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stt updates and intelligence updates

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Logan
2026-04-13 00:01:19 -04:00
parent 7b6fd640d9
commit 616c06f09c
6 changed files with 76 additions and 24 deletions
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drb-c2-core/app/config.py
+2 -2
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@@ -22,8 +22,8 @@ class Settings(BaseSettings):
# Gemini (intelligence extraction, embeddings, incident summaries)
gemini_api_key: Optional[str] = None
summary_interval_minutes: int = 15 # how often the summary loop runs
correlation_window_hours: int = 4 # how far back to look for matching incidents
summary_interval_minutes: int = 2 # how often the summary loop runs
correlation_window_hours: int = 1 # how far back to look for matching incidents
embedding_similarity_threshold: float = 0.82 # cosine similarity cutoff for slow-path match
# Internal service key — allows server-side services (discord bot) to call C2 without Firebase
drb-c2-core/app/internal/intelligence.py
+21 -8
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@@ -12,7 +12,7 @@ from typing import Optional
from app.internal.logger import logger
from app.internal import firestore as fstore
_PROMPT_TEMPLATE = """You are analyzing a P25 public safety radio transcript. Extract structured information and respond ONLY with a single valid JSON object — no markdown, no explanation.
_PROMPT_TEMPLATE = """You are analyzing a P25 public safety radio transcript. The audio was transcribed by Whisper through a digital radio vocoder, which introduces errors. Extract structured information and respond ONLY with a single valid JSON object — no markdown, no explanation.
Schema:
{{
@@ -21,7 +21,8 @@ Schema:
"location": "most specific location string found, or empty string",
"vehicles": [vehicle descriptions mentioned, e.g. "Hyundai Tucson", "black sedan"],
"units": [unit IDs or officer numbers mentioned, e.g. "Unit 511", "Car 4"],
"severity": one of "minor" | "moderate" | "major" | "unknown"
"severity": one of "minor" | "moderate" | "major" | "unknown",
"transcript_corrected": "corrected transcript string, or null if no corrections needed"
}}
Rules:
@@ -29,7 +30,9 @@ Rules:
- tags: be specific and lowercase, hyphenated. Do not repeat incident_type as a tag.
- units: only identifiers explicitly mentioned, not inferred.
- Do not invent details not present in the transcript.
- transcript_corrected: fix only clear STT errors caused by vocoder distortion (e.g. "Several" → "10-4", misheard street names, garbled unit IDs). Keep all radio language as-is — do NOT decode codes into plain English. Return null if the transcript looks accurate.
Talkgroup: {talkgroup_name}
Transcript:
{transcript}"""
@@ -37,17 +40,18 @@ Transcript:
async def extract_tags(
call_id: str,
transcript: str,
talkgroup_name: Optional[str] = None,
) -> tuple[list[str], Optional[str], Optional[str]]:
"""
Extract incident tags, type, and location from a transcript via Gemini.
Extract incident tags, type, location, and corrected transcript via Gemini.
Returns:
(tags, primary_type, location)
Side-effect: updates calls/{call_id} in Firestore with tags, location,
vehicles, units, severity; also stores the call embedding.
vehicles, units, severity, transcript_corrected; also stores the call embedding.
"""
result = await asyncio.to_thread(_sync_extract, transcript)
result = await asyncio.to_thread(_sync_extract, transcript, talkgroup_name)
tags: list[str] = result.get("tags") or []
incident_type: Optional[str] = result.get("incident_type") or None
@@ -55,6 +59,7 @@ async def extract_tags(
vehicles: list[str] = result.get("vehicles") or []
units: list[str] = result.get("units") or []
severity: str = result.get("severity") or "unknown"
transcript_corrected: Optional[str] = result.get("transcript_corrected") or None
if incident_type in ("unknown", "other", ""):
incident_type = None
@@ -74,6 +79,8 @@ async def extract_tags(
updates["units"] = units
if embedding:
updates["embedding"] = embedding
if transcript_corrected:
updates["transcript_corrected"] = transcript_corrected
try:
await fstore.doc_set("calls", call_id, updates)
@@ -82,12 +89,13 @@ async def extract_tags(
logger.info(
f"Intelligence: call {call_id} → type={incident_type}, "
f"tags={tags}, location={location!r}, severity={severity}"
f"tags={tags}, location={location!r}, severity={severity}, "
f"corrected={transcript_corrected is not None}"
)
return tags, incident_type, location
def _sync_extract(transcript: str) -> dict:
def _sync_extract(transcript: str, talkgroup_name: Optional[str]) -> dict:
"""Call Gemini Flash and parse the JSON response."""
