import hashlib import json import logging import os import uuid from functools import lru_cache from pathlib import Path import requests from config import ( AUDIO_STT_ENGINE, AUDIO_STT_MODEL, AUDIO_STT_OPENAI_API_BASE_URL, AUDIO_STT_OPENAI_API_KEY, AUDIO_TTS_API_KEY, AUDIO_TTS_ENGINE, AUDIO_TTS_MODEL, AUDIO_TTS_OPENAI_API_BASE_URL, AUDIO_TTS_OPENAI_API_KEY, AUDIO_TTS_SPLIT_ON, AUDIO_TTS_VOICE, CACHE_DIR, CORS_ALLOW_ORIGIN, DEVICE_TYPE, WHISPER_MODEL, WHISPER_MODEL_AUTO_UPDATE, WHISPER_MODEL_DIR, AppConfig, ) from constants import ERROR_MESSAGES from env import SRC_LOG_LEVELS 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 utils.utils import get_admin_user, get_current_user, get_verified_user log = logging.getLogger(__name__) log.setLevel(SRC_LOG_LEVELS["AUDIO"]) app = FastAPI() app.add_middleware( CORSMiddleware, allow_origins=CORS_ALLOW_ORIGIN, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) app.state.config = AppConfig() 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 app.state.config.TTS_API_KEY = AUDIO_TTS_API_KEY app.state.config.TTS_SPLIT_ON = AUDIO_TTS_SPLIT_ON # 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}") SPEECH_CACHE_DIR = Path(CACHE_DIR).joinpath("./audio/speech/") SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True) class TTSConfigForm(BaseModel): OPENAI_API_BASE_URL: str OPENAI_API_KEY: str API_KEY: str ENGINE: str MODEL: str VOICE: str SPLIT_ON: str class STTConfigForm(BaseModel): OPENAI_API_BASE_URL: str OPENAI_API_KEY: str ENGINE: str MODEL: str class AudioConfigUpdateForm(BaseModel): tts: TTSConfigForm stt: STTConfigForm 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}") @app.get("/config") async def get_audio_config(user=Depends(get_admin_user)): return { "tts": { "OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL, "OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY, "API_KEY": app.state.config.TTS_API_KEY, "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, }, "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, }, } @app.post("/config/update") async def update_audio_config( form_data: AudioConfigUpdateForm, user=Depends(get_admin_user) ): 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 app.state.config.TTS_API_KEY = form_data.tts.API_KEY 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 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 return { "tts": { "OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL, "OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY, "API_KEY": app.state.config.TTS_API_KEY, "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, }, "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, }, } @app.post("/speech") async def speech(request: Request, user=Depends(get_verified_user)): 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) 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") except Exception: 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']}" except Exception: 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) raise HTTPException(status_code=400, detail="Invalid JSON payload") voice_id = payload.get("voice", "") if voice_id not in get_available_voices(): raise HTTPException( status_code=400, detail="Invalid voice id", ) url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}" 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']}" except Exception: error_detail = f"External: {e}" raise HTTPException( status_code=r.status_code if r != None else 500, detail=error_detail, ) @app.post("/transcriptions") def transcribe( file: UploadFile = File(...), user=Depends(get_current_user), ): log.info(f"file.content_type: {file.content_type}") 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: 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}" print(filename) contents = file.file.read() with open(file_path, "wb") as f: f.write(contents) f.close() if app.state.config.STT_ENGINE == "": from faster_whisper import WhisperModel 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) except Exception: 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) ) transcript = "".join([segment.text for segment in list(segments)]) data = {"text": transcript.strip()} # 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) print(data) return data elif app.state.config.STT_ENGINE == "openai": 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) headers = {"Authorization": f"Bearer {app.state.config.STT_OPENAI_API_KEY}"} files = {"file": (filename, open(file_path, "rb"))} data = {"model": app.state.config.STT_MODEL} print(files, data) 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() data = r.json() # 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) print(data) return data 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']}" except Exception: error_detail = f"External: {e}" raise HTTPException( status_code=r.status_code if r != None else 500, detail=error_detail, ) except Exception as e: log.exception(e) raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail=ERROR_MESSAGES.DEFAULT(e), ) def get_available_models() -> list[dict]: 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 = {} if app.state.config.TTS_ENGINE == "openai": ret = { "alloy": "alloy", "echo": "echo", "fable": "fable", "onyx": "onyx", "nova": "nova", "shimmer": "shimmer", } elif app.state.config.TTS_ENGINE == "elevenlabs": try: ret = get_elevenlabs_voices() except Exception: # Avoided @lru_cache with exception pass 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 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()]}