Implement Admin UI to disable AI components
This commit is contained in:
@@ -0,0 +1,62 @@
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"""
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Global AI feature flags stored in Firestore at config/ai_features.
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Defaults to all-on when the document does not exist yet. Uses a short
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in-memory TTL cache so flag reads don't add a Firestore round-trip to every
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call upload.
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"""
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import time
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from typing import Any
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from app.internal.logger import logger
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from app.internal import firestore as fstore
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_COLLECTION = "config"
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_DOC_ID = "ai_features"
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_TTL = 30.0 # seconds before re-reading from Firestore
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_DEFAULTS: dict[str, bool] = {
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"stt_enabled": True,
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"correlation_enabled": True,
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"summaries_enabled": True,
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"vocabulary_learning_enabled": True,
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}
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_cache: dict[str, Any] = {}
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_cache_ts: float = 0.0
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async def get_flags() -> dict[str, bool]:
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"""Return the current feature flags, using the TTL cache when fresh."""
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global _cache, _cache_ts
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now = time.monotonic()
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if _cache and (now - _cache_ts) < _TTL:
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return dict(_cache)
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try:
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doc = await fstore.doc_get(_COLLECTION, _DOC_ID)
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if doc:
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merged = {**_DEFAULTS, **{k: bool(v) for k, v in doc.items() if k in _DEFAULTS}}
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else:
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merged = dict(_DEFAULTS)
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except Exception as e:
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logger.warning(f"Feature flags: could not read from Firestore ({e}), using defaults")
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merged = dict(_DEFAULTS)
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_cache = merged
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_cache_ts = now
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return dict(_cache)
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async def set_flags(updates: dict[str, bool]) -> dict[str, bool]:
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"""Write flag updates to Firestore and invalidate the cache."""
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global _cache, _cache_ts
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clean = {k: bool(v) for k, v in updates.items() if k in _DEFAULTS}
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if not clean:
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raise ValueError(f"No recognised flag keys in update: {list(updates)}")
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await fstore.doc_set(_COLLECTION, _DOC_ID, clean)
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_cache_ts = 0.0 # force re-read on next get_flags()
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logger.info(f"Feature flags updated: {clean}")
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return await get_flags()
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@@ -16,13 +16,18 @@ from app.config import settings
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async def summarizer_loop() -> None:
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from app.internal.feature_flags import get_flags
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interval = settings.summary_interval_minutes * 60
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logger.info(f"Summarizer started — interval: {settings.summary_interval_minutes}m")
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while True:
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await asyncio.sleep(interval)
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try:
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await _run_summary_pass()
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await _resolve_stale_incidents()
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flags = await get_flags()
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if flags["summaries_enabled"]:
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await _run_summary_pass()
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await _resolve_stale_incidents()
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else:
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logger.info("Summaries disabled — skipping summary pass and stale incident sweep")
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except Exception as e:
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logger.error(f"Summarizer pass failed: {e}")
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@@ -243,6 +243,7 @@ def build_gpt_vocab_block(vocabulary: list[str]) -> str:
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# ─────────────────────────────────────────────────────────────────────────────
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async def vocabulary_induction_loop() -> None:
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from app.internal.feature_flags import get_flags
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interval = settings.vocabulary_induction_interval_hours * 3600
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logger.info(
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f"Vocabulary induction loop started — "
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@@ -252,7 +253,11 @@ async def vocabulary_induction_loop() -> None:
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while True:
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await asyncio.sleep(interval)
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try:
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await _run_induction_pass()
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flags = await get_flags()
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if flags["vocabulary_learning_enabled"]:
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await _run_induction_pass()
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else:
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logger.info("Vocabulary learning disabled — skipping induction pass")
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except Exception as e:
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logger.error(f"Vocabulary induction pass failed: {e}")
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@@ -10,7 +10,7 @@ from app.internal.vocabulary_learner import vocabulary_induction_loop
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from app.internal.recorrelation_sweep import recorrelation_loop
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from app.config import settings
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from app.internal.auth import require_firebase_token, require_service_or_firebase_token
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from app.routers import nodes, systems, calls, upload, tokens, incidents, alerts
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from app.routers import nodes, systems, calls, upload, tokens, incidents, alerts, admin
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from app.internal import firestore as fstore
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@@ -69,6 +69,7 @@ app.include_router(tokens.router, dependencies=[Depends(require_service_or_fi
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app.include_router(incidents.router, dependencies=[Depends(require_service_or_firebase_token)])
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app.include_router(alerts.router, dependencies=[Depends(require_service_or_firebase_token)])
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app.include_router(upload.router) # auth is per-node, handled inline
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app.include_router(admin.router) # auth is per-endpoint (read: firebase, write: admin)
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@app.get("/health")
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@@ -0,0 +1,17 @@
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from fastapi import APIRouter, Depends
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from app.internal.auth import require_admin_token, require_firebase_token
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from app.internal.feature_flags import get_flags, set_flags
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router = APIRouter(prefix="/admin", tags=["admin"])
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@router.get("/features")
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async def get_feature_flags(_=Depends(require_firebase_token)):
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"""Return the current AI feature flag state. Any authenticated user can read."""
