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知微
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#!/usr/bin/env python3
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"""session_to_cron_bridge.py — 将Hermes session DB中的cron报告写到cron/output目录
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Hermes cron jobs（如快速盯盘）将LLM输出存在 session DB (state.db) 中。
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cron_to_xmpp.py 扫描 ~/.hermes/cron/output/ 目录的 .md 文件推送到XMPP。
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这个脚本弥补这个缺口：从state.db读取最新的cron输出，生成.md文件。
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工作方式：
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1. 查询 state.db 中最近的 cron 会话（source='cron'）
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2. 提取 assistant 的最后一条非空消息
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3. 与 relay journal 对比去重
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4. 新消息写入 cron/output/<job_id>/ 目录
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5. cron_to_xmpp.py 自然捡起并推送
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"""
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import json
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import sqlite3
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import subprocess
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import re
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import sys
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from datetime import datetime
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from pathlib import Path
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REAL_HOME = Path("/home/hmo")
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PROFILE = "position-analyst"
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# 要中继的 cron job ID 列表（需要推送到 XMPP 的）
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RELAY_JOBS = {
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"62a2ba59f7ff": "快速盯盘-15分钟",
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"e27e2e92ed80": "知识萃取-盘后",
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"9d1236d8a07f": "策略评估-每日",
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"5dde4e1a42ce": "分析师-持仓复查",
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}
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# 输出目录（与 cron_to_xmpp.py 一致）
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# 注意：~/.hermes 是 symlink 到 /home/hmo/.hermes/profiles/position-analyst/home/.hermes
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# cron_to_xmpp.py 使用绝对路径 REAL_HOME / ".hermes" / "cron" / "output"
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# 所以这里必须用绝对路径，不要相信 ~/.hermes 的解析
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OUTPUT_DIRS = [
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REAL_HOME / ".hermes" / "cron" / "output",
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REAL_HOME / ".hermes" / "profiles" / PROFILE / "cron" / "output",
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]
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JOURNAL = REAL_HOME / ".hermes" / "cron" / ".relay_journal.json"
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STATE_DB = REAL_HOME / ".hermes" / "profiles" / PROFILE / "state.db"
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MAX_AGE_MINUTES = 70 # 只处理最近70分钟内的报告
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TRACK_FILE = REAL_HOME / ".hermes" / "cron" / ".bridge_track.json" # 追踪已桥接的session
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def load_track():
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try:
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return set(json.loads(TRACK_FILE.read_text()))
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except:
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return set()
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def save_track(entries):
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TRACK_FILE.write_text(json.dumps(sorted(entries)))
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def load_journal():
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try:
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return set(json.loads(JOURNAL.read_text()))
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except:
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return set()
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def save_journal(entries):
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JOURNAL.write_text(json.dumps(sorted(entries)))
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def ensure_output_dirs():
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for d in OUTPUT_DIRS:
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d.mkdir(parents=True, exist_ok=True)
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for job_id in RELAY_JOBS:
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(d / job_id).mkdir(exist_ok=True)
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def extract_report_content(content):
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"""从assistant消息中提取报告正文"""
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if not content or content.strip() in ("", " ", "\n", "\n\n"):
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return None
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text = content.strip()
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# 跳过太短的消息
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if len(text) < 20:
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return None
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# 跳过 [SILENT]
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if "[SILENT]" in text:
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return None
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# 跳过思考过程（只留下实际报告内容）
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# 如果消息以"Now let me"/"Let me"/"I need"等开头，尝试找后面的报告正文
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lines = text.split('\n')
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report_lines = []
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in_report = False
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for line in lines:
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if not in_report:
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# 报告特征：以【开头 或 包含📊 或 包含【知微】
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if any(x in line for x in ["【", "📊", "【知微", "【⚡", "## "]):
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in_report = True
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report_lines.append(line)
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else:
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report_lines.append(line)
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if report_lines:
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text = '\n'.join(report_lines)
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if len(text) < 20:
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return None
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return text
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def scan():
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processed = load_journal()
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tracked = load_track()
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new = set()
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n_written = 0
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if not STATE_DB.exists():
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print(f"state.db not found: {STATE_DB}", file=sys.stderr)
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return
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conn = sqlite3.connect(str(STATE_DB))
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conn.row_factory = sqlite3.Row
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cur = conn.cursor()
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now = datetime.now()
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for job_id, job_name in RELAY_JOBS.items():
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# Find recent sessions for this job
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cur.execute('''
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SELECT id, started_at, message_count, source
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FROM sessions
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WHERE id LIKE ?
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ORDER BY started_at DESC
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LIMIT 10
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''', (f'cron_{job_id}_%',))
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sessions = cur.fetchall()
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for s in sessions:
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session_id = s['id']
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# Skip already bridged sessions
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if session_id in tracked:
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continue
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started_at = datetime.fromtimestamp(s['started_at']) if s['started_at'] else now
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# Skip too old sessions
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age_minutes = (now - started_at).total_seconds() / 60
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if age_minutes > MAX_AGE_MINUTES:
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continue
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# Find the last assistant message
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cur.execute('''
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SELECT content, timestamp
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FROM messages
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WHERE session_id = ? AND role = 'assistant'
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AND content NOT IN ('', ' ', '\n', '\n\n', '\n\n\n')
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ORDER BY timestamp DESC
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LIMIT 1
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''', (session_id,))
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msg = cur.fetchone()
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if not msg:
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tracked.add(session_id)
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continue
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content = msg['content'].strip()
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report = extract_report_content(content)
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if not report:
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tracked.add(session_id)
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continue
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# Mark as tracked even before writing
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tracked.add(session_id)
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# Generate a unique key for this report
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ts = datetime.fromtimestamp(msg['timestamp']).strftime('%Y%m%d_%H%M%S') if msg['timestamp'] else started_at.strftime('%Y%m%d_%H%M%S')
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filename = f"{job_name}_{ts}.md"
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for out_dir in OUTPUT_DIRS:
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out_path = out_dir / job_id / filename
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key = str(out_path.resolve())
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if key in processed or key in new:
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continue
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# Write the report as an .md file (matching cron_to_xmpp.py format)
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md_content = f"# Cron Job: {job_name} ({session_id})\n\n## Response\n\n{report}\n"
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out_path.write_text(md_content, encoding='utf-8')
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new.add(key)
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n_written += 1
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print(f" Written: {out_path.relative_to(REAL_HOME)}", file=sys.stderr)
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conn.close()
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if tracked:
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save_track(tracked)
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print(f"桥接完成：写入{n_written}份新报告", file=sys.stderr)
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# 桥接脚本只负责写入 .md 文件，不做去重追踪
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# 这样可以避免重复推送的复杂问题
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# 可能每次运行会写重复的文件，但cron_to_xmpp.py会用journal去重
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print(f"桥接完成：写入{n_written}份新报告", file=sys.stderr)
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if __name__ == "__main__":
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scan()
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