Logan
106 lines
3.5 KiB
Python
106 lines
3.5 KiB
Python
from fastapi import APIRouter, BackgroundTasks, HTTPException, Query, Depends
|
|
from pydantic import BaseModel
|
|
from typing import Optional
|
|
from app.internal import firestore as fstore
|
|
from app.internal.auth import require_admin_token
|
|
|
|
|
|
class TranscriptUpdate(BaseModel):
|
|
transcript: str
|
|
|
|
router = APIRouter(prefix="/calls", tags=["calls"])
|
|
|
|
|
|
@router.get("")
|
|
async def list_calls(
|
|
node_id: Optional[str] = Query(None),
|
|
status: Optional[str] = Query(None),
|
|
system_id: Optional[str] = Query(None),
|
|
):
|
|
filters = {}
|
|
if node_id:
|
|
filters["node_id"] = node_id
|
|
if status:
|
|
filters["status"] = status
|
|
if system_id:
|
|
filters["system_id"] = system_id
|
|
return await fstore.collection_list("calls", **filters)
|
|
|
|
|
|
@router.get("/{call_id}")
|
|
async def get_call(call_id: str):
|
|
call = await fstore.doc_get("calls", call_id)
|
|
if not call:
|
|
raise HTTPException(404, f"Call '{call_id}' not found.")
|
|
return call
|
|
|
|
|
|
@router.post("/{call_id}/reprocess")
|
|
async def reprocess_call(call_id: str, background_tasks: BackgroundTasks):
|
|
"""Re-run the full intelligence pipeline (transcription → extraction → correlation) for a call."""
|
|
call = await fstore.doc_get("calls", call_id)
|
|
if not call:
|
|
raise HTTPException(404, f"Call '{call_id}' not found.")
|
|
|
|
from app.routers.upload import _run_intelligence_pipeline, _public_url_to_gcs_uri
|
|
|
|
audio_url = call.get("audio_url")
|
|
gcs_uri = _public_url_to_gcs_uri(audio_url) if audio_url else None
|
|
|
|
background_tasks.add_task(
|
|
_run_intelligence_pipeline,
|
|
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"),
|
|
gcs_uri=gcs_uri,
|
|
)
|
|
return {"ok": True, "call_id": call_id}
|
|
|
|
|
|
@router.patch("/{call_id}/transcript")
|
|
async def patch_transcript(
|
|
call_id: str,
|
|
body: TranscriptUpdate,
|
|
background_tasks: BackgroundTasks,
|
|
_: dict = Depends(require_admin_token),
|
|
):
|
|
"""Overwrite a call's transcript and re-run intelligence extraction."""
|
|
call = await fstore.doc_get("calls", call_id)
|
|
if not call:
|
|
raise HTTPException(404, f"Call '{call_id}' not found.")
|
|
|
|
# Save user correction as transcript_corrected; leave original transcript intact.
|
|
# Clear stale intelligence fields so re-extraction runs fresh.
|
|
await fstore.doc_set("calls", call_id, {
|
|
"transcript_corrected": body.transcript,
|
|
"tags": [],
|
|
"severity": "unknown",
|
|
"location": None,
|
|
"units": [],
|
|
"vehicles": [],
|
|
"embedding": None,
|
|
})
|
|
|
|
# Learn from the correction: diff original → corrected and add new tokens to vocabulary
|
|
system_id = call.get("system_id")
|
|
original_text = call.get("transcript_corrected") or call.get("transcript") or ""
|
|
if system_id and original_text:
|
|
from app.internal.vocabulary_learner import learn_from_correction
|
|
await learn_from_correction(system_id, original_text, body.transcript)
|
|
|
|
from app.routers.upload import _run_extraction_pipeline
|
|
background_tasks.add_task(
|
|
_run_extraction_pipeline,
|
|
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"),
|
|
transcript=body.transcript,
|
|
segments=call.get("segments"),
|
|
preserve_transcript_correction=True,
|
|
)
|
|
return {"ok": True, "call_id": call_id}
|