Second-brain 2.0: hybrid retrieval, obsidian bridge, vector watermark, tests

src/openclaw_bridge.py

@@ -38,6 +38,12 @@ try:
 except ImportError:
     Retriever = None
 
+# Chroma: optional (braucht chromadb)
+try:
+    from src.chroma_store import ChromaStore
+except Exception:
+    ChromaStore = None
+
 
 # --- Konfiguration ---
 BRAIN_DB = Path(__file__).parent.parent / "data" / "brain.sqlite"
@@ -207,10 +213,34 @@ def enrich_context(topic: str, limit: int = 3) -> str:
     """
     store = get_brain()
 
-    # Versuche Retriever (mit Embeddings), fallback auf einfache Textsuche
+    # Versuche Hybrid-Retrieval (FTS + optional Vector), fallback auf Textsuche
     if Retriever:
-        ret = Retriever(store)
-        results = ret.retrieve(topic, limit=limit, min_confidence=0.3)
+        chroma = None
+        if ChromaStore:
+            try:
+                chroma = ChromaStore(path=str(Path(__file__).parent.parent / "data" / "chroma"))
+            except Exception:
+                chroma = None
+        ret = Retriever(store, chroma=chroma)
+        try:
+            results = ret.hybrid_retrieve(topic, limit=limit * 3, min_confidence=0.3)
+        except Exception:
+            results = ret.retrieve(topic, limit=limit * 3, min_confidence=0.3)
+
+        # confirmed-first ranking
+        def _rank(r):
+            eg = r["engram"]
+            confirmed = 1 if getattr(eg.correctness, "confirmed", False) else 0
+            return (confirmed, float(r.get("score", 0.0)))
+
+        results.sort(key=_rank, reverse=True)
+
+        # If we have confirmed results, show only confirmed up to limit
+        confirmed_only = [r for r in results if r["engram"].correctness.confirmed]
+        if confirmed_only:
+            results = confirmed_only[:limit]
+        else:
+            results = results[:limit]
     else:
         results_raw = store.search_text(topic, limit=limit)
         results = [{"engram": eg, "score": 0.5} for eg in results_raw]