correlator: LLM tier reads the scene transcript, not the whole call (#112)
This commit was merged in pull request #112.
This commit is contained in:
@@ -670,6 +670,7 @@ async def correlate_call(
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reassignment: bool = False,
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embedding: Optional[list] = None,
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severity: Optional[str] = None,
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transcript: Optional[str] = None,
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) -> Optional[str]:
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"""
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Link call_id to an existing incident or create a new one.
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@@ -686,7 +687,7 @@ async def correlate_call(
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system_id=system_id, talkgroup_id=talkgroup_id, talkgroup_name=talkgroup_name,
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tags=tags, incident_type=incident_type, location=location,
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reassignment=reassignment, create_if_new=create_if_new,
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embedding=embedding, severity=severity,
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embedding=embedding, severity=severity, transcript=transcript,
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)
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decision = _run_decision(ctx)
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return await _apply_and_log(decision, ctx)
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@@ -710,6 +711,7 @@ async def preview_correlation(
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reassignment: bool = False,
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embedding: Optional[list] = None,
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severity: Optional[str] = None,
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transcript: Optional[str] = None,
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) -> dict:
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"""
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Run the rules engine and return the decision WITHOUT committing to Firestore.
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@@ -730,7 +732,7 @@ async def preview_correlation(
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system_id=system_id, talkgroup_id=talkgroup_id, talkgroup_name=talkgroup_name,
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tags=tags, incident_type=incident_type, location=location,
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reassignment=reassignment, create_if_new=create_if_new,
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embedding=embedding, severity=severity,
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embedding=embedding, severity=severity, transcript=transcript,
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)
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decision = _run_decision(ctx)
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return {"decision": decision, "ctx": ctx}
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@@ -765,6 +767,7 @@ async def _build_context(
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create_if_new: bool,
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embedding: Optional[list] = None,
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severity: Optional[str] = None,
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transcript: Optional[str] = None,
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) -> dict:
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now = reference_time or datetime.now(timezone.utc)
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window = timedelta(hours=settings.correlation_window_hours)
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@@ -804,6 +807,13 @@ async def _build_context(
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call_vehicles = vehicles if vehicles is not None else (call_doc.get("vehicles") or [])
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call_cleared = cleared_units if cleared_units is not None else (call_doc.get("cleared_units") or [])
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call_severity = severity or "routine"
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# The transcript the LLM correlation tier reasons over. Prefer the SCENE's
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# own words (server-26#102) — passed by upload.py's scene loop — and fall
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# back to the call doc only when no scene text was supplied (the
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# recorrelation sweep, and single-scene calls where the two are identical).
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# Without this, every non-primary scene of a multi-scene call was judged by
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# the LLM against a transcript containing the OTHER scenes.
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scene_transcript = transcript or call_doc.get("transcript_corrected") or call_doc.get("transcript")
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# A string that is not a place is not a location anywhere downstream — not
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# in the fit tests, not in the thin-call test, not in the LLM prompt, and
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# not on the incident. Its coordinates go with it: coords are geocoded
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@@ -826,6 +836,7 @@ async def _build_context(
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return {
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"call_id": call_id, "org_id": org_id, "all_active": all_active, "recent": recent,
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"call_doc": call_doc, "call_embedding": call_embedding,
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"scene_transcript": scene_transcript,
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"call_units": call_units, "call_vehicles": call_vehicles,
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"call_cleared": call_cleared, "call_severity": call_severity,
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"coords": coords, "is_thin_call": is_thin_call, "now": now,
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@@ -172,7 +172,7 @@ async def extract_scenes(
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Each scene dict contains:
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tags, incident_type, location, location_coords, resolved,
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severity, vehicles, units, transcript_corrected,
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severity, vehicles, units, transcript, transcript_corrected,
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segment_indices, embedding
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Side-effect: updates calls/{call_id} in Firestore with merged tags,
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@@ -337,6 +337,10 @@ async def extract_scenes(
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)
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embedding = await asyncio.to_thread(_sync_embed, scene_text)
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scene_transcript = _scene_transcript_text(
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transcript, segments, segment_indices, transcript_corrected
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)
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processed.append({
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"tags": tags,
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"incident_type": incident_type,
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@@ -348,6 +352,7 @@ async def extract_scenes(
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"severity": severity,
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"resolved": resolved,
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"reassignment": reassignment,
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"transcript": scene_transcript,
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"transcript_corrected": transcript_corrected,
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"segment_indices": segment_indices,
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"embedding": embedding,
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@@ -571,11 +576,49 @@ def _municipality_from_tg(tg_name: Optional[str]) -> Optional[str]:
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def _build_transcript_block(transcript: str, segments: Optional[list[dict]]) -> str:
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"""Format transcript as numbered transmissions if segments are available."""
