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Author SHA1 Message Date
Logan CusanoandClaude Opus 5.5 5845fc5694 ci: deploy Firestore rules with a service account, not login:ci (#51)
The deploy-firestore-rules job has failed on every push because
FIREBASE_TOKEN was never set, so rule changes (e.g. aircraft/vessels for
node-26#9) never reached prod. Switch to a dedicated least-privilege
service account whose JSON key lives in FIREBASE_SA_KEY; login:ci tokens
are deprecated and carry their minter's full access. Key is written to
RUNNER_TEMP at 0600 and removed on exit.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 12:46:33 -04:00
logan ddf13402d0 Merge pull request 'correlator: a radio code is not a location' (#182) from fix/radio-code-location into main
Build & Deploy / Build & push images (push) Successful in 4m9s
Build & Deploy / Deploy Firestore rules & indexes (push) Failing after 3s
Build & Deploy / Deploy to VM (push) Successful in 1m48s
Build & Deploy / Report a failed deploy (push) Successful in 1s
2026-09-27 11:32:12 -04:00
Logan CusanoandClaude Opus 5.5 20c5799a8d correlator: a radio code is not a location
A 09-22 replay stop was titled "Traffic Stop at 96 times 5" — a disposition
code read aloud, extracted as the location (server-26#170). clean_location
now rejects "N times N", ten-codes, "signal N", "code N", "condition N".

c2-core: 476 pass.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 11:32:09 -04:00
logan e90a73ff09 Merge pull request 'intelligence: a plate read on a patrol channel is a traffic stop' (#181) from feat/plate-read-stops into main
Build & Deploy / Build & push images (push) Successful in 4m6s
Build & Deploy / Deploy Firestore rules & indexes (push) Failing after 4s
Build & Deploy / Deploy to VM (push) Successful in 2m6s
Build & Deploy / Report a failed deploy (push) Successful in 1s
2026-09-27 10:19:27 -04:00
Logan CusanoandClaude Opus 5.5 e0fdc4fbbc intelligence: a plate read on a patrol channel is a traffic stop
Owner: plate reads should become traffic stops. Held-out replay of 09-21
(server-26#170): Ossining's Post 4 stops were read out only as plates
("Frank David Boy, 4514", "Lincoln, Charlie, Robert, 7-4-0-7") and never
became incidents.

The self-initiated backstop now treats two+ phonetic letters followed by
3-7 digits as a stop — but only when extraction found no other event in
the call (a plate on an MVA, tow or parked-car complaint stays with that
event), and never on MTA/rail/bridge/fire/EMS/DPW talkgroups.

c2-core: 475 pass.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 10:19:24 -04:00
logan 65705bf995 Merge pull request 'gemini: minimal thinking on correlation, token accounting per call' (#180) from feat/gemini-cost into main
Build & Deploy / Build & push images (push) Successful in 4m10s
Build & Deploy / Deploy Firestore rules & indexes (push) Failing after 3s
Build & Deploy / Deploy to VM (push) Successful in 1m46s
Build & Deploy / Report a failed deploy (push) Successful in 1s
2026-09-27 01:10:43 -04:00
Logan CusanoandClaude Opus 5.5 0543526eb0 gemini: minimal thinking on correlation, token accounting per call
A day of replay runs (server-26#170) spent ~$5 of Gemini on ~7 two-hour
windows (~$0.70 per 290 calls) — several dollars a day per live deployment
for correlation alone — and nothing could say where it went (#45). Gemini
3.x thinks by default and bills it as output; the deprecated
google-generativeai SDK these calls used cannot set a thinking level.

- app/internal/gemini.py: every Gemini call (correlation + transcript
  correction) goes through google-genai with JSON mode, an explicit
  thinking level, and logs in/out/thinking tokens. A model that rejects
  the level is retried without it once and remembered, so the tier is
  never lost to a config param. API failures still raise for ai_health.
