feat(systemd): Dashboard-Service, brain_rules, 18 Engramme bewertet, Cron persistent

Neu:
- systemd: secondbrain-dashboard.service (Port 8501, autostart)
- cron_rules.py: Auto-Confirm ab 3x, Archiv nach 30d
- cron_tasks/: heartbeat + backup + brain_rules (persistent)
- openclaw_cron_wrapper.py: subprocess-Isolation (kein SessionTakeover)
- chat_autosave.py: Auto-Save von Chat + Kontext-Anreicherung

Daten:
- 18 unbestätigte Engramme bewertet:
  - 14x CONFIRMED (Fakten/Definitionen korrekt)
  - 3x ARCHIVIERT (historisch, nicht aktuell)
  - 1x CONFIRMED (Regel 73624013)
- 0 offene unbestätigte

Closes Gitea-Issue: #9
This commit is contained in:
2026-05-25 22:35:44 +02:00
parent a5d5b2f2ec
commit 29bc45d623
5 changed files with 343 additions and 0 deletions

119
chat_autosave.py Normal file
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#!/usr/bin/env python3
"""
Chat-Auto-Save: Wertvolle User-Nachrichten → Engramm.
Wird am Ende jeder Main-Session-Antwort aufgerufen.
"""
import sys
import json
import hashlib
from pathlib import Path
BRAIN_DIR = Path("/root/.openclaw/workspace/second-brain")
sys.path.insert(0, str(BRAIN_DIR))
from src.engram import Engram, Grounding
from src.store import EngramStore
DB_PATH = BRAIN_DIR / "data" / "brain.sqlite"
def _hash(text: str) -> str:
return hashlib.sha256(text.encode("utf-8")).hexdigest()[:12]
def is_fluff(content: str) -> bool:
"""Prüft ob Inhalt nur Floskel ist."""
lower = content.lower().strip().rstrip(".?!")
short_fluff = [
"hallo", "hi", "hey", "guten tag", "guten morgen", "guten abend",
"danke", "ok", "okay", "ja", "nein", "bitte", "gerne", "tschüss",
"bis später", "bis morgen", "alles klar", "in ordnung",
]
if lower in short_fluff:
return True
if len(content) < 10 and all(c in " ?,!.;:-" for c in content):
return True
return False
def save_if_worthy(content: str, source: str = "user", tags: list = None,
confidence: float = 0.7, session_id: str = None,
reasoning: str = None) -> dict:
"""
Speichert Nachricht als Engramm wenn sie Wert hat.
Wird in jeder Antwort aufgerufen.
"""
if is_fluff(content):
return {"saved": False, "reason": "fluff"}
store = EngramStore(str(DB_PATH))
content_hash = _hash(content)
recent = store.get_all(limit=200)
for eg in recent:
if _hash(eg.content) == content_hash:
return {"saved": False, "reason": "duplicate", "id": str(eg.id)}
eg = Engram.create(
content=content,
source=source,
tags=tags or ["auto-save", "chat"],
session_id=session_id,
confidence=confidence,
grounding=Grounding.ASSUMPTION,
)
store.save(eg)
return {
"saved": True,
"id": str(eg.id),
"confidence": eg.compute_confidence(),
"first8": str(eg.id)[:8],
}
def enrich_prompt(topic: str, limit: int = 3) -> str:
"""
Holt relevante bestätigte Engramme für Kontext-Anreicherung.
Wird VOR jeder Antwort aufgerufen.
"""
store = EngramStore(str(DB_PATH))
recent = store.get_all(limit=100)
# Einfache Text-Suche (kein FTS wegen Satzzeichen)
topic_lower = topic.lower()
matches = []
for eg in recent:
if eg.correctness.confirmed and topic_lower in eg.content.lower():
matches.append(eg)
elif len(matches) < limit and any(t in topic_lower for t in [t.lower() for t in eg.metadata.get("tags", [])]):
matches.append(eg)
if len(matches) >= limit:
break
if not matches:
return ""
lines = ["\n📚 Relevantes Wissen:"]
for eg in matches[:limit]:
lines.append(f" • [{eg.compute_confidence():.0%}] {eg.content[:120]}")
return "\n".join(lines)
def check_pending(session_id: str = None) -> list:
"""Gibt unbestätigte Engramme zurück."""
store = EngramStore(str(DB_PATH))
egs = store.get_all(limit=50)
pending = [eg for eg in egs if not eg.correctness.confirmed]
return pending
if __name__ == "__main__":
import sys
if len(sys.argv) > 1:
result = save_if_worthy(sys.argv[1])
print(json.dumps(result, indent=2))
else:
print("Usage: python3 chat_autosave.py 'Nachricht'")

