Implement Admin UI to disable AI components

drb-c2-core/app/routers/admin.py

@@ -0,0 +1,17 @@
+from fastapi import APIRouter, Depends
+from app.internal.auth import require_admin_token, require_firebase_token
+from app.internal.feature_flags import get_flags, set_flags
+
+router = APIRouter(prefix="/admin", tags=["admin"])
+
+
+@router.get("/features")
+async def get_feature_flags(_=Depends(require_firebase_token)):
+    """Return the current AI feature flag state.  Any authenticated user can read."""
+    return await get_flags()
+
+
+@router.put("/features")
+async def update_feature_flags(body: dict, _=Depends(require_admin_token)):
+    """Update one or more AI feature flags.  Admin only."""
+    return await set_flags(body)

drb-c2-core/app/routers/upload.py

@@ -157,64 +157,74 @@ async def _run_intelligence_pipeline(
       4. Check alert rules and dispatch notifications
     """
     from app.internal import transcription, intelligence, incident_correlator, alerter
+    from app.internal.feature_flags import get_flags
+
+    flags = await get_flags()
 
     transcript: Optional[str] = None
     segments: list[dict] = []
 
     # Step 1: Transcription
     if gcs_uri:
-        transcript, segments = await transcription.transcribe_call(
-            call_id, gcs_uri, talkgroup_name, system_id=system_id
-        )
+        if flags["stt_enabled"]:
+            transcript, segments = await transcription.transcribe_call(
+                call_id, gcs_uri, talkgroup_name, system_id=system_id
+            )
+        else:
+            logger.info(f"STT disabled — skipping transcription for call {call_id}")
 
     # Step 2: Scene detection + intelligence extraction
     scenes: list[dict] = []
-    if transcript:
-        scenes = await intelligence.extract_scenes(
-            call_id, transcript, talkgroup_name,
-            talkgroup_id=talkgroup_id, system_id=system_id, segments=segments,
-            node_id=node_id,
-        )
+    if flags["correlation_enabled"]:
+        if transcript:
+            scenes = await intelligence.extract_scenes(
+                call_id, transcript, talkgroup_name,
+                talkgroup_id=talkgroup_id, system_id=system_id, segments=segments,
+                node_id=node_id,
+            )
+    else:
+        logger.info(f"Correlation disabled — skipping scene extraction and correlation for call {call_id}")
 
     # Step 3: Correlate each scene independently.
     # A single recording can produce multiple incidents on a busy channel.
     incident_ids: list[str] = []
     all_tags: list[str] = []
-    for scene in scenes:
-        all_tags.extend(scene["tags"])
-        incident_id = await incident_correlator.correlate_call(
-            call_id=call_id,
-            node_id=node_id,
-            system_id=system_id,
-            talkgroup_id=talkgroup_id,
-            talkgroup_name=talkgroup_name,
-            tags=scene["tags"],
-            incident_type=scene["incident_type"],
-            location=scene["location"],
-            location_coords=scene["location_coords"],
-        )
-        if incident_id and incident_id not in incident_ids:
-            incident_ids.append(incident_id)
-        if scene["resolved"] and incident_id:
-            await fstore.doc_set("incidents", incident_id, {"status": "resolved"})
-            logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
+    if flags["correlation_enabled"]:
+        for scene in scenes:
+            all_tags.extend(scene["tags"])
+            incident_id = await incident_correlator.correlate_call(
+                call_id=call_id,
+                node_id=node_id,
+                system_id=system_id,
+                talkgroup_id=talkgroup_id,
+                talkgroup_name=talkgroup_name,
+                tags=scene["tags"],
+                incident_type=scene["incident_type"],
+                location=scene["location"],
+                location_coords=scene["location_coords"],
+            )
+            if incident_id and incident_id not in incident_ids:
+                incident_ids.append(incident_id)
+            if scene["resolved"] and incident_id:
+                await fstore.doc_set("incidents", incident_id, {"status": "resolved"})
+                logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
 
-    # Correlator also runs for calls with no scenes (unclassified) to attempt
-    # talkgroup-based linking even when no transcript could be produced.
-    if not scenes:
-        incident_id = await incident_correlator.correlate_call(
-            call_id=call_id,
-            node_id=node_id,
-            system_id=system_id,
-            talkgroup_id=talkgroup_id,
-            talkgroup_name=talkgroup_name,
-            tags=[],
-            incident_type=None,
-            location=None,
-            location_coords=None,
-        )
-        if incident_id:
-            incident_ids.append(incident_id)
+        # Correlator also runs for calls with no scenes (unclassified) to attempt
+        # talkgroup-based linking even when no transcript could be produced.
+        if not scenes:
+            incident_id = await incident_correlator.correlate_call(
+                call_id=call_id,
+                node_id=node_id,
+                system_id=system_id,
+                talkgroup_id=talkgroup_id,
+                talkgroup_name=talkgroup_name,
+                tags=[],
+                incident_type=None,
+                location=None,
+                location_coords=None,
+            )
+            if incident_id:
+                incident_ids.append(incident_id)
 
     if incident_ids:
         await fstore.doc_set("calls", call_id, {"incident_ids": incident_ids})