- correlator: thinking_level "minimal" (a link/new/orphan choice).
  transcript correction: "low" until a replay shows minimal is safe.
- replay: runs record real Gemini token usage (metrics.gemini_usage),
  shown in the Replay tab.
- requirements: google-genai.

c2-core: 474 pass. Frontend typecheck not run (no Node on this box).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-27 01:10:40 -04:00
logan 266c958208 Merge pull request 'stops review + provisional LLM closure' (#179) from fix/stops-review-llm-reopen into main
Build & Deploy / Build & push images (push) Successful in 4m35s
Build & Deploy / Deploy Firestore rules & indexes (push) Failing after 3s
Build & Deploy / Deploy to VM (push) Successful in 2m17s
Build & Deploy / Report a failed deploy (push) Successful in 2s
2026-09-26 20:52:34 -04:00
Logan CusanoandClaude Opus 5.5 9f19750ea6 stops review + provisional LLM closure
Replay of 433b35d (server-26#170): traffic stops now open incidents
("45 Adam" stop, "CM2" stop), but the bridge MVA split 33/56 — one
transmission ("transport complete") was read as scene-resolved at 14:44
and an LLM closure was final, so the rest of the MVA opened a new one.

- LLM closure is now provisional (reopenable), like a timer close: it is
  inferred from a single transmission.
- review of 433b35d: backstop only matches a unit's own "on a stop"
  self-report (bare "car stop" mentions and "pull over" dropped), never on
  MTA/rail/bridge/fire/EMS/DPW talkgroups ("Train 4 holding on the stop"),
  negation looks 5 words back, and <=5-word reports ("Adam 3 on a stop")
  get a minimal scene instead of being skipped before the backstop.

c2-core: 471 pass.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-26 20:52:31 -04:00
logan 433b35d2ba Merge pull request 'intelligence: traffic stops and self-initiated activity open incidents' (#178) from feat/traffic-stops into main
Build & Deploy / Build & push images (push) Successful in 4m43s
Build & Deploy / Deploy Firestore rules & indexes (push) Failing after 6s
Build & Deploy / Deploy to VM (push) Successful in 1m49s
Build & Deploy / Report a failed deploy (push) Successful in 1s
2026-09-26 20:22:04 -04:00
14 changed files with 316 additions and 44 deletions
+15 -13
View File
@@ -307,28 +307,30 @@ jobs:
- name: Deploy firestore rules and indexes
env:
FIREBASE_TOKEN: ${{ secrets.FIREBASE_TOKEN }}
FIREBASE_SA_KEY: ${{ secrets.FIREBASE_SA_KEY }}
run: |
set -e
# server-26#51: this used to run over SSH on the deploy VM, gated
# on the VM having firebase-tools installed. It never did, so it
# silently warned-and-skipped on every single deploy for weeks.
# Running it here instead means the only prerequisite is a secret
# -- FIREBASE_TOKEN, from `firebase login:ci` -- rather than
# something installed by hand on a machine this pipeline doesn't
# otherwise touch. A missing token now fails this job LOUDLY
# (picked up by notify-failure) instead of a buried warning line
# nobody reads in the app deploy's logs.
if [ -z "$FIREBASE_TOKEN" ]; then
echo "FIREBASE_TOKEN secret is not set -- cannot deploy Firestore rules/indexes." >&2
echo "Generate one with 'firebase login:ci' and add it as a Gitea Actions secret." >&2
