Logan
94 lines
3.1 KiB
Python
94 lines
3.1 KiB
Python
"""
|
|
Speech-to-text transcription for recorded calls using OpenAI Whisper.
|
|
|
|
Audio is downloaded from GCS then sent to the Whisper API. Falls back to
|
|
returning None on any failure so the intelligence pipeline can still run.
|
|
"""
|
|
import asyncio
|
|
import tempfile
|
|
import os
|
|
from typing import Optional
|
|
from app.internal.logger import logger
|
|
from app.internal import firestore as fstore
|
|
|
|
|
|
async def transcribe_call(call_id: str, gcs_uri: str) -> 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
|
|
|
|
Returns:
|
|
The transcript string, or None if transcription failed / was skipped.
|
|
"""
|
|
if not gcs_uri or not gcs_uri.startswith("gs://"):
|
|
return None
|
|
|
|
try:
|
|
transcript = await asyncio.to_thread(_sync_transcribe, gcs_uri)
|
|
except Exception as e:
|
|
logger.warning(f"Transcription failed for call {call_id}: {e}")
|
|
return None
|
|
|
|
if transcript:
|
|
try:
|
|
await fstore.doc_set("calls", call_id, {"transcript": transcript})
|
|
logger.info(f"Transcript saved for call {call_id} ({len(transcript)} chars)")
|
|
except Exception as e:
|
|
logger.warning(f"Could not save transcript for {call_id}: {e}")
|
|
|
|
return transcript
|
|
|
|
|
|
def _sync_transcribe(gcs_uri: str) -> Optional[str]:
|
|
"""Download audio from GCS and transcribe with OpenAI Whisper."""
|
|
from google.cloud import storage as gcs
|
|
from google.oauth2 import service_account
|
|
from openai import OpenAI
|
|
from app.config import settings
|
|
|
|
if not settings.openai_api_key:
|
|
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,
|
|
scopes=["https://www.googleapis.com/auth/cloud-platform"],
|
|
)
|
|
gcs_client = gcs.Client(credentials=creds)
|
|
else:
|
|
gcs_client = gcs.Client()
|
|
|
|
bucket = gcs_client.bucket(bucket_name)
|
|
blob = bucket.blob(blob_path)
|
|
|
|
suffix = os.path.splitext(blob_path)[1] or ".mp3"
|
|
with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
|
|
tmp_path = tmp.name
|
|
|
|
try:
|
|
blob.download_to_filename(tmp_path)
|
|
|
|
openai_client = OpenAI(api_key=settings.openai_api_key)
|
|
with open(tmp_path, "rb") as f:
|
|
response = openai_client.audio.transcriptions.create(
|
|
model="whisper-1",
|
|
file=f,
|
|
language="en",
|
|
prompt="Public safety radio communication. May include police codes, fire, EMS, talkgroup IDs, unit numbers, addresses.",
|
|
)
|
|
return response.text.strip() or None
|
|
finally:
|
|
try:
|
|
os.unlink(tmp_path)
|
|
except OSError:
|
|
pass
|