correlator: LLM tier reads the scene's transcript, not the whole call (server-26#102)

The last leg of the #80/#95 scene-context leak. llm_correlator._call_block
read call_doc's whole-call transcript for every scene, so on a multi-scene
call every scene's cheap-tier and tiebreaker decision was made against text
that also contained the other scenes.

- intelligence.py: each processed[] scene now carries its own "transcript" —
  transcript_corrected, else this scene's segments joined, else (single scene)
  the whole transcript.
- _build_context / preview_correlation / correlate_call: take a `transcript`
  param; _build_context resolves ctx["scene_transcript"] from it, falling
  back to the call doc (sweep, single-scene, tests) — the fallback is kept
  here, unlike embedding/severity, because a scene always has real text.
- upload.py: both scene loops pass scene["transcript"].
- llm_correlator._call_block: reads ctx["scene_transcript"] (call-doc
  fallback retained for test-built ctx).
- recorrelation_sweep: passes the call doc's text explicitly.
- +1 regression test. Full c2-core suite green (296 passed, sandboxed venv).

NOT for merge until the running correlation measurement window closes and its
dump is analysed — deploying a correlator change mid-window would mix old and
new behaviour in the sample.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

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

@@ -670,6 +670,7 @@ async def correlate_call(
     reassignment: bool = False,
     embedding: Optional[list] = None,
     severity: Optional[str] = None,
+    transcript: Optional[str] = None,
 ) ->Optional[str]:
     """
     Link call_id to an existing incident or create a new one.
@@ -686,7 +687,7 @@ async def correlate_call(
         system_id=system_id, talkgroup_id=talkgroup_id, talkgroup_name=talkgroup_name,
         tags=tags, incident_type=incident_type, location=location,
         reassignment=reassignment, create_if_new=create_if_new,
-        embedding=embedding, severity=severity,
+        embedding=embedding, severity=severity, transcript=transcript,
     )
     decision = _run_decision(ctx)
     return await _apply_and_log(decision, ctx)
@@ -710,6 +711,7 @@ async def preview_correlation(
     reassignment: bool = False,
     embedding: Optional[list] = None,
     severity: Optional[str] = None,
+    transcript: Optional[str] = None,
 ) ->dict:
     """
     Run the rules engine and return the decision WITHOUT committing to Firestore.
@@ -730,7 +732,7 @@ async def preview_correlation(
         system_id=system_id, talkgroup_id=talkgroup_id, talkgroup_name=talkgroup_name,
         tags=tags, incident_type=incident_type, location=location,
         reassignment=reassignment, create_if_new=create_if_new,
-        embedding=embedding, severity=severity,
+        embedding=embedding, severity=severity, transcript=transcript,
     )
     decision = _run_decision(ctx)
     return {"decision": decision, "ctx": ctx}
@@ -765,6 +767,7 @@ async def _build_context(
     create_if_new: bool,
     embedding: Optional[list] = None,
     severity: Optional[str] = None,
+    transcript: Optional[str] = None,
 ) -> dict:
     now    = reference_time or datetime.now(timezone.utc)
     window = timedelta(hours=settings.correlation_window_hours)
@@ -804,6 +807,13 @@ async def _build_context(
     call_vehicles  = vehicles      if vehicles      is not None else (call_doc.get("vehicles")      or [])
     call_cleared   = cleared_units if cleared_units is not None else (call_doc.get("cleared_units") or [])
     call_severity  = severity or "routine"
+    # The transcript the LLM correlation tier reasons over. Prefer the SCENE's
+    # own words (server-26#102) — passed by upload.py's scene loop — and fall
+    # back to the call doc only when no scene text was supplied (the
+    # recorrelation sweep, and single-scene calls where the two are identical).
+    # Without this, every non-primary scene of a multi-scene call was judged by
+    # the LLM against a transcript containing the OTHER scenes.
+    scene_transcript = transcript or call_doc.get("transcript_corrected") or call_doc.get("transcript")
     # A string that is not a place is not a location anywhere downstream — not
     # in the fit tests, not in the thin-call test, not in the LLM prompt, and
     # not on the incident.  Its coordinates go with it: coords are geocoded
@@ -826,6 +836,7 @@ async def _build_context(
     return {
         "call_id": call_id, "org_id": org_id, "all_active": all_active, "recent": recent,
         "call_doc": call_doc, "call_embedding": call_embedding,
+        "scene_transcript": scene_transcript,
         "call_units": call_units, "call_vehicles": call_vehicles,
         "call_cleared": call_cleared, "call_severity": call_severity,
         "coords": coords, "is_thin_call": is_thin_call, "now": now,

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

@@ -172,7 +172,7 @@ async def extract_scenes(
 
     Each scene dict contains:
         tags, incident_type, location, location_coords, resolved,
-        severity, vehicles, units, transcript_corrected,
+        severity, vehicles, units, transcript, transcript_corrected,
         segment_indices, embedding
 
     Side-effect: updates calls/{call_id} in Firestore with merged tags,
@@ -337,6 +337,19 @@ async def extract_scenes(
         )
         embedding = await asyncio.to_thread(_sync_embed, scene_text)
 