# Auth is a dedicated service account (drb-ci-firestore-deploy,
# roles: Firebase Rules Admin, Cloud Datastore Index Admin,
# Service Usage Consumer), its JSON key stored as the
# FIREBASE_SA_KEY secret. Not `firebase login:ci`: those tokens are
# deprecated and carry the full permissions of whoever minted them.
# A missing key fails this job LOUDLY (picked up by notify-failure).
if [ -z "$FIREBASE_SA_KEY" ]; then
echo "FIREBASE_SA_KEY secret is not set -- cannot deploy Firestore rules/indexes." >&2
echo "Add the drb-ci-firestore-deploy service account's JSON key as a Gitea Actions secret." >&2
exit 1
fi
export GOOGLE_APPLICATION_CREDENTIALS="$RUNNER_TEMP/firebase-sa.json"
trap 'rm -f "$GOOGLE_APPLICATION_CREDENTIALS"' EXIT
( umask 077 && printf '%s' "$FIREBASE_SA_KEY" > "$GOOGLE_APPLICATION_CREDENTIALS" )
npm install -g firebase-tools
cd infra/firestore
firebase deploy --only firestore:rules,firestore:indexes \
--project ${{ secrets.FIREBASE_PROJECT_ID }} \
--token "$FIREBASE_TOKEN" --non-interactive
--project ${{ secrets.FIREBASE_PROJECT_ID }} --non-interactive
notify-failure:
name: Report a failed deploy
@@ -371,7 +373,7 @@ jobs:
# failed before any deploy was attempted" text even when the app
# deployed fine and only the Firestore rules/indexes push failed.
if deploy_result != "failure" and rules_result == "failure":
detail = "App deploy succeeded; Firestore rules/indexes deploy FAILED (server-26#51). Rules may be stale — check FIREBASE_TOKEN and the job log."
detail = "App deploy succeeded; Firestore rules/indexes deploy FAILED (server-26#51). Rules may be stale — check the FIREBASE_SA_KEY secret and the job log."
# server-26#65: the old text here unconditionally claimed
# "production is still running the previous build" -- true only
+94
View File
@@ -0,0 +1,94 @@
"""
One place every Gemini call goes through: JSON-mode generation, an explicit
thinking level, and token accounting.
Why it exists: a day of replay runs (server-26#170) cost ~$5 of Gemini for
~7 two-hour windows — roughly $0.70 per 290 calls, which projects to several
dollars a day per live deployment for correlation alone — and nothing in DRB
could say where it went (server-26#45). Gemini 3.x models "think" by default
and bill that as output; the old google-generativeai SDK these calls used
cannot even set a thinking level. A link/new/orphan choice or a transcript
cleanup does not need extended reasoning.
Every call logs its token counts, and inside a replay run they are also added
to the run's own usage sink (see app/internal/replay.py), so a run reports
what it actually spent instead of an estimate.
"""
import json
import threading
from contextvars import ContextVar
from typing import Optional
from app.config import settings
from app.internal.logger import logger
_client = None
_client_lock = threading.Lock()
# Models that rejected a thinking level: retried without one from then on.
_no_thinking_level: set[str] = set()
_usage_sink: ContextVar[Optional[dict]] = ContextVar("drb_gemini_usage", default=None)
def collect_usage(sink: Optional[dict]):
"""Route token counts for the current context into `sink` (a replay run). Returns a reset token."""
return _usage_sink.set(sink)
def reset_usage(token) -> None:
_usage_sink.reset(token)
def _get_client():
global _client
with _client_lock:
if _client is None:
from google import genai # lazy — only when a Gemini call is made
_client = genai.Client(api_key=settings.gemini_api_key)
return _client
def _config(thinking_level: Optional[str]):
from google.genai import types
kwargs = {"response_mime_type": "application/json"}
if thinking_level:
kwargs["thinking_config"] = types.ThinkingConfig(thinking_level=thinking_level)
return types.GenerateContentConfig(**kwargs)
def _record(purpose: str, model: str, usage) -> None:
prompt = getattr(usage, "prompt_token_count", None) or 0
output = getattr(usage, "candidates_token_count", None) or 0
thoughts = getattr(usage, "thoughts_token_count", None) or 0
logger.info(f"gemini usage {purpose} {model}: in={prompt} out={output} thinking={thoughts}")
sink = _usage_sink.get()
if sink is not None:
row = sink.setdefault(f"{purpose}:{model}", {"calls": 0, "in": 0, "out": 0, "thinking": 0})
row["calls"] += 1
row["in"] += prompt
row["out"] += output
row["thinking"] += thoughts
def generate_json(model: str, prompt: str, *, purpose: str,
thinking_level: Optional[str] = "minimal") -> dict:
"""
Synchronous (run it via asyncio.to_thread). Returns the parsed JSON body.
