feat: Phase 2.6 edges migration to Qdrant (TKG-only architecture)

Phase 2.6.1: co_occurrence_edges migration
- build_co_occurrence_edges_from_qdrant()
- Qdrant embeddings → frame grouping → YOLO objects
- Result: 6679 edges (vs 6701 PostgreSQL)

Phase 2.6.2: face_face_edges migration
- build_face_face_edges_from_qdrant()
- Qdrant embeddings → frame grouping → face pairs
- mutual_gaze detection preserved
- Result: 6 edges (exact match)

Phase 2.6.3: speaker_face_edges migration
- build_speaker_face_edges_from_qdrant()
- Qdrant embeddings → trace_id frame ranges
- SPEAKS_AS edge creation

Architecture:
- All edges use Qdrant payload (no face_detections queries)
- PostgreSQL fallback for empty Qdrant
- Estimated 3.6x performance improvement

Testing:
- Playground (3003): ✓ All Phase 2.6 logs verified
- Edge counts: ✓ Close match with PostgreSQL
- Fallback: ✓ Working

Docs:
- docs_v1.0/DESIGN/TKG_PHASE2_6_EDGES_MIGRATION.md
- docs_v1.0/M4_workspace/2026-06-21_phase2_6_test.md

v1.1/scripts/update_embeddings_v1.11.py

@@ -0,0 +1,107 @@
+#!/opt/homebrew/bin/python3.11
+"""Update face_detections embeddings from face_traced.json"""
+
+import json
+import psycopg2
+import sys
+import os
+
+DATABASE_URL = os.getenv("DATABASE_URL", "postgres://accusys@localhost:5432/momentry")
+
+def update_embeddings(file_uuid: str, traced_json_path: str, schema: str = "dev"):
+    """Update embeddings in face_detections from face_traced.json"""
+    
+    with open(traced_json_path, 'r') as f:
+        data = json.load(f)
+    
+    conn = psycopg2.connect(DATABASE_URL)
+    cur = conn.cursor()
+    
+    frames = data.get('frames', {})
+    
+    updated = 0
+    no_match = 0
+    
+    # Process frames in batches of 1000
+    batch = []
+    
+    for frame_key, frame_data in frames.items():
+        frame_num = int(frame_key)
+        faces = frame_data.get('faces', [])
+        
+        for face in faces:
+            embedding = face.get('embedding')
+            if not embedding or len(embedding) == 0:
+                continue
+            
+            trace_id = face.get('trace_id')
+            x = face.get('x', 0)
+            y = face.get('y', 0)
+            w = face.get('width', 0)
+            h = face.get('height', 0)
+            
+            # Convert embedding to PostgreSQL array format
+            emb_str = '[' + ','.join(str(v) for v in embedding) + ']'
+            
+            batch.append((trace_id, emb_str, file_uuid, frame_num, x, y, w, h))
+        
+        # Execute batch every 1000 frames
+        if len(batch) >= 1000:
+            for item in batch:
+                try:
+                    cur.execute(
+                        f"""
+                        UPDATE {schema}.face_detections
+                        SET embedding = %s::real[], trace_id = %s
+                        WHERE file_uuid = %s AND frame_number = %s
+                          AND x = %s AND y = %s AND width = %s AND height = %s
+                          AND embedding IS NULL
+                        """,
+                        (item[1], item[0], item[2], item[3], item[4], item[5], item[6], item[7])
+                    )
+                    updated += cur.rowcount
+                except Exception as e:
+                    pass
+            conn.commit()
+            batch = []
+            print(f"[UPDATE] Processed {updated} so far...", file=sys.stderr)
+    
+    # Final batch
+    for item in batch:
+        try:
+            cur.execute(
+                f"""
+                UPDATE {schema}.face_detections
+                SET embedding = %s::real[], trace_id = %s
+                WHERE file_uuid = %s AND frame_number = %s
+                  AND x = %s AND y = %s AND width = %s AND height = %s
+                  AND embedding IS NULL
+                """,
+                (item[1], item[0], item[2], item[3], item[4], item[5], item[6], item[7])
+            )
+            updated += cur.rowcount
+        except Exception as e:
+            pass
+    
+    conn.commit()
+    cur.close()
+    conn.close()
+    
+    print(f"[UPDATE] Total updated: {updated}")
+    return updated
+
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--file-uuid", required=True)
+    parser.add_argument("--traced-json", help="Path to face_traced.json")
+    parser.add_argument("--schema", default="dev")
+    args = parser.parse_args()
+    
+    traced_json = args.traced_json or f"/Users/accusys/momentry/output_dev/{args.file_uuid}.face_traced.json"
+    
+    if not os.path.exists(traced_json):
+        print(f"File not found: {traced_json}", file=sys.stderr)
+        sys.exit(1)
+    
+    update_embeddings(args.file_uuid, traced_json, args.schema)