Make "AI is off" true, and stop the transcript PATCH from destroying calls

config/ai_features was not the switch it was documented to be. Three paths
spent money with it off, and one path read it wrong, so per-system opt-outs
did not opt anything out.

- Correlation in the ingest pipeline tested the raw global flag instead of the
  per-system resolution. With a system opted out, extraction was skipped but
  the no-scenes fallback still correlated the call with empty tags, taking the
  thin/recency path and attaching it to whatever incident was most recent on
  that system. The opt-out did not disable correlation, it disabled good
  correlation and left the worst kind running. (#75)

- Transcript correction ran on every transcribed call gated only by an env var,
  spending Gemini tokens and a Places lookup per proposed location. An
  "STT-only" window was never STT-only and its cost could not be attributed.
  Now behind transcript_correction_enabled. (#76)

- _run_extraction_pipeline and the vocabulary learner, both reachable from
  PATCH /calls/{id}/transcript, checked no flags at all. (#76, #81)

The flag resolver now lives in feature_flags.resolve_flags() rather than as a
local helper in upload.py. Three copies of that logic is how #75 happened.

PATCH /calls/{id}/transcript now refuses with 409 when correlation is off.
That route wipes tags, severity, location, units, embedding and unlinks the
call from every incident before queueing re-extraction. Gating extraction
alone would have made it destructive-only in the standing flags-off
configuration: the call left blank and orphaned forever, with the route still
answering 200. The wipe and the rebuild are one transaction in intent, so it
refuses before the first write.

Also: the summarizer's stale-incident sweep is no longer behind
summaries_enabled. It is pure Firestore with no model call in it, and gating
it meant nothing auto-resolved while AI was off - so every incident stayed
active forever and the candidate set every correlation reads kept growing.

transcript_correction_enabled is documented as NOT a pure cost lever. The
corrector is also the noise gate that sets not_speech; with it off, recogniser
noise reaches extraction as a real transcript, comes back thin, and
auto-attaches. Never open an evaluation window with correction off and
correlation on.

14 tests added covering flag precedence, both pipeline paths, the 409, the
correction gate and the summarizer no-op. Suite: 264 passed.

Refs #75, #76, #81, #45.

drb-c2-core/app/internal/feature_flags.py

@@ -19,6 +19,21 @@ _DEFAULTS: dict[str, bool] = {
     "correlation_enabled":          True,
     "summaries_enabled":            True,
     "vocabulary_learning_enabled":  True,
+    # Transcript correction runs inside transcribe_call and spends Gemini
+    # tokens plus Places quota on every transcribed call.  Until server-26#76
+    # it was reachable only through an env var and an ansible run, which meant
+    # an "STT-only" evaluation window was never STT-only and its cost could
+    # not be attributed (server-26#45).
+    #
+    # NOT a pure cost lever.  The corrector is also the noise gate: it is what
+    # sets not_speech, and transcription.py returns nothing for a call it
+    # flags.  _is_degenerate does not catch what the corrector catches, so with
+    # this off, recogniser noise reaches extraction as a real transcript, comes
+    # back with no units/tags/location, is judged thin, and auto-attaches to the
+    # most recent incident on the talkgroup with no fit check.  Turning this off
+    # while correlation_enabled is on therefore pushes over-merging -- do not do
+    # it during an evaluation window.
+    "transcript_correction_enabled": True,
 }
 
 _cache: dict[str, Any] = {}
@@ -60,3 +75,33 @@ async def set_flags(updates: dict[str, bool]) -> dict[str, bool]:
     _cache_ts = 0.0  # force re-read on next get_flags()
     logger.info(f"Feature flags updated: {clean}")
     return await get_flags()
+
+
+async def resolve_flags(system_id: str | None):
+    """
+    Resolve the AI feature flags for one radio system.
+
+    Returns ``(flags, flag)``: ``flags`` is the raw global config/ai_features
+    document, and ``flag(name)`` layers the system's own ``ai_flags`` on top of
+    it.  A system flag of False beats a global True, but a global False beats
+    everything -- config/ai_features is the master switch, which is the whole
+    point of having one (server-26#75, server-26#76).
+
+    Every AI spend path resolves through here.  A path that reads ``flags``
+    directly re-introduces #75; a path that reads neither re-introduces #76.
+    """
+    from app.internal import firestore as _fstore
+
+    flags = await get_flags()
+
+    system_ai_flags: dict = {}
+    if system_id:
+        sys_doc = await _fstore.doc_get_cached("systems", system_id)
+        system_ai_flags = (sys_doc or {}).get("ai_flags") or {}
+
+    def flag(name: str) -> bool:
+        if not flags[name]:                      # global master off
+            return False
+        return system_ai_flags.get(name, True)   # system override, else inherit
+
+    return flags, flag

drb-c2-core/app/internal/summarizer.py

@@ -25,9 +25,14 @@ async def summarizer_loop() -> None:
             flags = await get_flags()
             if flags["summaries_enabled"]:
                 await _run_summary_pass()
-                await _resolve_stale_incidents()
             else:
-                logger.info("Summaries disabled — skipping summary pass and stale incident sweep")
+                logger.info("Summaries disabled — skipping summary pass")
+            # Deliberately outside the flag. Auto-resolving a quiet incident is
+            # pure Firestore with no model call in it, and gating it behind the
+            # AI kill switch meant nothing ever auto-resolved in the standing
+            # flags-off configuration — leaving every incident "active" forever
+            # and growing the candidate set every correlation reads.
+            await _resolve_stale_incidents()
         except Exception as e:
             logger.error(f"Summarizer pass failed: {e}")
 
@@ -43,10 +48,17 @@ async def _run_summary_pass() -> None:
 
 
 async def _summarize_incident(inc: dict) -> None:
+    from app.internal.feature_flags import get_flags
+
     incident_id = inc.get("incident_id")
     if not incident_id:
         return
 
+    flags = await get_flags()
+    if not flags["summaries_enabled"]:
+        logger.info(f"Summaries disabled — skipping summary for incident {incident_id}")
+        return
+
     call_ids: list[str] = inc.get("call_ids", [])
     if not call_ids:
         return

drb-c2-core/app/internal/transcription.py

@@ -205,12 +205,25 @@ async def transcribe_call(
         # correlation all consume the transcript — correcting it afterwards
         # (which is where it used to live, inside the extraction prompt) meant
         # every one of them reasoned over known-bad text. server-26#36.
-        corrected, corrected_segments, not_speech = await transcript_correction.correct(
-            call_id, transcript, segments,
-            system_id=system_id,
-            talkgroup_id=talkgroup_id,
-            talkgroup_name=talkgroup_name,
-        )
+        # Correction is a second model call plus a Places lookup per proposed
+        # location, so it is real spend that used to be reachable only through
+        # an env var and an ansible run. That made an "STT-only" evaluation
+        # window not STT-only, and its cost unattributable (server-26#76, #45).
+        from app.internal.feature_flags import resolve_flags
+        _, _ai_flag = await resolve_flags(system_id)
+
+        corrected, corrected_segments, not_speech = (None, None, False)
+        if _ai_flag("transcript_correction_enabled"):
+            corrected, corrected_segments, not_speech = await transcript_correction.correct(
+                call_id, transcript, segments,
+                system_id=system_id,
+                talkgroup_id=talkgroup_id,
+                talkgroup_name=talkgroup_name,
+            )
+        else:
+            logger.info(
+                f"Transcript correction disabled — saving raw transcript for call {call_id}"
+            )
         if corrected_segments:
             # Raw stays as evidence; the corrected copy is what extraction reads.
             updates["segments_corrected"] = corrected_segments