chore: sync local workspace state

src/graph_view.py

@@ -134,11 +134,19 @@ def _node_size(access_count: int) -> float:
 
 def generate_graph_html(store: EngramStore, output_path: str) -> str:
     """Generiert interaktive HTML-Graph-Visualisierung."""
-    engrams = store.get_all()
+    # store.get_all() defaults to 1000; paginate so the graph can include all nodes.
+    engrams = []
+    offset = 0
+    while True:
+        batch = store.get_all(limit=2000, offset=offset)
+        if not batch:
+            break
+        engrams.extend(batch)
+        offset += len(batch)
 
     nodes = []
     edges = []
-    node_ids = set()
+    node_ids = set(str(e.id) for e in engrams)
 
     for eg in engrams:
         eid = str(eg.id)
@@ -156,22 +164,19 @@ def generate_graph_html(store: EngramStore, output_path: str) -> str:
                 "size": size,
                 "confidence": conf,
                 "confirmed": eg.correctness.confirmed,
+                "verdict": getattr(eg.correctness, "verdict", "unknown"),
                 "source": eg.metadata.get("source", "?"),
                 "tags": tags,
             }
         })
-        node_ids.add(eid)
 
+    # Add edges after all nodes are known (otherwise early nodes miss links).
+    for eg in engrams:
+        eid = str(eg.id)
         for lid in eg.links:
             lid_s = str(lid)
             if lid_s in node_ids:
-                edges.append({
-                    "data": {
-                        "id": f"{eid}_{lid_s}",
-                        "source": eid,
-                        "target": lid_s,
-                    }
-                })
+                edges.append({"data": {"id": f"{eid}_{lid_s}", "source": eid, "target": lid_s}})
 
     elements = {"nodes": nodes, "edges": edges}
     html = _HTML_TEMPLATE.format(elements_json=json.dumps(elements, ensure_ascii=False))

src/openclaw_bridge.py

@@ -12,6 +12,7 @@ import os
 import sys
 import json
 import traceback
+import re
 from pathlib import Path
 from datetime import datetime, timezone
 from typing import Optional, List, Dict, Any
@@ -48,6 +49,45 @@ except Exception:
 # --- Konfiguration ---
 BRAIN_DB = Path(__file__).parent.parent / "data" / "brain.sqlite"
 
+_UUID_RE = re.compile(r"\b[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}\b", re.I)
+_SHORT_ID_RE = re.compile(r"\b[0-9a-f]{8}\b", re.I)
+
+
+def _detect_feedback(content: str) -> dict | None:
+    """
+    Heuristik: erkennt kurze Korrektur-/Feedback-Nachrichten in Chats.
+
+    Returns:
+      {"kind":"confirm"|"reject"|"stop", "target": <id or short-id or None>, "raw": <normalized>}
+    """
+    if not isinstance(content, str):
+        return None
+    raw = content.strip()
+    if not raw:
+        return None
+    norm = raw.lower().strip()
+
+    target = None
+    m = _UUID_RE.search(raw)
+    if m:
+        target = m.group(0)
+    else:
+        m2 = _SHORT_ID_RE.search(raw)
+        if m2:
+            target = m2.group(0)
+
+    if norm in {"stop", "stopp", "halt"}:
+        return {"kind": "stop", "target": target, "raw": norm}
+    if norm in {"nein", "no", "falsch", "wrong"}:
+        return {"kind": "reject", "target": target, "raw": norm}
+    if norm in {"ja", "yes", "richtig", "korrekt", "stimmt"}:
+        return {"kind": "confirm", "target": target, "raw": norm}
+    if norm.startswith(("korrigiert", "korrektur", "correction")):
+        if "richtig" in norm or "korrekt" in norm:
+            return {"kind": "confirm", "target": target, "raw": norm}
+        return {"kind": "reject", "target": target, "raw": norm}
+    return None
+
 
 def get_brain() -> EngramStore:
     """Gibt initialisierten Brain-Store."""
@@ -77,14 +117,43 @@ def save_session_learned(
         )
     """
     store = get_brain()
+    tags = tags or []
+
+    fb = _detect_feedback(content) if source == "session" else None
+    fb_target_id: str | None = None
+    if fb:
+        tags = list(dict.fromkeys(tags + ["feedback", fb["kind"]]))
+        confidence = min(confidence, 0.2)
+        grounding = Grounding.ASSUMPTION
+        if session_id:
+            recent = store.get_latest_by_session_id(session_id, limit=10, exclude_tags=["feedback"])
+            if recent:
+                fb_target_id = str(recent[0].id)
+
     eg = Engram.create(
         content=content,
         source=source,
-        tags=tags or [],
+        tags=tags,
         session_id=session_id,
         confidence=confidence,
         grounding=grounding,
     )
+    if fb and fb_target_id:
+        target = store.get(fb_target_id)
+        if target:
+            try:
+                # Link both ways for graphing/traceability
+                eg.links.append(target.id)
+                if eg.id not in target.links:
+                    target.links.append(eg.id)
+
+                # Lock target so auto-review does not keep "re-deciding" after a correction signal.
+                target.metadata["predict_locked"] = True
+                target.metadata["predict_locked_reason"] = f"feedback:{fb['raw']}"
+                target.metadata["predict_locked_at"] = datetime.now(timezone.utc).isoformat()
+                store.save(target)
+            except Exception:
+                pass
     store.save(eg)
     return eg
 

src/store.py

@@ -136,6 +136,32 @@ class EngramStore:
         ).fetchall()
         return [self._row_to_engram(r) for r in rows]
 
+    def get_latest_by_session_id(
+        self,
+        session_id: str,
+        *,
+        limit: int = 5,
+        exclude_tags: Optional[List[str]] = None,
+    ) -> List[Engram]:
+        """
+        Lädt die neuesten Engramme für eine OpenClaw-Session-ID.
+
+        Hinweis: session_id liegt im `metadata_json`; wir nutzen eine robuste
+        LIKE-Suche, damit auch Legacy-Records gefunden werden.
+        """
+        if not session_id:
+            return []
+        rows = self._conn.execute(
+            "SELECT * FROM engrams WHERE metadata_json LIKE ? ORDER BY created_at DESC LIMIT ?",
+            (f'%"session_id": "{session_id}"%', limit),
+        ).fetchall()
+        engrams = [self._row_to_engram(r) for r in rows]
+        if exclude_tags:
+            ex = set(t for t in exclude_tags if isinstance(t, str))
+            if ex:
+                engrams = [e for e in engrams if not (ex & set(e.metadata.get("tags", []) or []))]
+        return engrams
+
     def delete(self, engram_id: str) -> bool:
         """Löscht ein Engramm und alle Verknüpfungen."""
         rowid = self._conn.execute(