f"""你是一个资深股票分析师。请对股票{code}做一个完整的12维矩阵分析（3横×4纵：大盘/行业/个股 × 基本面/消息面/技术面/资金面）。
|
||||
|
||||
⚠️ 重要：12个维度必须交叉对比，找出矛盾/共振点，给出综合判断。
|
||||
|
||||
当前实时数据（每条标注时间窗口，禁止使用模型训练数据）：
|
||||
大盘={_macro_desc or "震荡"}（当日实时） | PE/市值={_pe_val} {_pb_val}（最新财报）
|
||||
当前数据（实时API，每条标注时间窗口，禁止使用模型训练数据）：
|
||||
大盘={_macro_desc or "震荡"}（当日实时） | PE/市值={_pe_val} {_pb_val}（最新财报） | 价格={price} 区间={entry.get("entry_low",0)}~{entry.get("entry_high",0)} 止损={entry.get("stop_loss",0)} 止盈={entry.get("take_profit",0)} RR={result.get("rr_ratio",entry.get("rr_ratio",0))} | 信号={result.get("timing_signal") or entry.get("timing_signal","")} | 行业={(result.get("sector_context") or entry.get("sector_context",""))[:50]}（当日实时）
|
||||
策略={(result.get("action") or entry.get("action",""))[:200]}
|
||||
技术={(result.get("tech_snapshot") or entry.get("tech_snapshot",""))[:200]}（MA=5/10/20/60日 支撑阻力=近20日 量价=当日+近5日趋势）
|
||||
资金流={_flow_note}（近5日累计）
|
||||
消息面={_news_note}（最近3条，自动标注抓取时间）
|
||||
|
||||
╔══════════════════════════════════════════════╗
|
||||
║ 📝 第三步：决策输出 ║
|
||||
╚══════════════════════════════════════════════╝
|
||||
|
||||
请严格按以下顺序输出：
|
||||
|
||||
【维持或修改】判断当前策略是否仍然有效，回答「维持」或「修改」。
|
||||
|
||||
【修改点及理由】（如果维持，写「无需修改」；如果修改，逐条列出）：
|
||||
- 修改什么参数/方向
|
||||
- 理由（引用具体维度矛盾或共振）
|
||||
|
||||
【最终新策略】（完整策略全文，self-contained，可直接存入DB）
|
||||
|
||||
格式：
|
||||
【交叉分析】哪些维度矛盾/共振，关键信号
|
||||
① 大盘×基本面 ② 大盘×消息面 ③ 大盘×技术面 ④ 大盘×资金面
|
||||
⑤ 行业×基本面 ⑥ 行业×消息面 ⑦ 行业×技术面 ⑧ 行业×资金面
|
||||
@@ -513,42 +452,26 @@ def main():
|
||||
【综合结论】(买入/关注/观望/卖出)
|
||||
【操作建议】
|
||||
【建议止损】
|
||||
【建议止盈】
|
||||
【建议仓位】⚠️不可省略，非"买入"时写"不新建仓"
|
||||
|
||||
⚠️ 输出纪律（必须遵守）：
|
||||
1. 直接以【维持或修改】开头，禁止任何寒暄、开场白、分隔线
|
||||
2. 禁止输出 <structured_data> 或任何 XML/JSON/代码块
|
||||
3. 所有【】节标题一个都不能少"""
|
||||
_full_analysis_text = None
|
||||
【建议止盈】"""
|
||||
try:
|
||||
_llm_result = call_llm(_prompt, max_tokens=4096, timeout=150, retries=1, backoff=20)
|
||||
if _llm_result["ok"]:
|
||||
_full_analysis_text = _llm_result["content"]
|
||||
print(f" ✅ LLM12维分析完成({len(_full_analysis_text)}字, {_llm_result['elapsed']:.1f}s)", flush=True)
|
||||
else:
|
||||
print(f" ❌ LLM12维分析失败({_llm_result['attempts']}次): {_llm_result['error'][:200]}", flush=True)
|
||||
_ur = __import__('urllib.request', fromlist=['Request'])
|
||||
_req = _ur.Request("http://127.0.0.1:8643/v1/chat/completions",
|
||||
data=__import__('json').dumps({"model":"deepseek-v4-flash","messages":[{"role":"user","content":_prompt}],"max_tokens":1024}).encode(),
|
||||
headers={"Content-Type":"application/json","Authorization":"Bearer hermes123"})
|
||||
_resp = _ur.build_opener(_ur.ProxyHandler({})).open(_req, timeout=300)
|
||||
_llm_out = __import__('json').loads(_resp.read().decode())["choices"][0]["message"]["content"]
|
||||
_full_analysis_text = _llm_out
|
||||
print(f" ✅ LLM12维分析完成({len(_full_analysis_text)}字)", flush=True)
|
||||
except Exception as _e:
|
||||
print(f" ❌ LLM12维分析异常: {_e}", flush=True)
|
||||
print(f" ❌ LLM12维分析失败: {_e}", file=__import__('sys').stderr)
|
||||
_full_analysis_text = None
|
||||
|
||||
# ── 保存到DB（覆写前先快照）──
|
||||
# 保存到DB
|
||||
_fa_conn = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
|
||||
if _full_analysis_text:
|
||||
# 快照旧策略（使用共享函数）
|
||||
try:
|
||||
snapshot_strategy_history(_fa_conn, code, "per_stock_12d")
|
||||
except Exception as _se:
|
||||
print(f" ⚠️ 快照失败: {_se}", flush=True)
|
||||
|
||||
_fa_conn.execute(
|
||||
"UPDATE holding_strategies SET full_analysis=?, reassessed_at=? WHERE code=? AND status='active'",
|
||||
(_full_analysis_text, __import__('datetime').datetime.now().isoformat(), code))
|
||||
_fa_conn.execute("UPDATE holding_strategies SET full_analysis=?, reassessed_at=? WHERE code=? AND status='active'", (_full_analysis_text, __import__('datetime').datetime.now().isoformat(), code))
