mirror of
https://github.com/open-webui/open-webui
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518 lines
16 KiB
Python
518 lines
16 KiB
Python
import hashlib
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import json
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import logging
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import os
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import uuid
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from functools import lru_cache
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from pathlib import Path
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import requests
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from config import (
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AUDIO_STT_ENGINE,
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AUDIO_STT_MODEL,
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AUDIO_STT_OPENAI_API_BASE_URL,
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AUDIO_STT_OPENAI_API_KEY,
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AUDIO_TTS_API_KEY,
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AUDIO_TTS_ENGINE,
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AUDIO_TTS_MODEL,
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AUDIO_TTS_OPENAI_API_BASE_URL,
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AUDIO_TTS_OPENAI_API_KEY,
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AUDIO_TTS_SPLIT_ON,
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AUDIO_TTS_VOICE,
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CACHE_DIR,
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CORS_ALLOW_ORIGIN,
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DEVICE_TYPE,
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WHISPER_MODEL,
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WHISPER_MODEL_AUTO_UPDATE,
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WHISPER_MODEL_DIR,
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AppConfig,
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)
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from constants import ERROR_MESSAGES
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from env import SRC_LOG_LEVELS
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from fastapi import Depends, FastAPI, File, HTTPException, Request, UploadFile, status
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import FileResponse
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from pydantic import BaseModel
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from utils.utils import get_admin_user, get_current_user, get_verified_user
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log = logging.getLogger(__name__)
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log.setLevel(SRC_LOG_LEVELS["AUDIO"])
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=CORS_ALLOW_ORIGIN,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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app.state.config = AppConfig()
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app.state.config.STT_OPENAI_API_BASE_URL = AUDIO_STT_OPENAI_API_BASE_URL
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app.state.config.STT_OPENAI_API_KEY = AUDIO_STT_OPENAI_API_KEY
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app.state.config.STT_ENGINE = AUDIO_STT_ENGINE
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app.state.config.STT_MODEL = AUDIO_STT_MODEL
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app.state.config.TTS_OPENAI_API_BASE_URL = AUDIO_TTS_OPENAI_API_BASE_URL
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app.state.config.TTS_OPENAI_API_KEY = AUDIO_TTS_OPENAI_API_KEY
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app.state.config.TTS_ENGINE = AUDIO_TTS_ENGINE
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app.state.config.TTS_MODEL = AUDIO_TTS_MODEL
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app.state.config.TTS_VOICE = AUDIO_TTS_VOICE
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app.state.config.TTS_API_KEY = AUDIO_TTS_API_KEY
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app.state.config.TTS_SPLIT_ON = AUDIO_TTS_SPLIT_ON
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# setting device type for whisper model
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whisper_device_type = DEVICE_TYPE if DEVICE_TYPE and DEVICE_TYPE == "cuda" else "cpu"
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log.info(f"whisper_device_type: {whisper_device_type}")
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SPEECH_CACHE_DIR = Path(CACHE_DIR).joinpath("./audio/speech/")
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SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True)
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class TTSConfigForm(BaseModel):
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OPENAI_API_BASE_URL: str
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OPENAI_API_KEY: str
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API_KEY: str
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ENGINE: str
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MODEL: str
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VOICE: str
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SPLIT_ON: str
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class STTConfigForm(BaseModel):
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OPENAI_API_BASE_URL: str
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OPENAI_API_KEY: str
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ENGINE: str
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MODEL: str
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class AudioConfigUpdateForm(BaseModel):
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tts: TTSConfigForm
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stt: STTConfigForm
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from pydub import AudioSegment
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from pydub.utils import mediainfo
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def is_mp4_audio(file_path):
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"""Check if the given file is an MP4 audio file."""
