mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
return both en and fr in transcriptio
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@@ -6,6 +6,7 @@ Reflector GPU backend - transcriber
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import os
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import tempfile
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from fastapi import File
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from modal import Image, Secret, Stub, asgi_app, method
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from pydantic import BaseModel
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@@ -18,7 +19,7 @@ WHISPER_CACHE_DIR: str = "/cache/whisper"
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# Translation Model
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TRANSLATION_MODEL = "facebook/m2m100_418M"
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stub = Stub(name="reflector-transcriber")
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stub = Stub(name="reflector-lang")
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def download_whisper():
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@@ -129,6 +130,8 @@ class Whisper:
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translation = result[0].strip()
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multilingual_transcript[target_language] = translation
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print(multilingual_transcript)
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return {
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"text": multilingual_transcript,
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"words": words
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@@ -149,7 +152,9 @@ class Whisper:
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)
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@asgi_app()
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def web():
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from fastapi import Depends, FastAPI, Form, HTTPException, UploadFile, status
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from typing import List
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from fastapi import Body, Depends, FastAPI, Form, HTTPException, UploadFile, status
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from fastapi.security import OAuth2PasswordBearer
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from typing_extensions import Annotated
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@@ -174,9 +179,9 @@ def web():
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@app.post("/transcribe", dependencies=[Depends(apikey_auth)])
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async def transcribe(
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file: UploadFile,
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timestamp: Annotated[float, Form()] = 0,
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source_language: Annotated[str, Form()] = "en",
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target_language: Annotated[str, Form()] = "en"
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target_language: Annotated[str, Form()] = "fr",
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timestamp: Annotated[float, Form()] = 0.0
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) -> TranscriptResponse:
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audio_data = await file.read()
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audio_suffix = file.filename.split(".")[-1]
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@@ -58,7 +58,10 @@ class AudioTranscriptModalProcessor(AudioTranscriptProcessor):
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# Update code here once this is possible.
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# i.e) extract from context/session objects
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source_language = "en"
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target_language = "en"
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# TODO: target lang is set to "fr" for demo purposes
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# Revert back once language selection is implemented
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target_language = "fr"
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languages = TranslationLanguages()
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# Only way to set the target should be the UI element like dropdown.
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@@ -74,7 +77,7 @@ class AudioTranscriptModalProcessor(AudioTranscriptProcessor):
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files=files,
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timeout=self.timeout,
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headers=self.headers,
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json=json_payload,
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data=json_payload,
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)
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self.logger.debug(
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@@ -84,12 +87,14 @@ class AudioTranscriptModalProcessor(AudioTranscriptProcessor):
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result = response.json()
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# Sanity check for translation status in the result
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translation = ""
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if target_language in result["text"]:
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text = result["text"][target_language]
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else:
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translation = result["text"][target_language]
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text = result["text"][source_language]
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transcript = Transcript(
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text=text,
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translation=translation,
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words=[
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Word(
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text=word["text"],
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@@ -34,12 +34,12 @@ class TranscriptLinerProcessor(Processor):
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if "." not in word.text:
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continue
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partial.translation = self.transcript.translation
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# emit line
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await self.emit(partial)
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# create new transcript
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partial = Transcript(words=[])
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self.transcript = partial
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async def _flush(self):
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@@ -47,6 +47,7 @@ class Word(BaseModel):
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class Transcript(BaseModel):
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text: str = ""
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translation: str = ""
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words: list[Word] = None
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@property
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@@ -84,7 +85,7 @@ class Transcript(BaseModel):
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words = [
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Word(text=word.text, start=word.start, end=word.end) for word in self.words
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]
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return Transcript(text=self.text, words=words)
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return Transcript(text=self.text, translation=self.translation, words=words)
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class TitleSummary(BaseModel):
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@@ -1,25 +1,27 @@
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import asyncio
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from fastapi import Request, APIRouter
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from reflector.events import subscribers_shutdown
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from pydantic import BaseModel
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from reflector.logger import logger
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from aiortc import RTCPeerConnection, RTCSessionDescription, MediaStreamTrack
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from json import loads, dumps
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from enum import StrEnum
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from json import dumps, loads
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from pathlib import Path
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import av
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from aiortc import MediaStreamTrack, RTCPeerConnection, RTCSessionDescription
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from fastapi import APIRouter, Request
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from pydantic import BaseModel
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from reflector.events import subscribers_shutdown
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from reflector.logger import logger
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from reflector.processors import (
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Pipeline,
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AudioChunkerProcessor,
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AudioFileWriterProcessor,
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AudioMergeProcessor,
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AudioTranscriptAutoProcessor,
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AudioFileWriterProcessor,
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FinalSummary,
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Pipeline,
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TitleSummary,
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Transcript,
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TranscriptFinalSummaryProcessor,
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TranscriptLinerProcessor,
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TranscriptTopicDetectorProcessor,
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TranscriptFinalSummaryProcessor,
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Transcript,
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TitleSummary,
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FinalSummary,
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)
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sessions = []
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@@ -108,6 +110,7 @@ async def rtc_offer_base(
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result = {
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"cmd": "SHOW_TRANSCRIPTION",
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"text": transcript.text,
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"translation": transcript.translation,
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}
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ctx.data_channel.send(dumps(result))
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@@ -7,7 +7,6 @@ from typing import Annotated, Optional
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from uuid import uuid4
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import av
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import reflector.auth as auth
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from fastapi import (
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APIRouter,
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Depends,
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@@ -18,11 +17,13 @@ from fastapi import (
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)
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from fastapi_pagination import Page, paginate
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from pydantic import BaseModel, Field
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from starlette.concurrency import run_in_threadpool
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import reflector.auth as auth
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from reflector.db import database, transcripts
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from reflector.logger import logger
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from reflector.settings import settings
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from reflector.utils.audio_waveform import get_audio_waveform
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from starlette.concurrency import run_in_threadpool
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from ._range_requests_response import range_requests_response
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from .rtc_offer import PipelineEvent, RtcOffer, rtc_offer_base
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@@ -49,6 +50,7 @@ class AudioWaveform(BaseModel):
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class TranscriptText(BaseModel):
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text: str
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translation: str
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class TranscriptTopic(BaseModel):
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@@ -491,7 +493,10 @@ async def handle_rtc_event(event: PipelineEvent, args, data):
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# FIXME don't do copy
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if event == PipelineEvent.TRANSCRIPT:
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resp = transcript.add_event(event=event, data=TranscriptText(text=data.text))
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resp = transcript.add_event(
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event=event,
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data=TranscriptText(text=data.text, translation=data.translation),
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)
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await transcripts_controller.update(
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transcript,
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{
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