from app.config import settings
import google.generativeai as genai
@@ -102,8 +110,13 @@ def _sync_extract(transcript: str) -> dict:
generation_config={"response_mime_type": "application/json"},
)
prompt = _PROMPT_TEMPLATE.format(
transcript=transcript,
talkgroup_name=talkgroup_name or "unknown",
)
try:
response = model.generate_content(_PROMPT_TEMPLATE.format(transcript=transcript))
response = model.generate_content(prompt)
return json.loads(response.text)
except json.JSONDecodeError as e:
logger.warning(f"Gemini returned non-JSON: {e}")
drb-c2-core/app/internal/transcription.py
+22 -7
View File
@@ -11,17 +11,34 @@ from typing import Optional
from app.internal.logger import logger
from app.internal import firestore as fstore
# Whisper treats `prompt` as preceding transcript text, not instructions.
# Writing it as actual radio speech primes the vocabulary toward P25 codes
# and phrasing before the model hears the audio.
_WHISPER_PROMPT = (
"10-4. 10-23. 10-20. 10-97. 10-8. 10-7. 10-34. 10-50. 10-52. "
"Post 4, I'm out. Post 3. En route. On scene. In route. "
"Copy. Negative. Stand by. Be advised. Go ahead. "
"Units responding. Dispatch. Talkgroup. "
"Engine. Ladder. Medic. Rescue. Car. Unit. "
"MVA. MVC. Structure fire. Working fire."
)
async def transcribe_call(call_id: str, gcs_uri: str) -> Optional[str]:
async def transcribe_call(
call_id: str,
gcs_uri: str,
talkgroup_name: Optional[str] = None,
) -> Optional[str]:
"""
Transcribe audio at the given GCS URI and store the result in Firestore.
Args:
call_id: Firestore document ID in the 'calls' collection.
gcs_uri: GCS URI of the audio file, e.g. gs://bucket/calls/xyz.mp3
call_id: Firestore document ID in the 'calls' collection.
gcs_uri: GCS URI of the audio file, e.g. gs://bucket/calls/xyz.mp3
talkgroup_name: Passed through to the intelligence layer; unused here.
Returns:
The transcript string, or None if transcription failed / was skipped.
The raw Whisper transcript string, or None if transcription failed.
"""
if not gcs_uri or not gcs_uri.startswith("gs://"):
return None
@@ -53,11 +70,9 @@ def _sync_transcribe(gcs_uri: str) -> Optional[str]:
logger.warning("OPENAI_API_KEY not set — transcription disabled.")
return None
# Parse gs://bucket/path/to/file.mp3
without_scheme = gcs_uri[len("gs://"):]
bucket_name, blob_path = without_scheme.split("/", 1)
# Download to a temp file
if settings.gcp_credentials_path:
creds = service_account.Credentials.from_service_account_file(
settings.gcp_credentials_path,
@@ -83,7 +98,7 @@ def _sync_transcribe(gcs_uri: str) -> Optional[str]:
model="whisper-1",
file=f,
language="en",
prompt="Public safety radio communication. May include police codes, fire, EMS, talkgroup IDs, unit numbers, addresses.",
prompt=_WHISPER_PROMPT,
)
return response.text.strip() or None
finally:
drb-c2-core/app/routers/upload.py
+2 -2
View File
@@ -104,14 +104,14 @@ async def _run_intelligence_pipeline(
# Step 1: Transcription
if gcs_uri:
transcript = await transcription.transcribe_call(call_id, gcs_uri)
transcript = await transcription.transcribe_call(call_id, gcs_uri, talkgroup_name)
# Step 2: Intelligence extraction
tags: list[str] = []
incident_type: Optional[str] = None
location: Optional[str] = None
if transcript:
tags, incident_type, location = await intelligence.extract_tags(call_id, transcript)
tags, incident_type, location = await intelligence.extract_tags(call_id, transcript, talkgroup_name)
# Step 3: Incident correlation
if incident_type: