xxm
5b9d46efc6
- 归档 evolution/ + meta_growth/meta_watchdog/ab_research_daily - docs/evolution-archive-readme.md: 归档说明(旧模块功能+替代方案) - server.py: 新增 /api/research/effectiveness + effectiveness/summary + recommendation_log + execution_log - static/effectiveness.html: 新评估页面(概览/详细评估/推荐记录/执行记录) - 策略进化改为人驱动闭环(评估→用户决策→调整)
95 lines
3.8 KiB
Python
95 lines
3.8 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""AB路线每日LLM主导研究 v2（老莫2026-08-18）
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在原规则化分析基础上，集成 LLM 生成深度研究结论（真正"LLM主导"）
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1. 读温区覆盖 + 进化中心 + B组候选
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2. LLM 分析薄弱环节 → 建议尝试
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3. 写 strategy_research_log 表
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"""
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import sys, os, json, sqlite3
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from datetime import datetime
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sys.path.insert(0, "/home/hmo/MoFin/deploy/profile-scripts")
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DB = "/home/hmo/MoFin/data/mofin.db"
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CENTER = "/home/hmo/MoFin/data/evolution_center.json"
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def ensure_table(conn):
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conn.execute("""CREATE TABLE IF NOT EXISTS strategy_research_log (
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id INTEGER PRIMARY KEY AUTOINCREMENT, log_date TEXT NOT NULL, market TEXT,
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weak_regime TEXT, finding TEXT, experiment TEXT, result TEXT,
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produced_strategy TEXT, produced_verified INTEGER DEFAULT 0, llm_model TEXT, created_at TEXT)""")
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conn.commit()
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def load_center():
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if not os.path.exists(CENTER): return {}
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try: return json.load(open(CENTER))
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except: return {}
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def build_prompt(coverage, center):
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"""构造 LLM 研究 prompt"""
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line = []
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line.append("你是MoFin策略研究员。分析当前策略覆盖，找出薄弱环节并给出研究建议。")
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line.append("温区覆盖（trades>=30，2y）：")
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for c in coverage:
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line.append(f"- {c['market']}/{c['regime']}: {c['count']}个策略")
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bg = center.get("b_group") or []
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if bg:
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line.append(f"B组候选: {len(bg)}条")
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for b in bg[:3]:
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line.append(f" - {str(b)[:80]}")
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line.append("\n请输出：")
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line.append("1. 最薄弱的温区/环节（策略匮乏或合格策略少）")
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line.append("2. 具体研究建议（做什么尝试）")
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line.append("3. 预期成果类型")
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line.append("格式：发现|建议|预期")
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return "\n".join(line)
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def analyze_llm(coverage, center):
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"""LLM 生成研究结论"""
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try:
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from llm_client import call_llm
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prompt = build_prompt(coverage, center)
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res = call_llm(prompt)
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return str(res)[:400] if res else None
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except Exception as e:
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return f"[LLM调用失败: {e}]"
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def main():
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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ensure_table(conn)
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today = datetime.now().strftime("%Y-%m-%d")
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if conn.execute("SELECT COUNT(*) FROM strategy_research_log WHERE log_date=?", (today,)).fetchone()[0]:
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print(f"[AB研究] {today} 已有记录"); conn.close(); return
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# 读取覆盖
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rows = conn.execute("""SELECT market, regime, COUNT(DISTINCT strategy) as cnt
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FROM strategy_regime_perf_by_period WHERE period_tag='2y' AND trades >= 30
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GROUP BY market, regime""").fetchall()
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coverage = [{"market": r[0], "regime": r[1], "count": r[2]} for r in rows]
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center = load_center()
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# 基础规则发现
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findings = []
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weak = []
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if coverage:
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c_sorted = sorted(coverage, key=lambda x: x["count"])
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weak = c_sorted[:2]
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findings.append("覆盖最少的温区: " + "; ".join(f"{c['market']}/{c['regime']}({c['count']})" for c in weak))
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# LLM 深度分析
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if coverage:
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llm_res = analyze_llm(coverage, center)
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if llm_res:
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findings.append("LLM分析: " + llm_res)
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finding_text = "; ".join(findings) or "无明显薄弱点"
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weak_rg = weak[0]["regime"] if weak else ""
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weak_mkt = weak[0]["market"] if weak else "a"
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conn.execute(
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"INSERT INTO strategy_research_log (log_date, market, weak_regime, finding, experiment, result, produced_strategy, created_at) "
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"VALUES (?,?,?,?,?,?,?,?)",
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(today, weak_mkt, weak_rg, finding_text, "LLM主导温区覆盖+B组分析", "记录待验证", "",
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datetime.now().isoformat()))
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conn.commit()
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print(f"[AB研究] {today} 记录完成 (LLM主导)")
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conn.close()
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if __name__ == "__main__":
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main() |