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return await get_flags()
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@router.put("/features")
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async def update_feature_flags(body: dict, _=Depends(require_admin_token)):
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"""Update one or more AI feature flags. Admin only."""
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return await set_flags(body)
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@@ -157,64 +157,74 @@ async def _run_intelligence_pipeline(
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4. Check alert rules and dispatch notifications
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"""
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from app.internal import transcription, intelligence, incident_correlator, alerter
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from app.internal.feature_flags import get_flags
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flags = await get_flags()
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transcript: Optional[str] = None
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segments: list[dict] = []
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# Step 1: Transcription
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if gcs_uri:
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transcript, segments = await transcription.transcribe_call(
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call_id, gcs_uri, talkgroup_name, system_id=system_id
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)
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if flags["stt_enabled"]:
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transcript, segments = await transcription.transcribe_call(
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call_id, gcs_uri, talkgroup_name, system_id=system_id
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)
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else:
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logger.info(f"STT disabled — skipping transcription for call {call_id}")
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# Step 2: Scene detection + intelligence extraction
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scenes: list[dict] = []
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if transcript:
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scenes = await intelligence.extract_scenes(
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call_id, transcript, talkgroup_name,
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talkgroup_id=talkgroup_id, system_id=system_id, segments=segments,
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node_id=node_id,
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)
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if flags["correlation_enabled"]:
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if transcript:
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scenes = await intelligence.extract_scenes(
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call_id, transcript, talkgroup_name,
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talkgroup_id=talkgroup_id, system_id=system_id, segments=segments,
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node_id=node_id,
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)
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else:
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logger.info(f"Correlation disabled — skipping scene extraction and correlation for call {call_id}")
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# Step 3: Correlate each scene independently.
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# A single recording can produce multiple incidents on a busy channel.
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incident_ids: list[str] = []
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all_tags: list[str] = []
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for scene in scenes:
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all_tags.extend(scene["tags"])
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incident_id = await incident_correlator.correlate_call(
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call_id=call_id,
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node_id=node_id,
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system_id=system_id,
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talkgroup_id=talkgroup_id,
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talkgroup_name=talkgroup_name,
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tags=scene["tags"],
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incident_type=scene["incident_type"],
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location=scene["location"],
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location_coords=scene["location_coords"],
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)
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if incident_id and incident_id not in incident_ids:
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incident_ids.append(incident_id)
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if scene["resolved"] and incident_id:
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await fstore.doc_set("incidents", incident_id, {"status": "resolved"})
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logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
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if flags["correlation_enabled"]:
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for scene in scenes:
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all_tags.extend(scene["tags"])
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incident_id = await incident_correlator.correlate_call(
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call_id=call_id,
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node_id=node_id,
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system_id=system_id,
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talkgroup_id=talkgroup_id,
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talkgroup_name=talkgroup_name,
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tags=scene["tags"],
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incident_type=scene["incident_type"],
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location=scene["location"],
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location_coords=scene["location_coords"],
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)
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if incident_id and incident_id not in incident_ids:
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incident_ids.append(incident_id)
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if scene["resolved"] and incident_id:
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await fstore.doc_set("incidents", incident_id, {"status": "resolved"})
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logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
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# Correlator also runs for calls with no scenes (unclassified) to attempt
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# talkgroup-based linking even when no transcript could be produced.
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if not scenes:
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incident_id = await incident_correlator.correlate_call(
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call_id=call_id,
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node_id=node_id,
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system_id=system_id,
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talkgroup_id=talkgroup_id,
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talkgroup_name=talkgroup_name,
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tags=[],
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incident_type=None,
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location=None,
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location_coords=None,
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)
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if incident_id:
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incident_ids.append(incident_id)
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# Correlator also runs for calls with no scenes (unclassified) to attempt
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# talkgroup-based linking even when no transcript could be produced.