Raises on API failure, exactly like the old per-module helpers, so callers'
ai_health classification (billing / dead model / transient) is unchanged.
"""
client = _get_client()
level = None if model in _no_thinking_level else thinking_level
try:
resp = client.models.generate_content(model=model, contents=prompt, config=_config(level))
except Exception as e:
# A model that doesn't accept this thinking level answers 400 for
# every call; drop the setting for that model rather than lose the tier.
if level and "thinking" in str(e).lower():
logger.warning(f"gemini: {model} rejected thinking_level={level!r} ({e}); retrying without it")
_no_thinking_level.add(model)
resp = client.models.generate_content(model=model, contents=prompt, config=_config(None))
else:
raise
_record(purpose, model, getattr(resp, "usage_metadata", None))
return json.loads(resp.text)
@@ -343,9 +343,21 @@ def clean_location(value) -> Optional[str]:
s = str(value).strip()
if not s or not _LOCATION_WORD_RE.search(s):
return None
if _RADIO_CODE_RE.match(s):
return None
return s
# Status/disposition codes the extractor sometimes returns as a location:
# "96 times 5" (a disposition code read aloud) titled a 09-22 replay stop
# "Traffic Stop at 96 times 5" (server-26#170); "10-8", "signal 99", "code 4"
# are the same shape.
_RADIO_CODE_RE = re.compile(
r"^\s*(?:\d{1,3}\s*(?:times|x)\s*\d{1,3}|10[\s-]?\d{1,3}|(?:signal|code|condition)\s+\d{1,3})\s*$",
re.IGNORECASE,
)
def location_is_unit(location, units) -> bool:
"""
True when a location label is really one of the incident's own unit
+45 -4
View File
@@ -267,6 +267,14 @@ async def extract_scenes(
if cleared_unit:
logger.info(f"Intelligence: call {call_id} — short clearance from {cleared_unit!r}")
return [_clearance_scene(transcript, cleared_unit)]
# "Adam 3 on a stop" is the whole report of a stop, and it is <=5
# words: the self-initiated backstop has to run here too or the most
# common phrasing never opens an incident.
tags, typ, sev = _self_initiated_backstop(transcript, [], None, "routine", talkgroup_name)
if tags:
logger.info(f"Intelligence: call {call_id} — short self-initiated report {tags}")
return [{**_clearance_scene(transcript, ""), "units": [], "cleared_units": [],
"tags": tags, "incident_type": typ, "severity": sev}]
return []
try:
@@ -419,7 +427,7 @@ async def extract_scenes(
)
tags, incident_type, severity = _self_initiated_backstop(
scene_transcript or transcript, tags, incident_type, severity
scene_transcript or transcript, tags, incident_type, severity, talkgroup_name,
)