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if not os.path.isfile(file_path):
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print(f"File not found: {file_path}")
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return False
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info = mediainfo(file_path)
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if (
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info.get("codec_name") == "aac"
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and info.get("codec_type") == "audio"
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and info.get("codec_tag_string") == "mp4a"
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):
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return True
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return False
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def convert_mp4_to_wav(file_path, output_path):
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"""Convert MP4 audio file to WAV format."""
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audio = AudioSegment.from_file(file_path, format="mp4")
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audio.export(output_path, format="wav")
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print(f"Converted {file_path} to {output_path}")
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@app.get("/config")
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async def get_audio_config(user=Depends(get_admin_user)):
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return {
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"tts": {
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"OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL,
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"OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY,
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"API_KEY": app.state.config.TTS_API_KEY,
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"ENGINE": app.state.config.TTS_ENGINE,
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"MODEL": app.state.config.TTS_MODEL,
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"VOICE": app.state.config.TTS_VOICE,
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"SPLIT_ON": app.state.config.TTS_SPLIT_ON,
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},
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"stt": {
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"OPENAI_API_BASE_URL": app.state.config.STT_OPENAI_API_BASE_URL,
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"OPENAI_API_KEY": app.state.config.STT_OPENAI_API_KEY,
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"ENGINE": app.state.config.STT_ENGINE,
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"MODEL": app.state.config.STT_MODEL,
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},
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}
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@app.post("/config/update")
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async def update_audio_config(
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form_data: AudioConfigUpdateForm, user=Depends(get_admin_user)
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):
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app.state.config.TTS_OPENAI_API_BASE_URL = form_data.tts.OPENAI_API_BASE_URL
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app.state.config.TTS_OPENAI_API_KEY = form_data.tts.OPENAI_API_KEY
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app.state.config.TTS_API_KEY = form_data.tts.API_KEY
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app.state.config.TTS_ENGINE = form_data.tts.ENGINE
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app.state.config.TTS_MODEL = form_data.tts.MODEL
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app.state.config.TTS_VOICE = form_data.tts.VOICE
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app.state.config.TTS_SPLIT_ON = form_data.tts.SPLIT_ON
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app.state.config.STT_OPENAI_API_BASE_URL = form_data.stt.OPENAI_API_BASE_URL
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app.state.config.STT_OPENAI_API_KEY = form_data.stt.OPENAI_API_KEY
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app.state.config.STT_ENGINE = form_data.stt.ENGINE
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app.state.config.STT_MODEL = form_data.stt.MODEL
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return {
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"tts": {
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"OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL,
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"OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY,
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"API_KEY": app.state.config.TTS_API_KEY,
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"ENGINE": app.state.config.TTS_ENGINE,
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"MODEL": app.state.config.TTS_MODEL,
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"VOICE": app.state.config.TTS_VOICE,
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"SPLIT_ON": app.state.config.TTS_SPLIT_ON,
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},
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"stt": {
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"OPENAI_API_BASE_URL": app.state.config.STT_OPENAI_API_BASE_URL,
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"OPENAI_API_KEY": app.state.config.STT_OPENAI_API_KEY,
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"ENGINE": app.state.config.STT_ENGINE,
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"MODEL": app.state.config.STT_MODEL,
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},
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}
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@app.post("/speech")
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async def speech(request: Request, user=Depends(get_verified_user)):
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body = await request.body()
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name = hashlib.sha256(body).hexdigest()
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file_path = SPEECH_CACHE_DIR.joinpath(f"{name}.mp3")
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file_body_path = SPEECH_CACHE_DIR.joinpath(f"{name}.json")
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# Check if the file already exists in the cache
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if file_path.is_file():
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return FileResponse(file_path)
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if app.state.config.TTS_ENGINE == "openai":
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headers = {}
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headers["Authorization"] = f"Bearer {app.state.config.TTS_OPENAI_API_KEY}"
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headers["Content-Type"] = "application/json"
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try:
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body = body.decode("utf-8")
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body = json.loads(body)
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body["model"] = app.state.config.TTS_MODEL
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body = json.dumps(body).encode("utf-8")
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except Exception:
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pass
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r = None
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try:
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r = requests.post(
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url=f"{app.state.config.TTS_OPENAI_API_BASE_URL}/audio/speech",
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data=body,
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headers=headers,
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stream=True,
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)
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r.raise_for_status()
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# Save the streaming content to a file
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with open(file_path, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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with open(file_body_path, "w") as f:
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json.dump(json.loads(body.decode("utf-8")), f)
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# Return the saved file
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return FileResponse(file_path)
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']['message']}"
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except Exception:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r != None else 500,
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detail=error_detail,
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)
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elif app.state.config.TTS_ENGINE == "elevenlabs":
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payload = None
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try:
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payload = json.loads(body.decode("utf-8"))
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except Exception as e:
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log.exception(e)
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raise HTTPException(status_code=400, detail="Invalid JSON payload")
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voice_id = payload.get("voice", "")
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if voice_id not in get_available_voices():
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raise HTTPException(
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status_code=400,
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detail="Invalid voice id",
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)
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url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}"
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headers = {
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"Accept": "audio/mpeg",
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"Content-Type": "application/json",
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"xi-api-key": app.state.config.TTS_API_KEY,
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}
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data = {
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"text": payload["input"],
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"model_id": app.state.config.TTS_MODEL,
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"voice_settings": {"stability": 0.5, "similarity_boost": 0.5},
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}
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try:
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r = requests.post(url, json=data, headers=headers)
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r.raise_for_status()
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# Save the streaming content to a file
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with open(file_path, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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with open(file_body_path, "w") as f:
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json.dump(json.loads(body.decode("utf-8")), f)
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# Return the saved file
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return FileResponse(file_path)
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']['message']}"
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except Exception:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r != None else 500,
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detail=error_detail,
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)
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@app.post("/transcriptions")
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def transcribe(
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file: UploadFile = File(...),
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user=Depends(get_current_user),
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):
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log.info(f"file.content_type: {file.content_type}")
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if file.content_type not in ["audio/mpeg", "audio/wav"]:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.FILE_NOT_SUPPORTED,
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)
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try:
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ext = file.filename.split(".")[-1]
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id = uuid.uuid4()
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filename = f"{id}.{ext}"
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file_dir = f"{CACHE_DIR}/audio/transcriptions"
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os.makedirs(file_dir, exist_ok=True)
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file_path = f"{file_dir}/{filename}"
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print(filename)
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contents = file.file.read()
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with open(file_path, "wb") as f:
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f.write(contents)
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f.close()
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if app.state.config.STT_ENGINE == "":
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from faster_whisper import WhisperModel
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whisper_kwargs = {
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"model_size_or_path": WHISPER_MODEL,
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"device": whisper_device_type,
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"compute_type": "int8",
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"download_root": WHISPER_MODEL_DIR,
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"local_files_only": not WHISPER_MODEL_AUTO_UPDATE,
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}
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log.debug(f"whisper_kwargs: {whisper_kwargs}")
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try:
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model = WhisperModel(**whisper_kwargs)
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except Exception:
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log.warning(
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"WhisperModel initialization failed, attempting download with local_files_only=False"
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)
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whisper_kwargs["local_files_only"] = False
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model = WhisperModel(**whisper_kwargs)
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segments, info = model.transcribe(file_path, beam_size=5)
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log.info(
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"Detected language '%s' with probability %f"
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% (info.language, info.language_probability)
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)
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transcript = "".join([segment.text for segment in list(segments)])
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data = {"text": transcript.strip()}
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# save the transcript to a json file
