open-webui/backend/open_webui/apps/audio/main.py

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