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server-26/drb-c2-core/app/internal/recorrelation_sweep.py
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Logan CusanoandClaude Opus 5.5 d485eae41a Transcription: config-driven OpenAI-compatible STT with OpenAI fallback (server-26#297, server-26#83)
STT_PROVIDER=auto picks Groq whisper-large-v3-turbo only when GROQ_API_KEY is
set (else OpenAI, unchanged); compat covers any OpenAI-compatible server via
STT_BASE_URL/STT_API_KEY. A failed primary falls back to OpenAI STT_MODEL on
the same downloaded audio; the fallback reports to its own ai_health tier so
a dead primary stays red. The non-OpenAI provider gets a token-budgeted
glossary prompt (area places, local_knowledge, vocabulary; never ten-codes),
guarded by a narrow prompt-echo check. A per-30s-window zlib compression
check (Whisper's 2.4) adds a noise gate that survives correction being off
(#83, partial). Call docs record stt_provider/model/audio_seconds/confidence.
The sweep hold-back counts the fallback attempt. gate_chatter added to
chatter_classifier (used by transcription to skip correction when
CHATTER_GATE_ENABLED). GROQ_API_KEY templated with default ''.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-27 20:28:30 -04:00

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"""
Re-correlation sweep.
Runs every summary_interval_minutes (same tick as the summarizer). Each pass
finds calls that are:
- recently ended (ended_at within the last recorrelation_scan_minutes)
- still orphaned (incident_id is null)
and re-runs the incident correlator against currently-active incidents, using
the call's own started_at as the time anchor so the window is correct regardless
of when the sweep fires.
Never creates new incidents — link-only. Zero LLM tokens (uses pre-computed
talkgroup strings, haversine math, and stored embeddings).
"""
import asyncio
import math
from datetime import datetime, timezone, timedelta
from typing import Optional
from app.internal.logger import logger
from app.internal import firestore as fstore
from app.config import settings
# server-26#131: minimum time since the real-time pipeline (routers/upload.py
# _run_intelligence_pipeline) marked intelligence_started_at before the sweep
# will touch a call, even though it already looks orphaned. STT + scene
# extraction + correlation is a multi-second-to-low-minutes chain (Whisper,
# then a Gemini call per scene); without this buffer the sweep could pick up
# a call mid-pipeline — no incident_id/corr_path written yet — and correlate
# it a second time, independently, sometimes onto a different incident than
# the real-time path lands on. That race is what #131 found (same call in
# two incidents' call_ids, ~2% of linked calls). A call with no
# intelligence_started_at at all (pre-#131 call doc, or the marker write
# itself failed) is NOT held back by this — absence isn't evidence of an
# in-flight pipeline, and #131's own bug predates this field existing.
#
# Derived, not guessed (server-26#153). Every AI request the real-time
# pipeline makes now has an explicit timeout (config.py: stt_timeout_seconds,
# openai_timeout_seconds, openai_max_retries, gemini_timeout_seconds), so the
# longest a call can stay "started but no corr_path yet" has an upper bound:
# pipeline_worst_case_seconds() below. The hold-back is that bound rounded up,
# never below the old hand-picked 15.
#
# Raising it costs nothing on the recovery side: a call that finished
# processing (linked OR genuinely orphaned) always has corr_path set
# (_apply_and_log writes it even on the orphan action), so it's already
# excluded by the `not c.get("corr_path")` filter below and never reaches this
# check at all — this constant only ever delays calls that are still actually
# running, or whose pipeline died after writing the marker.
# Scenes whose embeddings are computed before the first scene's correlation
# commits (intelligence.extract_scenes embeds every scene, then upload.py
# correlates them in order; scene 0's commit writes corr_path). Extraction
# rarely returns more than 2; 3 is the budget, not a hard cap.
_BOUND_SCENES = 3
# Non-AI work on the same path: GCS download, Firestore reads/writes, geocoding
# and place verification (httpx, 5s timeouts each).
_NON_AI_SLACK_SECONDS = 120.0
_FLOOR_MINUTES = 15
def pipeline_worst_case_seconds(n_scenes: int = _BOUND_SCENES) -> float:
"""Upper bound on intelligence_started_at -> first corr_path write, from
the configured AI timeouts. Order follows routers/upload.py
_run_intelligence_pipeline."""