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if segments and len(segments) > 1:
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lines = [f"{i+1}. [{s['start']}s] {s['text']}" for i, s in enumerate(segments)]
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# 0-based labels, matching the prompt's "0-based indices into the
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# numbered transmissions" — the model echoes these back as
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# `segment_indices`, which _build_scene_embed_text and the per-scene
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# `transcript` (server-26#102) then slice with directly.
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lines = [f"{i}. [{s['start']}s] {s['text']}" for i, s in enumerate(segments)]
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return f"Transmissions ({len(segments)}):\n" + "\n".join(lines)
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return f"Transcript:\n{transcript}"
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def _scene_transcript_text(
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transcript: str,
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segments: Optional[list[dict]],
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segment_indices: Optional[list[int]],
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transcript_corrected: Optional[str],
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) -> str:
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"""
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This scene's own words, unprefixed — the segments it owns, joined.
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server-26#102: the correlator's LLM tier reads this per scene instead of
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the call doc's whole-call transcript, so on a multi-scene call scene N is
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no longer judged against scenes 1..N-1's text.
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Never returns "". Anything that would leave the slice empty — no
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`segment_indices` (a single-segment call is never numbered by
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`_build_transcript_block`), or indices that are out of range / not ints —
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falls back to the whole-call transcript, which for a single-scene call is
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the same text and for a mis-sliced multi-scene call is at least this
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call's own words. `_sync_extract`'s prompt documents 0-based indices and
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`_build_transcript_block` numbers to match, so no base normalisation here.
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"""
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if transcript_corrected:
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return transcript_corrected
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if segments and segment_indices:
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joined = " ".join(
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segments[i]["text"]
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for i in segment_indices
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if isinstance(i, int) and 0 <= i < len(segments)
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)
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if joined:
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return joined
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return transcript
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def _build_scene_embed_text(
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transcript: str,
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segments: Optional[list[dict]],
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@@ -61,7 +61,13 @@ def _inc_summary(inc: dict, now: datetime) -> str:
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def _call_block(ctx: dict) -> str:
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lines = []
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call_doc = ctx["call_doc"]
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transcript = call_doc.get("transcript_corrected") or call_doc.get("transcript")
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# The SCENE's own transcript, resolved in _build_context (server-26#102).
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# Falls back to the call doc for a ctx built without a scene (tests, sweep).
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transcript = (
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ctx.get("scene_transcript")
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or call_doc.get("transcript_corrected")
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or call_doc.get("transcript")
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)
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if transcript:
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lines.append(f"Transcript: {transcript[:700]}")
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if ctx["tags"]:
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@@ -108,6 +108,7 @@ async def _recorrelate_orphan(call: dict) -> bool:
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cleared_units = call.get("cleared_units") or [],
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embedding = call.get("embedding"),
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severity = call.get("severity"),
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transcript = call.get("transcript_corrected") or call.get("transcript"),
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reference_time = started_at, # anchor window to when the call happened
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create_if_new = False, # never create — link-only
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)
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@@ -116,6 +116,7 @@ async def _correlate_with_consensus(
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reassignment: bool = False,
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embedding: Optional[list] = None,
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severity: Optional[str] = None,
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transcript: Optional[str] = None,
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) -> Optional[str]:
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"""
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Consensus correlator: runs the rules engine and the cheap LLM in sequence.