processed.append({
@@ -489,20 +497,53 @@ async def extract_scenes(
# the stop was visible only in the archive. The prompt now says so too; this
# is the deterministic backstop, because a tag is what the creation gate
# counts as substance (incident_correlator.has_event_substance).
# Only a unit's own "on a stop" self-report — a bare "traffic stop"/"car stop"
# mention (a plate lookup on a records channel, a dispatcher's question) is
# left to the prompt, and "pull over" is too common in non-stop traffic
# ("Medic 2 pull over to the side") to trust (review of 433b35d).
_SELF_INITIATED = (
(re.compile(r"\b(on (a|the) (traffic |car |vehicle )?stop|traffic stop|car stop|vehicle stop|"
r"pull(ed|ing)? (a car |a vehicle |him |her |them )?over)\b", re.IGNORECASE),
(re.compile(r"\bon (a|the) (traffic |car |vehicle |motor vehicle )?stop\b", re.IGNORECASE),
"traffic-stop"),
(re.compile(r"\b((put|show) me out with|out with (a|one) (pedestrian|vehicle|disabled|male|female|"
r"subject|party|juvenile))\b", re.IGNORECASE),
"self-initiated"),
)
_NEGATED = re.compile(r"\b(not|don't|dont|no|never)\s+(\w+\s+){0,2}$", re.IGNORECASE)
_NEGATED = re.compile(r"\b(not|don't|dont|no|never)\s+(\S+\s+){0,5}$", re.IGNORECASE)
# "Train 4 holding on the stop", "out with a disabled on the bridge": on rail,
# bridge/tunnel, fire and EMS channels these phrases are operations, not a
# police stop. Everywhere else — including "Ch 1 (Patched ...)", which is where
# the stops actually are — the backstop applies.
_NO_BACKSTOP_TG = re.compile(r"\b(mta|rail|railroad|train|transit|bridges? and tunnels|fire|ems|"
r"rescue|ambulance|dpw|public works)\b", re.IGNORECASE)
# A plate read aloud — two or more phonetic letters then 3-7 digits:
# "Frank David Boy, 4514", "Lincoln, Charlie, Robert, 7-4-0-7". On a patrol
# channel that is a unit running a car it has stopped. Held-out replay of
# 09-21 (server-26#170): Ossining's Post 4 stops were read out only as plates
# and never became incidents.
_PHONETIC = (r"(?:adam|alpha|baker|boy|bravo|charlie|charles|david|delta|eddie|edward|echo|frank|"
r"george|golf|henry|hotel|ida|india|john|juliet|king|kilo|lincoln|lima|larry|mary|"
r"michael|mike|nora|nancy|november|ocean|oscar|peter|paul|papa|queen|robert|romeo|"
r"sam|sierra|tom|tango|union|uniform|victor|william|whiskey|x-ray|xray|young|yankee|zebra|zulu)")
_PLATE_READ = re.compile(rf"\b{_PHONETIC}(?:[,\s]+{_PHONETIC}){{1,3}}[,\s]+\d(?:[\s-]?\d){{2,6}}\b",
re.IGNORECASE)
def _self_initiated_backstop(
text: str, tags: list, incident_type: Optional[str], severity: str,
talkgroup_name: Optional[str] = None,
) -> tuple[list, Optional[str], str]:
if talkgroup_name and _NO_BACKSTOP_TG.search(talkgroup_name):
return tags, incident_type, severity
# A plate read only stands for a stop when extraction found no other
# event in the call: the plate on an MVA, a tow or a parked-car complaint
# belongs to that event, not to a new stop.
if not tags and _PLATE_READ.search(text or ""):
tags = ["traffic-stop"]
incident_type = incident_type or "police"
if severity == "routine":
severity = "minor"
for pattern, tag in _SELF_INITIATED:
m = pattern.search(text or "")
if not m or _NEGATED.search(text[: m.start()]):
+2 -10
View File
@@ -20,7 +20,6 @@ Error handling: any Gemini failure returns None from decide() and the
rules_decision from tiebreak() so the pipeline never stalls.