openai_attempts = 1 + max(0, settings.openai_max_retries)
stt_rounds = 2 if settings.stt_retry_on_degenerate else 1
# A failed primary STT provider falls back to OpenAI (server-26#297), so
# the worst case is every configured target timing out in turn.
from app.internal.transcription import stt_targets
stt_providers = max(1, len(stt_targets()))
stt = stt_providers * stt_rounds * openai_attempts * settings.stt_timeout_seconds
# Transcript correction (inside transcribe_call). gemini.generate_json only
# re-issues a request when the model rejects a thinking level — a fast
# 400, not a timeout — and google-genai itself does not retry.
correction = settings.gemini_timeout_seconds
extraction = openai_attempts * settings.openai_timeout_seconds
embeddings = n_scenes * openai_attempts * settings.openai_timeout_seconds
correlation = 2 * settings.gemini_timeout_seconds # decide + tiebreak, scene 0
return stt + correction + extraction + embeddings + correlation + _NON_AI_SLACK_SECONDS
def _derive_min_minutes() -> int:
return max(_FLOOR_MINUTES, math.ceil(pipeline_worst_case_seconds() / 60))
# 21 with the defaults (stt 120s, openai 60s x2 attempts, gemini 60s, 3 scenes).
MIN_MINUTES_SINCE_PIPELINE_START = _derive_min_minutes()
# Standard link-only retry budget before a call is tombstoned corr_path="unlinked".
MAX_SWEEP_ATTEMPTS = 3
# server-26#115 — a call the consensus LLM-orphan gate parked (llm=orphan vs
# rules=new, no substance) gets a longer budget. The gate fires before any
# incident for the job may exist, so the substantive call that would justify
# linking can land well after the standard ~6 min. Still link-only: a genuinely
# thin call must not mint an incident, and the rules creation gate would re-orphan
# it anyway.
GATED_ORPHAN_SWEEP_ATTEMPTS = 10
def _max_sweep_attempts(call: dict) -> int:
if call.get("corr_consensus") == "llm_orphan_gate":
return GATED_ORPHAN_SWEEP_ATTEMPTS
return MAX_SWEEP_ATTEMPTS
async def recorrelation_loop() -> None:
interval = settings.summary_interval_minutes * 60
logger.info(
f"Re-correlation sweep started — "
f"interval: {settings.summary_interval_minutes}m, "
f"scan window: {settings.recorrelation_scan_minutes}m, "
f"pipeline hold-back: {MIN_MINUTES_SINCE_PIPELINE_START}m"
)
if MIN_MINUTES_SINCE_PIPELINE_START >= settings.recorrelation_scan_minutes:
# A call is held back longer than the window that finds it, so the
# sweep can never recover a call whose pipeline died mid-flight.
logger.warning(
f"Re-correlation sweep: pipeline hold-back ({MIN_MINUTES_SINCE_PIPELINE_START}m) "
f">= scan window ({settings.recorrelation_scan_minutes}m) — lower the AI "
f"timeouts or raise RECORRELATION_SCAN_MINUTES"
)
while True:
await asyncio.sleep(interval)
try:
await _run_sweep_pass()
except Exception as e:
logger.error(f"Re-correlation sweep failed: {e}")
def _pipeline_likely_still_running(call: dict, now: datetime) -> bool:
"""server-26#131 — True when the real-time pipeline marked
intelligence_started_at recently enough that it's probably still mid-flight
(STT / scene extraction / correlation), so the sweep should not race it.