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@@ -133,7 +134,7 @@ async def _correlate_with_consensus(
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tags=tags, incident_type=incident_type, location=location,
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location_coords=location_coords, units=units, vehicles=vehicles,
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cleared_units=cleared_units, reassignment=reassignment,
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embedding=embedding, severity=severity,
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embedding=embedding, severity=severity, transcript=transcript,
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)
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ctx = preview["ctx"]
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rules_decision = preview["decision"]
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@@ -226,6 +227,7 @@ async def _run_extraction_pipeline(
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reassignment=is_reassignment,
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embedding=scene.get("embedding"),
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severity=scene.get("severity"),
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transcript=scene.get("transcript"),
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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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@@ -343,6 +345,7 @@ async def _run_intelligence_pipeline(
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reassignment=is_reassignment,
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embedding=scene.get("embedding"),
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severity=scene.get("severity"),
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transcript=scene.get("transcript"),
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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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@@ -304,6 +304,39 @@ async def test_a_scene_is_judged_on_its_own_embedding_and_severity():
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assert ctx["call_severity"] == "major"
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@pytest.mark.asyncio
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async def test_the_llm_tier_reads_the_scene_transcript_not_the_whole_call():
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"""
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server-26#102. intelligence.py writes only the primary scene's corrected
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text to calls/{id}. _call_block (the LLM correlation prompt) must reason
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over the SCENE being correlated, not a whole-call transcript that also
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contains the other scenes. _build_context threads the scene's text in;
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with no scene text it falls back to the call doc (sweep / single-scene).
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"""
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with patch("app.internal.incident_correlator.fstore") as mock_fstore:
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mock_fstore.doc_get = AsyncMock(return_value={
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"transcript": "scene one about a fire. scene two about a traffic stop.",
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})
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mock_fstore.collection_list = AsyncMock(return_value=[])
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scene = await _build_context(
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call_id="call-1", units=None, vehicles=None, cleared_units=None,
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location_coords=None, reference_time=NOW,
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system_id="sys-1", talkgroup_id=383, talkgroup_name=DISPATCH_TG,
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tags=[], incident_type="police", location=None,
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reassignment=False, create_if_new=True,
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transcript="scene two about a traffic stop.",
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)
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fallback = await _build_context(
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call_id="call-1", units=None, vehicles=None, cleared_units=None,
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location_coords=None, reference_time=NOW,
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system_id="sys-1", talkgroup_id=383, talkgroup_name=DISPATCH_TG,
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tags=[], incident_type="police", location=None,
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reassignment=False, create_if_new=True,
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)
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assert scene["scene_transcript"] == "scene two about a traffic stop."
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assert fallback["scene_transcript"] == "scene one about a fire. scene two about a traffic stop."
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@pytest.mark.asyncio
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async def test_a_bare_number_never_becomes_an_incident_location_or_title():
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inc = await _create(tags=["flames"], location="49", coords=None,
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@@ -0,0 +1,40 @@
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"""
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server-26#102 — a scene is correlated on its OWN transcript, not the whole call.
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_scene_transcript_text slices the segments a scene owns. It must never return
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"" (an empty slice would let incident_correlator._build_context fall back to
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the call doc's whole-call transcript, re-opening the leak in exactly the case
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— bad indices — where it matters).
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"""
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from app.internal.intelligence import _scene_transcript_text
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SEGS = [
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{"text": "structure fire, 12 Main"},
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{"text": "engine 4 responding"},
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{"text": "traffic stop, plate ABC"},
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{"text": "one occupant"},
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]
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WHOLE = "structure fire, 12 Main engine 4 responding traffic stop, plate ABC one occupant"
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def test_scene_owns_a_subset_of_segments():
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assert _scene_transcript_text(WHOLE, SEGS, [0, 1], None) == "structure fire, 12 Main engine 4 responding"
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assert _scene_transcript_text(WHOLE, SEGS, [2, 3], None) == "traffic stop, plate ABC one occupant"
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def test_corrected_text_wins_when_present():
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assert _scene_transcript_text(WHOLE, SEGS, [0], "cleaned up text") == "cleaned up text"
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def test_no_segment_indices_falls_back_to_whole_call():
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# single-segment calls are never numbered by _build_transcript_block → null indices
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assert _scene_transcript_text(WHOLE, SEGS, None, None) == WHOLE
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assert _scene_transcript_text(WHOLE, None, [0, 1], None) == WHOLE
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def test_out_of_range_or_nonint_indices_fall_back_never_empty():
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assert _scene_transcript_text(WHOLE, SEGS, [9, 10], None) == WHOLE # all out of range
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assert _scene_transcript_text(WHOLE, SEGS, ["1", "2"], None) == WHOLE # 1-based strings, rejected
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assert _scene_transcript_text(WHOLE, SEGS, [-1], None) == WHOLE # negative
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# partial validity: keep what's in range
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assert _scene_transcript_text(WHOLE, SEGS, [3, 99], None) == "one occupant"
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