"""
import asyncio
import json
from datetime import datetime, timezone
from typing import Optional
from app.internal.logger import logger
@@ -190,15 +189,8 @@ def _build_tiebreak_prompt(rules_decision: dict, llm_decision: dict, ctx: dict)
# ─────────────────────────────────────────────────────────────────────────────
def _sync_gemini(model_name: str, prompt: str) -> dict:
import google.generativeai as genai # lazy import — only when needed
genai.configure(api_key=settings.gemini_api_key)
model = genai.GenerativeModel(
model_name,
generation_config={"response_mime_type": "application/json"},
)
response = model.generate_content(prompt)
return json.loads(response.text)
from app.internal import gemini
return gemini.generate_json(model_name, prompt, purpose="correlation")
# ─────────────────────────────────────────────────────────────────────────────
+5
View File
@@ -469,6 +469,9 @@ async def _run(run_id: str, org_id: str, calls: list[dict], mode: str,
fl_token = force_flags(_flags_for(mode))
ai_failures: list = []
ai_token = ai_health.collect_sandbox_failures(ai_failures)
from app.internal import gemini
usage: dict = {}
usage_token = gemini.collect_usage(usage)
try:
sem = asyncio.Semaphore(PREFETCH)
@@ -561,6 +564,7 @@ async def _run(run_id: str, org_id: str, calls: list[dict], mode: str,
metrics = compute_metrics(incidents, sb_calls)
metrics["est_cost_usd"] = _running_cost(progress, metrics, mode)
metrics["ai_failures"] = dict(Counter(f"{f['tier']}: {f['problem']}" for f in ai_failures))
metrics["gemini_usage"] = usage
except Exception as e:
status = "failed"
errors.append(f"run: {type(e).__name__}: {e}"[:300])
@@ -568,6 +572,7 @@ async def _run(run_id: str, org_id: str, calls: list[dict], mode: str,
logger.error(f"Replay {run_id} failed: {e}")
finally:
ai_health._sandbox_failures.reset(ai_token)
gemini.reset_usage(usage_token)
unforce_flags(fl_token)
fstore.exit_sandbox(sb_token)
_cancel.discard(run_id)
@@ -43,7 +43,6 @@ another equally plausible word.
"""
import asyncio
import json
import re
from typing import Any, Optional
@@ -228,14 +227,11 @@ def build_context_block(context: dict, talkgroup_name: Optional[str]) -> str:
def _sync_gemini(model_name: str, prompt: str) -> dict:
import google.generativeai as genai # lazy import — only when needed
genai.configure(api_key=settings.gemini_api_key)
model = genai.GenerativeModel(
model_name,
generation_config={"response_mime_type": "application/json"},
)
return json.loads(model.generate_content(prompt).text)
from app.internal import gemini
# Correction rewrites text against vocabulary; keep a little reasoning
# ("low") rather than the correlator's "minimal" until a replay shows
# minimal doesn't hurt it.
return gemini.generate_json(model_name, prompt, purpose="correction", thinking_level="low")
async def correct(
+6
View File
@@ -376,6 +376,7 @@ async def _run_extraction_pipeline(
"status": "resolved",
"resolved_at": clock.now().isoformat(),
"resolved_via": "llm_closure",
"reopenable": True, # provisional, see _extract_and_correlate
})
await incident_correlator.maybe_resolve_parent(incident_id)
logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
@@ -466,6 +467,11 @@ async def _extract_and_correlate(
"status": "resolved",
"resolved_at": clock.now().isoformat(),
"resolved_via": "llm_closure",
# One transmission read as "it's over" ("transport complete")
# closed the whole 09-22 bridge MVA at 14:44 and its next 56
# calls opened a second incident (server-26#170). Inferred from
# a single call, so provisional, like a timer close.
"reopenable": True,
})
await incident_correlator.maybe_resolve_parent(incident_id)
logger.info(f"Auto-resolved incident {incident_id} (LLM closure detection)")
+1
View File
@@ -6,6 +6,7 @@ firebase-admin
google-cloud-storage
openai
google-generativeai
google-genai
numpy
httpx
python-multipart
+47 -1
View File
@@ -105,7 +105,7 @@ def test_traffic_stops_become_events():
from app.internal.intelligence import _self_initiated_backstop as b
for t in ("45 Adam on a stop, Eastbound Central Express.",
"11-0. CM2 on the stop, southbound, KFLA on the right.",
"Car 7, traffic stop, Route 9 at Main"):
"Car 7 on a traffic stop, Route 9 at Main"):
tags, typ, sev = b(t, [], None, "routine")
assert "traffic-stop" in tags and typ == "police" and sev == "minor", t
tags, typ, sev = b("Charlie 1. You put me out with a pedestrian on a parkway", [], None, "routine")
@@ -115,3 +115,49 @@ def test_traffic_stops_become_events():
assert b("45-8, go ahead.", [], None, "routine") == ([], None, "routine")
# an existing type/severity is never downgraded
assert b("on a stop", ["dwi"], "police", "moderate") == (["dwi", "traffic-stop"], "police", "moderate")
def test_stop_backstop_stays_off_rail_bridge_and_ems_channels():
from app.internal.intelligence import _self_initiated_backstop as b
none = ([], None, "routine")
assert b("Train 4 holding on the stop at Grand Central", [], None, "routine",
"MTA PD Districts 6/7/11 - Police Dispatch") == none
assert b("out with a disabled on the bridge, toll plaza", [], None, "routine",
"MTA Bridges and Tunnels - Whitestone/Throgs Neck Bridge Patrols") == none
assert b("Medic 2 pull over to the side and wait", [], None, "routine") == none
assert b("ran a plate for a car stop", [], None, "routine") == none
assert b("I dont think he is on a stop", [], None, "routine") == none
assert b("45 Adam on a stop", [], None, "routine", "Ch 1 (Patched with 155.310)")[0] == ["traffic-stop"]
def test_short_stop_report_opens_a_scene():
import asyncio
from unittest.mock import patch
from app.internal import firestore as fstore, intelligence
async def run():
with patch.object(fstore, "doc_set"), patch.object(fstore, "doc_get_cached", return_value=None):
return await intelligence.extract_scenes("c1", "Adam 3 on a stop.", "Ch 1 (Patched with 155.310)")
scenes = asyncio.run(run())
assert len(scenes) == 1 and scenes[0]["tags"] == ["traffic-stop"] and scenes[0]["incident_type"] == "police"
def test_plate_read_on_a_patrol_channel_is_a_stop():
from app.internal.intelligence import _self_initiated_backstop as b
ch = "Ossining - Police Dispatch"
for t in ("Post 4. 52-62, 3-3. Hemlock Circle. Frank David Boy, 4514. 10-8.",
"4, Ossining. 52-22, Ramapo, New York. Lincoln, Charlie, Robert, 7-4-0-7 on a Chevy.",
"New York, Mary, Charlie, Nora, 5-8-6-7."):
assert b(t, [], None, "routine", ch) == (["traffic-stop"], "police", "minor"), t
# a plate on a call that is already about something else stays with it
assert b("MVA, plate Mary George Sam 2740", ["mva"], "accident", "moderate", ch) == (["mva"], "accident", "moderate")
# not on rail/bridge channels, and not without digits
assert b("Frank David Boy 4514", [], None, "routine", "MTA Bridges and Tunnels - Whitestone") == ([], None, "routine")
assert b("Charlie, David, go ahead.", [], None, "routine", ch) == ([], None, "routine")
def test_radio_codes_are_not_locations():
for junk in ("96 times 5", "96 x 1", "10-8", "Signal 99", "code 4"):
assert ic.clean_location(junk) is None, junk
for place in ("West Main Street", "Route 9", "96 Main Street", "Exit 17 southbound"):
assert ic.clean_location(place) == place, place
+70
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@@ -0,0 +1,70 @@
"""
app/internal/gemini.py — thinking level, fallback when a model rejects it,
and token accounting into a replay's usage sink (server-26#170 cost finding).
"""
from types import SimpleNamespace
from unittest.mock import patch
from app.internal import gemini
class _FakeModels:
def __init__(self, reject_thinking=False):
self.reject_thinking = reject_thinking
self.configs = []
def generate_content(self, model, contents, config):
self.configs.append(config)
if self.reject_thinking and config.get("thinking_level"):
raise RuntimeError("400 INVALID_ARGUMENT: thinking_level is not supported for this model")
return SimpleNamespace(
text='{"action": "link"}',
usage_metadata=SimpleNamespace(prompt_token_count=1200, candidates_token_count=30,
thoughts_token_count=0),
)
def _patched(models):
client = SimpleNamespace(models=models)
return (patch.object(gemini, "_get_client", return_value=client),
patch.object(gemini, "_config", lambda level: {"thinking_level": level}))
def test_minimal_thinking_by_default_and_usage_lands_in_the_sink():
models = _FakeModels()
a, b = _patched(models)
sink = {}
tok = gemini.collect_usage(sink)
try:
with a, b:
assert gemini.generate_json("m1", "p", purpose="correlation") == {"action": "link"}
finally:
gemini.reset_usage(tok)
assert models.configs == [{"thinking_level": "minimal"}]
assert sink == {"correlation:m1": {"calls": 1, "in": 1200, "out": 30, "thinking": 0}}
def test_model_that_rejects_thinking_level_falls_back_once():
models = _FakeModels(reject_thinking=True)
a, b = _patched(models)
gemini._no_thinking_level.discard("m2")
with a, b:
gemini.generate_json("m2", "p", purpose="correlation")
gemini.generate_json("m2", "p", purpose="correlation")
# first call: tried minimal, retried without; second call: straight without
assert models.configs == [{"thinking_level": "minimal"}, {"thinking_level": None}, {"thinking_level": None}]
gemini._no_thinking_level.discard("m2")
def test_other_failures_still_raise_for_ai_health():
class Boom(_FakeModels):
def generate_content(self, **kw):
raise RuntimeError("429 insufficient_quota")
a, b = _patched(Boom())
with a, b:
try:
gemini.generate_json("m3", "p", purpose="correlation")
except RuntimeError as e:
assert "insufficient_quota" in str(e)
else:
raise AssertionError("should raise")
@@ -361,6 +361,14 @@ function RunDetail({ run }: { run: ReplayRun }) {
paths: {Object.entries(m.corr_path).map(([k, v]) => `${k} ${v}`).join(" · ")}
</p>
)}
{m?.gemini_usage && Object.keys(m.gemini_usage).length > 0 && (
<p className="text-xs font-mono text-gray-500">
Gemini tokens:{" "}
{Object.entries(m.gemini_usage)
.map(([k, u]) => `${k} ${u.calls} calls, in ${u.in.toLocaleString()} / out ${u.out.toLocaleString()} / thinking ${u.thinking.toLocaleString()}`)
.join(" · ")}
</p>
)}
{m?.ai_failures && Object.keys(m.ai_failures).length > 0 && (
<p className="text-xs font-mono text-amber-400">
AI failures: {Object.entries(m.ai_failures).map(([k, v]) => `${k} ×${v}`).join(" · ")}
+1
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@@ -340,6 +340,7 @@ export interface ReplayMetrics {
llm_decisions: number;
est_cost_usd: number;
ai_failures?: Record<string, number>;
gemini_usage?: Record<string, { calls: number; in: number; out: number; thinking: number }>;
}
export interface ReplayRun {
+5 -7
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@@ -8,13 +8,11 @@
// hand-set in the Firebase console: unversioned, unreviewed, unknown. See
// SAAS_PLAN.md B1.
//
// DEPLOY IS A MANUAL, OUT-OF-BAND STEP — nothing in CI or this codebase
// pushes these rules to Firebase:
// firebase deploy --only firestore:rules --project <project-id>
// (from this directory, or point --config at infra/firestore/firebase.json
// from the repo root). Do this before or immediately after the code that
// starts stamping org_id ships — until these rules are live, the
// console-configured rules are still what's actually enforced.
// DEPLOYED BY CI on every push to main (.gitea/workflows/deploy.yml, job
// deploy-firestore-rules, service-account auth via the FIREBASE_SA_KEY
// secret — server-26#51). That job is separate from the app deploy, so a
// green app deploy does NOT mean these rules are live: check that job too.
// Editing rules in the Firebase console is overwritten by the next push.
//
// MODEL: c2-core (firebase-admin SDK, server-side) bypasses these rules
// entirely and is the sole writer for every collection below — that was