No marker at all (older call doc, or the marker write itself failed)
returns False — absence isn't evidence of an in-flight pipeline."""
started = _parse_dt(call.get("intelligence_started_at"))
if not started:
return False
age_minutes = (now - started).total_seconds() / 60
return age_minutes < MIN_MINUTES_SINCE_PIPELINE_START
async def _run_sweep_pass() -> None:
from app.internal import clock
now = clock.now()
cutoff = now - timedelta(minutes=settings.recorrelation_scan_minutes)
# Server-side range query: only calls that ended within the scan window.
# Filter incident_id=null client-side (Firestore can't query for missing fields).
# This keeps the fetched set small regardless of total collection size.
recent_ended = await fstore.collection_where("calls", [
("status", "==", "ended"),
("ended_at", ">=", cutoff),
])
# corr_path="unlinked" is written after the attempt budget is exhausted.
# Allows a few retries so a welfare-check call can link to an escalation
# incident that is created a few minutes later, without sweeping 30× forever.
orphans = [
c for c in recent_ended
if not c.get("incident_ids") and not c.get("incident_id")
and not c.get("corr_path") # skip calls already exhausted
and not c.get("duplicate_of") # another node's copy — never processed by design
# /upload deliberately skips correlation for garbage and too-short
# transcripts (routers/upload.py) because they carry no signal. The sweep
# was not applying the same guard, so those fragments came back in through
# the thin path minutes later and attached to whatever was most recent —
# a second route into the over-merge the thin fix above addresses.
and not c.get("skip_reason")
and c.get("corr_sweep_count", 0) < _max_sweep_attempts(c)
and not _pipeline_likely_still_running(c, now)
]
if not orphans:
return
logger.info(f"Re-correlation sweep: {len(orphans)} orphaned call(s) to check")
linked = 0
for call in orphans:
if await _recorrelate_orphan(call):
linked += 1
if linked:
logger.info(f"Re-correlation sweep: linked {linked}/{len(orphans)} orphaned call(s)")
async def _recorrelate_orphan(call: dict) -> bool:
"""
Attempt to link a single orphaned call to an existing incident.
Returns True if a match was found and the call was linked.
"""
from app.internal import incident_correlator
call_id = call.get("call_id")
started_at = _parse_dt(call.get("started_at"))
if not call_id or not started_at:
return False
# All data needed for correlation was stored by the first-pass extraction.
# embedding/severity are no longer read from the call doc inside
# _build_context (server-26#80/#95) — the sweep re-links a whole call, not a
# scene, so it passes the call doc's stored (primary-scene) values here. It
# is link-only (create_if_new=False), so a borrowed severity cannot open a
# new incident off this path.
incident_id = await incident_correlator.correlate_call(
call_id = call_id,
node_id = call.get("node_id", ""),
system_id = call.get("system_id"),
talkgroup_id = call.get("talkgroup_id"),
talkgroup_name = call.get("talkgroup_name"),
tags = call.get("tags") or [],
incident_type = call.get("incident_type"),
location = call.get("location"),
location_coords= call.get("location_coords"),
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
)
if incident_id:
await fstore.doc_set("calls", call_id, {"incident_ids": [incident_id]})
logger.info(
f"Re-correlation: linked orphaned call {call_id} → incident {incident_id}"
)
return True
# Increment the attempt counter. Once the budget is reached the orphan filter
# above will stop picking this call up, and we write corr_path="unlinked" as
# a permanent tombstone.
attempts = call.get("corr_sweep_count", 0) + 1
update: dict = {"corr_sweep_count": attempts}
if attempts >= _max_sweep_attempts(call):
update["corr_path"] = "unlinked"
await fstore.doc_set("calls", call_id, update)
return False
def _parse_dt(value) -> Optional[datetime]:
if not value:
return None
try:
dt = datetime.fromisoformat(str(value).replace("Z", "+00:00"))
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
return dt
except Exception:
return None