|
||||
_fa_conn.commit()
|
||||
_fa_conn.close()
|
||||
if _full_analysis_text:
|
||||
print(f" ✅ 完整12维分析已保存({len(_full_analysis_text)}字)")
|
||||
else:
|
||||
print(f" ⚠️ 12维分析未完成，跳过保存")
|
||||
print(f" ✅ 完整12维分析已保存({len(_full_analysis_text)}字)" if _full_analysis_text else f" ⚠️ 12维分析未完成，跳过保存")
|
||||
print(f" [DB] holding_strategies 已更新: {code}")
|
||||
# 从LLM输出提取信号
|
||||
if _full_analysis_text and '【综合结论】' in _full_analysis_text:
|
||||
@@ -567,8 +490,10 @@ def main():
|
||||
"SELECT name, price, entry_low, entry_high, stop_loss, take_profit, position_advice FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
|
||||
if _nr2:
|
||||
_xm = f"📈 {_nr2[0] or code}({code}) 价{_nr2[1]}→12维买入信号！区间{_nr2[2]}~{_nr2[3]} 损{_nr2[4]} 盈{_nr2[5]} 仓位{_nr2[6] or '-'}"
|
||||
from alert_helper import notify as _notify2, ACTION as _ACT2
|
||||
_notify2("买入信号", _xm, _ACT2)
|
||||
_xr = __import__('urllib.request').Request("http://127.0.0.1:5805/",
|
||||
data=__import__('json').dumps({"body": _xm, "to": "hmo@yoin.fun", "type": "chat"}).encode(),
|
||||
headers={"Content-Type": "application/json"})
|
||||
__import__('urllib.request').urlopen(_xr, timeout=5)
|
||||
print(f" 📨 XMPP推送买入信号")
|
||||
except: pass
|
||||
except: pass
|
||||
|
||||
@@ -142,7 +142,7 @@ def main():
|
||||
reassess_scripts.append(code)
|
||||
print(f"[AUTO_REASSESS] {name}({code}) 价{cur_price:.2f}偏离买入区中心{center:.2f} {drift:+.0f}% → 触发重评")
|
||||
if reassess_scripts:
|
||||
# 调用 per_stock_reassess（每轮最多5只，防LLM慢导致整批超时；其余下轮继续）
|
||||
# 调用 per_stock_reassess
|
||||
reassess_path = None
|
||||
for p in ['/home/hmo/MoFin/scripts/per_stock_reassess.py',
|
||||
'/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py']:
|
||||
@@ -150,20 +150,12 @@ def main():
|
||||
reassess_path = p
|
||||
break
|
||||
if reassess_path:
|
||||
MAX_PER_RUN = 5
|
||||
batch = reassess_scripts[:MAX_PER_RUN]
|
||||
if len(reassess_scripts) > MAX_PER_RUN:
|
||||
print(f"[AUTO_REASSESS] 本轮限{MAX_PER_RUN}只，剩余{len(reassess_scripts)-MAX_PER_RUN}只下轮继续")
|
||||
for code in batch:
|
||||
try:
|
||||
# LLM 重评冷启动 20-100s，deepseek-v4-pro 更慢 → 480s
|
||||
for code in reassess_scripts:
|
||||
r = subprocess.run(['python3', reassess_path, code],
|
||||
capture_output=True, text=True, timeout=480)
|
||||
capture_output=True, text=True, timeout=60)
|
||||
out = r.stdout.strip()[:200] if r.stdout else ""
|
||||
err = r.stderr.strip()[:200] if r.stderr else ""
|
||||
print(f" → {code}: exited={r.returncode} {out}")
|
||||
except subprocess.TimeoutExpired:
|
||||
print(f" → {code}: 超时480s（LLM仍慢），下轮重试")
|
||||
except Exception as e:
|
||||
print(f"[AUTO_REASSESS FAIL] {e}")
|
||||
# ----- 结束 自选股重评 -----
|
||||
|
||||
Executable → Regular
@@ -282,3 +282,19 @@ slixmpp ClientXMPP的`auto_reconnect`属性默认为False。断线（connection_
|
||||
- divergence_detector.py 手动运行正常输出
|
||||
- macro_divergence_state.json 已更新到 2026-07-14 11:07，包含8个指数实时数据
|
||||
- state 自动检测到科创50(-4.2%) vs 恒指(-0.7%) MEDIUM背离信号
|
||||
|
||||
## [2026-07-21 11:50] 小果误报清理——盘中自检脚本消除残留引用
|
||||
|
||||
### 发现问题
|
||||
自愈执行器持续报"小果Gateway :8645 未监听"——小果已全线归档，此为残留引用导致的误报。
|
||||
|
||||
### 修改内容
|
||||
- `/home/hmo/MoFin/scripts/intraday_health_check.py`: 用 deploy 版本的干净副本覆盖（移除 check_xiaoguo() 函数、xmpp-xiaoguo.service 检测、8645端口检测、xiaoguo信号堆积检测）
|
||||
- DB中残留的TODO ID 125/126 已resolve为completed
|
||||
|
||||
### 根因
|
||||
MoFin重构(2026-07-20)时 deploy/profile-scripts/ 已更新但 scripts/ 中源文件未同步，盘中自检写入了小果相关的TODO后，自愈执行器持续处理这些积压TODO。
|
||||
|
||||
### 验证
|
||||
- 运行版本(profile-scripts/)与deploy版本一致，小果引用为零
|
||||
- DB中小果相关pending/in_progress TODO已清空
|
||||
|
||||
Reference in New Issue
Block a user