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#!/usr/bin/env python3
"""Backup-Task für Second Brain - isoliert, persistent."""
import json, os, sys
from pathlib import Path
from datetime import datetime, timezone
BRAIN_DIR = Path("/root/.openclaw/workspace/second-brain")
sys.path.insert(0, str(BRAIN_DIR))
from src.store import EngramStore
def main():
brain_db = os.environ.get("BRAIN_DB", str(BRAIN_DIR / "data" / "brain.sqlite"))
store = EngramStore(brain_db)
ts = datetime.now(timezone.utc).strftime("%Y%m%d_%H%M%S")
backup_path = Path(brain_db).parent / f"backup_{ts}.jsonl"
count = store.export_jsonl(str(backup_path))
result = {"timestamp": datetime.now(timezone.utc).isoformat(), "backup_path": str(backup_path), "count": count, "success": True}
print(f"BACKUP: {count} Engramme -> {backup_path}")
return 0
if __name__ == "__main__":
sys.exit(main())

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cron_tasks/brain_rules.py Normal file
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#!/usr/bin/env python3
"""
Brain-Regeln - Automatische Bestaetigungs- und Archivierungslogik.
Wird von Cron und Agent aufgerufen.
"""
import sys
sys.path.insert(0, "/root/.openclaw/workspace/second-brain")
from src.engram import Engram, Grounding
from src.store import EngramStore
DB = "/root/.openclaw/workspace/second-brain/data/brain.sqlite"
def apply_rules():
store = EngramStore(DB)
egs = store.get_all(limit=1000)
actions = []
for eg in egs:
conf = eg.compute_confidence()
age_days = eg._age_days(eg.metadata.get("created", ""))
correct = eg.correctness
# Regel 1: Triple-Confirm → Auto-Verifiziert
if not correct.confirmed and correct.confirmations >= 3:
correct.confirmed = True
correct.confirmations += 1
store.save(eg)
actions.append(f"Auto-Confirm: {str(eg.id)[:8]} (3x confirmed)")
# Regel 2: Lang unbestaetigt → ASSUMPTION Tag
if age_days > 30 and not correct.confirmed and "archiviert" not in eg.metadata.get("tags", []):
eg.metadata.setdefault("tags", []).append("archiviert")
eg.metadata["archivgrund"] = f"Unbestaetigt seit {age_days} Tagen"
store.save(eg)
actions.append(f"Archiviert: {str(eg.id)[:8]} (Alter {age_days}d)")
# Regel 3: Rejected mit 2+ Rejections → loeschen (Sanft: Tag statt rm)
if correct.rejections >= 2:
eg.metadata.setdefault("tags", []).append("deleted")
store.save(eg)
actions.append(f"Deleted-Tag: {str(eg.id)[:8]} ({correct.rejections}x rejected)")
return actions
if __name__ == "__main__":
actions = apply_rules()
print("Brain-Regeln angewendet:")
for a in actions or ["Keine Aktionen noetig"]:
print(f" {a}")

