Tighten Auto-Match refs and log accept/reject (Phase 2).

Raise reference quality floor to 0.5, align browse/run/auto-accept defaults with UI copy, and persist match_decisions for later confidence calibration.

backend/api/faces.py

@@ -49,6 +49,7 @@ from backend.services.face_service import (
     find_similar_faces,
     get_auto_match_people_list,
     list_unidentified_faces,
+    record_match_decisions,
 )
 from backend.services.face_service import (
     get_auto_match_person_matches as get_person_matches_service,
@@ -612,7 +613,7 @@ def auto_match_faces(
     """Start auto-match process with tolerance threshold and optional auto-acceptance.
     
     Matches desktop auto-match workflow exactly:
-    1. Gets all identified people (one face per person, best quality >= 0.3)
+    1. Gets all identified people (one face per person, best quality >= MIN_AUTO_MATCH_REFERENCE_QUALITY)
     2. For each person, finds similar unidentified faces (confidence >= 40%)
     3. Returns matches grouped by person, sorted by person name
     
@@ -620,7 +621,7 @@ def auto_match_faces(
     - Only processes persons with frontal or tilted reference faces (not profile)
     - Only processes persons with reference face quality > 50% (quality_score > 0.5)
     - Only matches with frontal or tilted unidentified faces (not profile)
-    - Only auto-accepts matches with similarity >= threshold
+    - Only auto-accepts matches with similarity >= threshold (default 85%)
     - Only auto-accepts faces with quality > 50% (quality_score > 0.5)
     """
     from backend.db.models import Person, Photo
@@ -649,6 +650,7 @@ def auto_match_faces(
             # 3. Quality must be > 50% (quality_score > 0.5)
             
             qualifying_faces = []
+            accept_log_items = []
             for face, distance, confidence_pct in similar_faces:
                 # Check similarity threshold
                 if confidence_pct < request.auto_accept_threshold:
@@ -662,6 +664,14 @@ def auto_match_faces(
                     continue
                 
                 qualifying_faces.append(face.id)
+                accept_log_items.append(
+                    {
+                        "face_id": face.id,
+                        "similarity": float(confidence_pct),
+                        "distance": float(distance),
+                        "reference_face_id": reference_face_id,
+                    }
+                )
             
             # Auto-accept qualifying faces
             if qualifying_faces:
@@ -670,6 +680,16 @@ def auto_match_faces(
                         db, person_id, qualifying_faces
                     )
                     auto_accepted_faces += identified_count
+                    if identified_count:
+                        record_match_decisions(
+                            db,
+                            decision="accept",
+                            source="auto_accept",
+                            person_id=person_id,
+                            items=accept_log_items,
+                            user_id=None,
+                            commit=True,
+                        )
                 except Exception as e:
                     import logging
                     logger = logging.getLogger(__name__)

backend/api/people.py

@@ -21,7 +21,7 @@ from backend.schemas.people import (
     PersonUpdateRequest,
     PersonWithFacesResponse,
 )
-from backend.services.face_service import accept_auto_match_matches
+from backend.services.face_service import accept_auto_match_matches, record_match_decisions
 
 router = APIRouter(prefix="/people", tags=["people"])
 
@@ -278,9 +278,63 @@ def accept_matches(
     
     user_id = current_user["user_id"]
     try:
-        identified_count, updated_count = accept_auto_match_matches(
-            db, person_id, request.face_ids, user_id=user_id
-        )
+        person = db.query(Person).filter(Person.id == person_id).first()
+        if not person:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Person {person_id} not found",
+            )
+
+        if request.face_ids:
+            accept_auto_match_matches(
+                db, person_id, request.face_ids, user_id=user_id
+            )
+
+        # Log accepts (with optional scores from client)
+        score_by_face = {
+            item.face_id: item for item in (request.accepted_matches or [])
+        }
+        accept_items = []
+        for face_id in request.face_ids:
+            scored = score_by_face.get(face_id)
+            accept_items.append(
+                {
+                    "face_id": face_id,
+                    "similarity": scored.similarity if scored else None,
+                    "distance": scored.distance if scored else None,
+                    "reference_face_id": scored.reference_face_id if scored else None,
+                }
+            )
+        if accept_items:
+            record_match_decisions(
+                db,
+                decision="accept",
+                source="auto_match",
+                person_id=person_id,
+                items=accept_items,
+                user_id=user_id,
+                commit=True,
+            )
+
+        if request.rejected_matches:
+            reject_items = [
+                {
+                    "face_id": item.face_id,
+                    "similarity": item.similarity,
+                    "distance": item.distance,
+                    "reference_face_id": item.reference_face_id,
+                }
+                for item in request.rejected_matches
+            ]
+            record_match_decisions(
+                db,
+                decision="reject",
+                source="auto_match",
+                person_id=person_id,
+                items=reject_items,
+                user_id=user_id,
+                commit=True,
+            )
     except ValueError as e:
         if "not found" in str(e).lower():
             raise HTTPException(