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transcript_file = f"{file_dir}/{id}.json"
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with open(transcript_file, "w") as f:
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json.dump(data, f)
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print(data)
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return data
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elif app.state.config.STT_ENGINE == "openai":
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if is_mp4_audio(file_path):
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print("is_mp4_audio")
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os.rename(file_path, file_path.replace(".wav", ".mp4"))
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# Convert MP4 audio file to WAV format
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convert_mp4_to_wav(file_path.replace(".wav", ".mp4"), file_path)
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headers = {"Authorization": f"Bearer {app.state.config.STT_OPENAI_API_KEY}"}
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files = {"file": (filename, open(file_path, "rb"))}
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data = {"model": app.state.config.STT_MODEL}
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print(files, data)
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r = None
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try:
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r = requests.post(
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url=f"{app.state.config.STT_OPENAI_API_BASE_URL}/audio/transcriptions",
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headers=headers,
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files=files,
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data=data,
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)
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r.raise_for_status()
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data = r.json()
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# save the transcript to a json file
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transcript_file = f"{file_dir}/{id}.json"
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with open(transcript_file, "w") as f:
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json.dump(data, f)
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print(data)
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return data
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']['message']}"
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except Exception:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r != None else 500,
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detail=error_detail,
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)
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except Exception as e:
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log.exception(e)
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.DEFAULT(e),
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)
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def get_available_models() -> list[dict]:
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if app.state.config.TTS_ENGINE == "openai":
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return [{"id": "tts-1"}, {"id": "tts-1-hd"}]
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elif app.state.config.TTS_ENGINE == "elevenlabs":
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headers = {
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"xi-api-key": app.state.config.TTS_API_KEY,
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"Content-Type": "application/json",
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}
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try:
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response = requests.get(
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"https://api.elevenlabs.io/v1/models", headers=headers
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)
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response.raise_for_status()
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models = response.json()
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return [
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{"name": model["name"], "id": model["model_id"]} for model in models
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]
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except requests.RequestException as e:
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log.error(f"Error fetching voices: {str(e)}")
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return []
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@app.get("/models")
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async def get_models(user=Depends(get_verified_user)):
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return {"models": get_available_models()}
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def get_available_voices() -> dict:
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"""Returns {voice_id: voice_name} dict"""
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ret = {}
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if app.state.config.TTS_ENGINE == "openai":
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ret = {
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"alloy": "alloy",
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"echo": "echo",
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"fable": "fable",
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"onyx": "onyx",
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"nova": "nova",
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"shimmer": "shimmer",
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}
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elif app.state.config.TTS_ENGINE == "elevenlabs":
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try:
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ret = get_elevenlabs_voices()
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except Exception:
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# Avoided @lru_cache with exception
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pass
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return ret
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@lru_cache
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def get_elevenlabs_voices() -> dict:
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"""
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Note, set the following in your .env file to use Elevenlabs:
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AUDIO_TTS_ENGINE=elevenlabs
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AUDIO_TTS_API_KEY=sk_... # Your Elevenlabs API key
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AUDIO_TTS_VOICE=EXAVITQu4vr4xnSDxMaL # From https://api.elevenlabs.io/v1/voices
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AUDIO_TTS_MODEL=eleven_multilingual_v2
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"""
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|
headers = {
|
|
"xi-api-key": app.state.config.TTS_API_KEY,
|
|
"Content-Type": "application/json",
|
|
}
|
|
try:
|
|
# TODO: Add retries
|
|
response = requests.get("https://api.elevenlabs.io/v1/voices", headers=headers)
|
|
response.raise_for_status()
|
|
voices_data = response.json()
|
|
|
|
voices = {}
|
|
for voice in voices_data.get("voices", []):
|
|
voices[voice["voice_id"]] = voice["name"]
|
|
except requests.RequestException as e:
|
|
# Avoid @lru_cache with exception
|
|
log.error(f"Error fetching voices: {str(e)}")
|
|
raise RuntimeError(f"Error fetching voices: {str(e)}")
|
|
|
|
return voices
|
|
|
|
|
|
@app.get("/voices")
|
|
async def get_voices(user=Depends(get_verified_user)):
|
|
return {"voices": [{"id": k, "name": v} for k, v in get_available_voices().items()]}
|