From 05a60cf0d457ff272a2c03cf6c44a202a790530d Mon Sep 17 00:00:00 2001 From: hmo Date: Tue, 21 Jul 2026 23:24:45 +0800 Subject: [PATCH] =?UTF-8?q?revert(34337fc5):=20=E6=81=A2=E5=A4=8D=E8=A2=AB?= =?UTF-8?q?=E7=9F=A5=E5=BE=AE=E4=BA=8C=E6=AC=A1stale=E6=8F=90=E4=BA=A4?= =?UTF-8?q?=E8=A6=86=E7=9B=96=E7=9A=84=E6=98=A8=E6=99=9A=E9=87=8D=E6=9E=84?= =?UTF-8?q?=E2=80=94=E2=80=94batch/per=5Fstock/stale=5Fdetector/fix=5Fgate?= =?UTF-8?q?way=5Fport/candidate=5Ffilter=20=E5=9B=9E=E6=BB=9A=E8=87=B31e71?= =?UTF-8?q?a2d8=E7=89=88=E6=9C=AC=EF=BC=9B=E5=A5=B9=E6=8F=90=E4=BA=A4?= =?UTF-8?q?=E4=B8=AD=E7=9A=84=E8=BF=90=E8=A1=8C=E6=97=B6=E6=96=87=E4=BB=B6?= =?UTF-8?q?(db-shm/db-wal/price=5Fhistory/market=5Fscan=5Fsummary)?= =?UTF-8?q?=E7=A7=BB=E5=87=BA=E8=B7=9F=E8=B8=AA=EF=BC=9B=E4=BF=9D=E7=95=99?= =?UTF-8?q?=E5=85=B6morning=5Fhealth=5Fcheck=E5=B0=8F=E6=9E=9C=E6=B8=85?= =?UTF-8?q?=E7=90=86?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 5 + data/mofin.db-shm | Bin 32768 -> 0 bytes data/mofin.db-wal | 0 data/price_history.json | 2404 ----------------- deploy/profile-scripts/batch_reassess.py | 261 +- deploy/profile-scripts/candidate_filter.py | 4 +- .../data/market_scan_summary.json | 7 - deploy/profile-scripts/fix_gateway_port.py | 43 +- deploy/profile-scripts/per_stock_reassess.py | 129 +- deploy/profile-scripts/stale_detector.py | 22 +- 10 files changed, 332 insertions(+), 2543 deletions(-) delete mode 100644 data/mofin.db-shm delete mode 100644 data/mofin.db-wal delete mode 100644 data/price_history.json delete mode 100644 deploy/profile-scripts/data/market_scan_summary.json diff --git a/.gitignore b/.gitignore index 8ec8b65f..4496f22c 100644 --- a/.gitignore +++ b/.gitignore @@ -39,3 +39,8 @@ scripts/mo_data.py data/prompts/ data/backups/ + +data/mofin.db-shm +data/mofin.db-wal +data/price_history.json +deploy/profile-scripts/data/ diff --git a/data/mofin.db-shm b/data/mofin.db-shm deleted file mode 100644 index 6aecbd297b2141bc7de0c2e9bbeb3ee11b3cb021..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 32768 zcmeI*u?Ye(6b9gTimg~4?qKZ_Ru+zMn_Me6fQ5~{1Gs>ly@d#lV11Ve0b7e}j_-%Z zOF~HC8z8A)tH_z8sv;J7d|pOuc9+@b(Z17kzCE07_h+=%=D4r_+@H@Y>3&kyN?)hJ zG*#|GfB*pk1PBlyK!5-N0t5&UAV7cs0RjXF5FkK+009C72oNAZfB*pk1PBlyK!5-N z0t5&UAV7cs0RjXF5FkK+009C72oNAZfB*pk1PF{(AisDd1PBlyK!5-N0t5&UAV7cs z0RjXF5FkK+009C72n;Jweg6R&_70~LAV7cs0RjXF5FkK+009C72oNAZfB*pk1PBlq Gr$7&sawkRr diff --git a/data/mofin.db-wal b/data/mofin.db-wal deleted file mode 100644 index e69de29b..00000000 diff --git a/data/price_history.json b/data/price_history.json deleted file mode 100644 index f4679c9e..00000000 --- a/data/price_history.json +++ /dev/null @@ -1,2404 +0,0 @@ -{ - 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"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 - } - ] -} \ No newline at end of file diff --git a/deploy/profile-scripts/batch_reassess.py b/deploy/profile-scripts/batch_reassess.py index 196dab1b..5a464459 100644 --- a/deploy/profile-scripts/batch_reassess.py +++ b/deploy/profile-scripts/batch_reassess.py @@ -1,19 +1,30 @@ #!/usr/bin/env python3 -"""batch_reassess.py — 批量补全九维分析（逐只处理，间隔防限流） +"""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） -用法: python3 batch_reassess.py [--all] [--code XXXXXX] +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 -流程：收集最新数据 → 调LLM(gateway)写九维分析+策略 → 保存到DB +流程：收集最新数据 → 调LLM(gateway)写12维分析+策略 → 保存到DB """ -import sys, json, subprocess, sqlite3, re, time +import sys, json, subprocess, sqlite3, re, time, os 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生成的九维分析（>500字）""" + """检查是否为LLM生成的12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() @@ -33,13 +44,41 @@ 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""" + """收集最新数据（含完整策略原文）""" data = {"code": code} - # 从DB读策略 + # 从DB读策略（含 full_analysis / changelog_json / position_advice） 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 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, full_analysis, changelog_json, reassessed_at, position_advice FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone() if r: data["name"] = r[0] data["entry_low"] = r[1] or 0 @@ -52,10 +91,21 @@ 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 - prefix = "sh" if str(code).startswith(("6","9")) else "sz" + # 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" 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("~") @@ -80,9 +130,10 @@ def collect_data(code): return data def build_prompt(data): - """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 + """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） # 拉取资金流数据 _flow_note = "暂无资金流数据" @@ -122,7 +173,53 @@ def build_prompt(data): except: pass - 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。 + # ── 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 ── ⚠️ 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。 @@ -136,11 +233,18 @@ 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： +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。 【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] @@ -162,13 +266,18 @@ 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】只有综合结论为"买入"时才输出此项。仓位计算公式： +【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： 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 或任何 XML/JSON/代码块 +3. 所有【】节标题一个都不能少""" 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": ""} @@ -217,10 +326,13 @@ def parse_response(text): return result def save_result(code, full_text, parsed): - """保存LLM结果到DB""" + """保存LLM结果到DB（先快照再UPDATE）""" 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] @@ -260,106 +372,111 @@ 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}" - 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]}") + 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]}") except Exception as _e: - print(f" ⚠️ XMPP推送失败: {_e}") + print(f" \u26a0\ufe0f XMPP推送失败: {_e}") conn.close() -def process_stock(code): +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 has_llm_analysis(code): - print(f" ⏭ 已有LLM九维分析，跳过") + if in_cooldown(code): + print(f" \u23ed 冷却期内，跳过") return False - if in_cooldown(code): - print(f" ⏭ 冷却期内，跳过") + # 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" ⚠️ 无价格数据，跳过") + 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) - 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 r.returncode != 0: - print(f" ❌ curl失败: {r.stderr.decode()[:100]}") - return False - - 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" ✅ 已保存到DB") - return True - - except subprocess.TimeoutExpired: - print(f" ❌ 超时") - return False - except Exception as e: - print(f" ❌ 错误: {e}") + # ── 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: - # 所有自选策略 + # 按类型筛选 active 策略 + type_map = {"holding": "持仓策略", "watchlist": "自选策略"} conn = sqlite3.connect(DB) - rows = conn.execute("SELECT code FROM holding_strategies WHERE status='active' AND decision_type='自选策略' ORDER BY code").fetchall() + 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") + 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): - print(f" [{i+1}/{len(codes)}] ⏭ {code} 已有LLM分析") + 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): + if process_stock(code, force_today): ok += 1 else: fail += 1 - # 间隔15秒（防gateway过载） + # 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15秒...", flush=True) - time.sleep(15) + 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") diff --git a/deploy/profile-scripts/candidate_filter.py b/deploy/profile-scripts/candidate_filter.py index e33ab5b3..4a48c068 100644 --- a/deploy/profile-scripts/candidate_filter.py +++ b/deploy/profile-scripts/candidate_filter.py @@ -17,7 +17,9 @@ DB_PATH = Path("/home/hmo/MoFin/data/mofin.db") UA = "Mozilla/5.0" def get_conn(): - return sqlite3.connect(str(DB_PATH)) + c = sqlite3.connect(str(DB_PATH), timeout=30) + c.execute("PRAGMA busy_timeout=30000") + return c def log_candidate(conn, code, stage, passed, detail): """记录过滤日志""" diff --git a/deploy/profile-scripts/data/market_scan_summary.json b/deploy/profile-scripts/data/market_scan_summary.json deleted file mode 100644 index f5373921..00000000 --- a/deploy/profile-scripts/data/market_scan_summary.