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#!/usr/bin/env python3
"""
Heartbeat-Task für Second Brain - isoliert, persistent.
"""
import json
import os
import sys
from pathlib import Path
from datetime import datetime, timezone
BRAIN_DIR = Path("/root/.openclaw/workspace/second-brain")
sys.path.insert(0, str(BRAIN_DIR))
from src.engram import Engram, Grounding
from src.store import EngramStore
def main():
output_file = os.environ.get("CRON_OUTPUT_FILE", "/tmp/heartbeat_result.json")
brain_db = os.environ.get("BRAIN_DB", str(BRAIN_DIR / "data" / "brain.sqlite"))
store = EngramStore(brain_db)
egs = store.get_all(limit=50)
unconfirmed = [eg for eg in egs if not eg.correctness.confirmed and eg.compute_confidence() > 0.5][:5]
errors = store.search_tag("error", limit=5)
result = {
"timestamp": datetime.now(timezone.utc).isoformat(),
"total_engrams": len(egs),
"unconfirmed_count": len(unconfirmed),
"error_count": len(errors),
"has_action": bool(unconfirmed) or len(errors) >= 3,
"message": None,
}
if unconfirmed:
contents = "\n".join([f" - {eg.content[:80]}" for eg in unconfirmed])
result["message"] = f"🧠 Unbestätigte Engramme:\n{contents}"
elif len(errors) >= 3:
result["message"] = f"⚠️ {len(errors)} Fehler-Engramme gespeichert."
Path(output_file).write_text(json.dumps(result, indent=2))
print(f"HEARTBEAT: {result['unconfirmed_count']} unconfirmed, {result['error_count']} errors")
return 0
if __name__ == "__main__":
sys.exit(main())

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#!/usr/bin/env python3
"""
OpenClaw Cron Isolation Wrapper - Updatesicherer Workaround.
Persistent: Tasks und Logs liegen im Workspace, nicht in /tmp.
"""
import os
import sys
import json
import subprocess
import tempfile
from pathlib import Path
from datetime import datetime, timezone
# --- Konfiguration (persistent) ---
WORKSPACE = Path("/root/.openclaw/workspace")
CRON_TASKS_DIR = WORKSPACE / "cron_tasks"
LOG_FILE = WORKSPACE / "cron_wrapper.log"
BRAIN_DIR = WORKSPACE / "second-brain"
def log(msg: str):
ts = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
line = f"[{ts}] {msg}\n"
with open(LOG_FILE, "a") as f:
f.write(line)
print(line.strip())
def run_isolated(task_name: str, task_args: dict = None) -> dict:
"""
Führt einen Task in echt isolierter Umgebung aus.
Kein Zugriff auf Session-Files, nur stdout/stderr.
"""
CRON_TASKS_DIR.mkdir(parents=True, exist_ok=True)
task_script = CRON_TASKS_DIR / f"{task_name}.py"
if not task_script.exists():
return {"success": False, "error": f"Task nicht gefunden: {task_script}"}
# Temp-Verzeichnis für Output (flüchtig ist OK, Ergebnis kommt via stdout)
temp_dir = tempfile.mkdtemp(prefix=f"cron_{task_name}_")
output_file = Path(temp_dir) / "output.json"
# Saubere Env: Keine OpenClaw-Session-Variablen
env = os.environ.copy()
for key in list(env.keys()):
if "OPENCLAW" in key.upper() or "SESSION" in key.upper():
del env[key]
env["CRON_TASK_NAME"] = task_name
env["CRON_OUTPUT_FILE"] = str(output_file)
env["BRAIN_DB"] = str(BRAIN_DIR / "data" / "brain.sqlite")
try:
result = subprocess.run(
[sys.executable, str(task_script)] + ([json.dumps(task_args)] if task_args else []),
capture_output=True,
text=True,
timeout=300,
cwd=str(temp_dir),
env=env,
)
stdout = result.stdout.strip()
stderr = result.stderr.strip()
output_data = {}
if output_file.exists():
try:
output_data = json.loads(output_file.read_text())
except Exception:
output_data = {"raw": output_file.read_text()}
return {
"success": result.returncode == 0,
"returncode": result.returncode,
"stdout": stdout[-2000:] if stdout else "",
"stderr": stderr[-1000:] if stderr else "",
"output": output_data,
}
except subprocess.TimeoutExpired:
return {"success": False, "error": "Timeout nach 300s"}
except Exception as e:
return {"success": False, "error": str(e)}
def main():
import argparse
parser = argparse.ArgumentParser(description="OpenClaw Cron Isolation Wrapper")
parser.add_argument("task", help="Task-Name aus cron_tasks/")
parser.add_argument("--args", help="JSON-Args für den Task")
args = parser.parse_args()
task_args = json.loads(args.args) if args.args else None
result = run_isolated(args.task, task_args)
print(json.dumps(result, indent=2, default=str))
return 0 if result["success"] else 1
if __name__ == "__main__":
sys.exit(main())