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if not scenes:
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incident_id = await incident_correlator.correlate_call(
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call_id=call_id,
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node_id=node_id,
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system_id=system_id,
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talkgroup_id=talkgroup_id,
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talkgroup_name=talkgroup_name,
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tags=[],
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incident_type=None,
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location=None,
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location_coords=None,
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)
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if incident_id:
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incident_ids.append(incident_id)
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if incident_ids:
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await fstore.doc_set("calls", call_id, {"incident_ids": incident_ids})
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@@ -0,0 +1,135 @@
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"use client";
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import { useAuth } from "@/components/AuthProvider";
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import { c2api } from "@/lib/c2api";
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import { useEffect, useState } from "react";
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import { useRouter } from "next/navigation";
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interface FeatureFlags {
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stt_enabled: boolean;
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correlation_enabled: boolean;
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summaries_enabled: boolean;
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vocabulary_learning_enabled: boolean;
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}
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const FLAG_META: { key: keyof FeatureFlags; label: string; description: string }[] = [
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{
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key: "stt_enabled",
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label: "Speech-to-Text (Whisper)",
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description: "Transcribe call audio via OpenAI Whisper. When off, calls are recorded and stored but no transcript is generated.",
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},
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{
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key: "correlation_enabled",
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label: "Incident Correlation",
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description: "Run scene extraction and incident correlation on each call. When off, calls are logged but not linked to incidents.",
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},
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{
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key: "summaries_enabled",
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label: "Incident Summaries",
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description: "Generate AI summaries for active incidents on each summarizer pass. Auto-resolve sweep is also paused when off.",
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},
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{
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key: "vocabulary_learning_enabled",
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label: "Vocabulary Learning",
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description: "Run the background vocabulary induction loop that proposes new STT terms from recent transcripts.",
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},
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];
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function Toggle({
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enabled,
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onChange,
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disabled,
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}: {
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enabled: boolean;
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onChange: (val: boolean) => void;
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disabled: boolean;
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}) {
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return (
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<button
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onClick={() => onChange(!enabled)}
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disabled={disabled}
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className={`relative inline-flex h-6 w-11 items-center rounded-full transition-colors focus:outline-none disabled:opacity-50 ${
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enabled ? "bg-indigo-600" : "bg-gray-700"
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}`}
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>
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<span
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className={`inline-block h-4 w-4 rounded-full bg-white shadow transition-transform ${
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enabled ? "translate-x-6" : "translate-x-1"
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}`}
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/>
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</button>
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);
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}
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export default function AdminPage() {
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const { isAdmin } = useAuth();
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const router = useRouter();
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const [flags, setFlags] = useState<FeatureFlags | null>(null);
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const [loading, setLoading] = useState(true);
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const [saving, setSaving] = useState<string | null>(null);
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const [error, setError] = useState<string | null>(null);
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useEffect(() => {
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if (!isAdmin) {
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router.replace("/dashboard");
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return;
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}
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c2api.getFeatureFlags()
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.then((f) => setFlags(f as FeatureFlags))
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.catch((e) => setError(String(e)))
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.finally(() => setLoading(false));
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}, [isAdmin, router]);
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async function handleToggle(key: keyof FeatureFlags, value: boolean) {
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if (!flags) return;
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setSaving(key);
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setError(null);
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try {
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const updated = await c2api.setFeatureFlags({ [key]: value });
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setFlags(updated as FeatureFlags);
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} catch (e) {
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setError(String(e));
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} finally {
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setSaving(null);
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}
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}
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if (!isAdmin) return null;
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return (
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<div className="p-6 max-w-2xl mx-auto space-y-8">
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<h1 className="text-white text-xl font-bold font-mono">Admin</h1>
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<section className="space-y-3">
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<h2 className="text-sm font-mono text-gray-400 uppercase tracking-wider">AI Features</h2>
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{error && (
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<div className="bg-red-950 border border-red-800 rounded-lg p-3">
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<p className="text-red-400 text-sm font-mono">{error}</p>
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</div>
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)}
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{loading ? (
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<p className="text-gray-500 text-sm font-mono">Loading…</p>
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) : (
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<div className="bg-gray-900 border border-gray-800 rounded-xl divide-y divide-gray-800">
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{FLAG_META.map(({ key, label, description }) => (
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<div key={key} className="flex items-center justify-between gap-4 px-5 py-4">
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<div className="min-w-0">
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<p className="text-white text-sm font-semibold">{label}</p>
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<p className="text-gray-500 text-xs mt-0.5 leading-snug">{description}</p>
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</div>
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<Toggle
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enabled={flags?.[key] ?? true}
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onChange={(val) => handleToggle(key, val)}
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disabled={saving === key}
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/>
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</div>
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))}
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</div>
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)}
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</section>
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</div>
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);
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}
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@@ -18,6 +18,7 @@ const links = [
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const adminLinks = [
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{ href: "/tokens", label: "Tokens" },
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{ href: "/admin", label: "Admin" },
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];
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export function Nav() {
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@@ -115,4 +115,10 @@ export const c2api = {
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request(`/systems/${systemId}/vocabulary/pending/approve`, { method: "POST", body: JSON.stringify({ term }) }),
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dismissPendingTerm: (systemId: string, term: string) =>
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request(`/systems/${systemId}/vocabulary/pending/dismiss`, { method: "POST", body: JSON.stringify({ term }) }),
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// Feature flags (admin)
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getFeatureFlags: () =>
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request<Record<string, boolean>>("/admin/features"),
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setFeatureFlags: (flags: Record<string, boolean>) =>
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request<Record<string, boolean>>("/admin/features", { method: "PUT", body: JSON.stringify(flags) }),
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};
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