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "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" -} \ No newline at end of file diff --git a/deploy/profile-scripts/fix_gateway_port.py b/deploy/profile-scripts/fix_gateway_port.py index 2d7b0996..283cc1b7 100644 --- a/deploy/profile-scripts/fix_gateway_port.py +++ b/deploy/profile-scripts/fix_gateway_port.py @@ -21,33 +21,26 @@ def port_open(port, host="127.0.0.1"): s.close() def check_session_health(): - """调gateway API，检测session是否卡死。超过15s无响应→不健康""" + """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）。 + """ try: - 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 - 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 + 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)") + 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) + 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} 不健康: {e}", file=sys.stderr) - return False + print(f"Session {SESSION_ID} 健康检查异常: {e}（按健康处理）", file=sys.stderr) + return True def restart_gateway(): """通过systemd重启gateway""" diff --git a/deploy/profile-scripts/per_stock_reassess.py b/deploy/profile-scripts/per_stock_reassess.py index c5c1d172..f02b5be4 100644 --- a/deploy/profile-scripts/per_stock_reassess.py +++ b/deploy/profile-scripts/per_stock_reassess.py @@ -34,8 +34,11 @@ 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): @@ -431,18 +434,76 @@ def main(): except: pass - _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）。 + # ── 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 ║ +╚══════════════════════════════════════════════╝ ⚠️ 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） +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） 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） -格式： +╔══════════════════════════════════════════════╗ +║ 📝 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） + 【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 @@ -452,26 +513,42 @@ 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】""" - try: - _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维分析失败: {_e}", file=__import__('sys').stderr) - _full_analysis_text = None +【建议止盈】 +【建议仓位】⚠️不可省略，非"买入"时写"不新建仓" - # 保存到DB +⚠️ 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 或任何 XML/JSON/代码块 +3. 所有【】节标题一个都不能少""" + _full_analysis_text = None + 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) + except Exception as _e: + print(f" ❌ LLM12维分析异常: {_e}", flush=True) + + # ── 保存到DB（覆写前先快照）── _fa_conn = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db") - _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() + 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.commit() _fa_conn.close() - 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") + 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" [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: @@ -490,10 +567,8 @@ 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 '-'}" - _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) + from alert_helper import notify as _notify2, ACTION as _ACT2 + _notify2("买入信号", _xm, _ACT2) print(f" 📨 XMPP推送买入信号") except: pass except: pass diff --git a/deploy/profile-scripts/stale_detector.py b/deploy/profile-scripts/stale_detector.py index 93412551..fc805b83 100644 --- a/deploy/profile-scripts/stale_detector.py +++ b/deploy/profile-scripts/stale_detector.py @@ -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 + # 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） 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']: @@ -150,12 +150,20 @@ def main(): reassess_path = p break if reassess_path: - for code in reassess_scripts: - r = subprocess.run(['python3', reassess_path, code], - 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}") + 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 + r = subprocess.run(['python3', reassess_path, code], + capture_output=True, text=True, timeout=480) + 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 -----