+        # This scene's own words, unprefixed — corrected text if we have it,
+        # else the raw segments this scene owns, else (single-scene) the whole
+        # transcript. The correlator's LLM tier reads this per scene instead of
+        # the call doc's whole-call transcript (server-26#102).
+        if transcript_corrected:
+            scene_transcript = transcript_corrected
+        elif segments and segment_indices:
+            scene_transcript = " ".join(
+                segments[i]["text"] for i in segment_indices if i < len(segments)
+            )
+        else:
+            scene_transcript = transcript
+
         processed.append({
             "tags":                 tags,
             "incident_type":        incident_type,
@@ -348,6 +361,7 @@ async def extract_scenes(
             "severity":             severity,
             "resolved":             resolved,
             "reassignment":         reassignment,
+            "transcript":           scene_transcript,
             "transcript_corrected": transcript_corrected,
             "segment_indices":      segment_indices,
             "embedding":            embedding,

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

@@ -61,7 +61,13 @@ def _inc_summary(inc: dict, now: datetime) -> str:
 def _call_block(ctx: dict) -> str:
     lines = []
     call_doc = ctx["call_doc"]
-    transcript = call_doc.get("transcript_corrected") or call_doc.get("transcript")
+    # The SCENE's own transcript, resolved in _build_context (server-26#102).
+    # Falls back to the call doc for a ctx built without a scene (tests, sweep).
+    transcript = (
+        ctx.get("scene_transcript")
+        or call_doc.get("transcript_corrected")
+        or call_doc.get("transcript")
+    )
     if transcript:
         lines.append(f"Transcript: {transcript[:700]}")
     if ctx["tags"]:

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

@@ -108,6 +108,7 @@ async def _recorrelate_orphan(call: dict) -> bool:
         cleared_units  = call.get("cleared_units") or [],
         embedding      = call.get("embedding"),
         severity       = call.get("severity"),
+        transcript     = call.get("transcript_corrected") or call.get("transcript"),
         reference_time = started_at,   # anchor window to when the call happened
         create_if_new  = False,        # never create — link-only
     )

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

@@ -116,6 +116,7 @@ async def _correlate_with_consensus(
     reassignment: bool = False,
     embedding: Optional[list] = None,
     severity: Optional[str] = None,
+    transcript: Optional[str] = None,
 ) -> Optional[str]:
     """
     Consensus correlator: runs the rules engine and the cheap LLM in sequence.
@@ -133,7 +134,7 @@ async def _correlate_with_consensus(
         tags=tags, incident_type=incident_type, location=location,
         location_coords=location_coords, units=units, vehicles=vehicles,
         cleared_units=cleared_units, reassignment=reassignment,
-        embedding=embedding, severity=severity,
+        embedding=embedding, severity=severity, transcript=transcript,
     )
     ctx             = preview["ctx"]
     rules_decision  = preview["decision"]
@@ -226,6 +227,7 @@ async def _run_extraction_pipeline(
                 reassignment=is_reassignment,
                 embedding=scene.get("embedding"),
                 severity=scene.get("severity"),
+                transcript=scene.get("transcript"),
             )
             if incident_id and incident_id not in incident_ids:
                 incident_ids.append(incident_id)
@@ -343,6 +345,7 @@ async def _run_intelligence_pipeline(
                 reassignment=is_reassignment,
                 embedding=scene.get("embedding"),
                 severity=scene.get("severity"),
+                transcript=scene.get("transcript"),
             )
             if incident_id and incident_id not in incident_ids:
                 incident_ids.append(incident_id)

drb-c2-core/tests/test_incident_identity.py

@@ -304,6 +304,39 @@ async def test_a_scene_is_judged_on_its_own_embedding_and_severity():
     assert ctx["call_severity"] == "major"
 
 
+@pytest.mark.asyncio
+async def test_the_llm_tier_reads_the_scene_transcript_not_the_whole_call():
+    """
+    server-26#102. intelligence.py writes only the primary scene's corrected
+    text to calls/{id}. _call_block (the LLM correlation prompt) must reason
+    over the SCENE being correlated, not a whole-call transcript that also
+    contains the other scenes. _build_context threads the scene's text in;
+    with no scene text it falls back to the call doc (sweep / single-scene).
+    """
+    with patch("app.internal.incident_correlator.fstore") as mock_fstore:
+        mock_fstore.doc_get = AsyncMock(return_value={
+            "transcript": "scene one about a fire. scene two about a traffic stop.",
+        })
+        mock_fstore.collection_list = AsyncMock(return_value=[])
+        scene = await _build_context(
+            call_id="call-1", units=None, vehicles=None, cleared_units=None,
+            location_coords=None, reference_time=NOW,
+            system_id="sys-1", talkgroup_id=383, talkgroup_name=DISPATCH_TG,
+            tags=[], incident_type="police", location=None,
+            reassignment=False, create_if_new=True,
+            transcript="scene two about a traffic stop.",
+        )
+        fallback = await _build_context(
+            call_id="call-1", units=None, vehicles=None, cleared_units=None,
+            location_coords=None, reference_time=NOW,
+            system_id="sys-1", talkgroup_id=383, talkgroup_name=DISPATCH_TG,
+            tags=[], incident_type="police", location=None,
+            reassignment=False, create_if_new=True,
+        )
+    assert scene["scene_transcript"] == "scene two about a traffic stop."
+    assert fallback["scene_transcript"] == "scene one about a fire. scene two about a traffic stop."
+
+
 @pytest.mark.asyncio
 async def test_a_bare_number_never_becomes_an_incident_location_or_title():
     inc = await _create(tags=["flames"], location="49", coords=None,