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Set a valid voice for a persona (xi_labs voices)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,39 @@ | ||
| from starlette.responses import JSONResponse | ||
| from backend.managers.VoicesFacesManager import VoicesFacesManager | ||
| from common.paths import api_base_url | ||
| from backend.pagination import parse_pagination_params | ||
| from backend.schemas import VoiceCreateSchema | ||
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| class VoicesFacesView: | ||
| def __init__(self): | ||
| self.vfm = VoicesFacesManager() | ||
| # TODO: Finish text to speech | ||
| async def post(self, id: str, body: VoiceCreateSchema): | ||
| response, error_message = await self.vfm.text_to_speech(id, body) | ||
| if error_message: | ||
| return JSONResponse({"error": error_message}, status_code=404) | ||
| else: | ||
| return JSONResponse(response, status_code=200) | ||
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| async def search(self, filter: str = None, range: str = None, sort: str = None): | ||
| result = parse_pagination_params(filter, range, sort) | ||
| if isinstance(result, JSONResponse): | ||
| return result | ||
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| offset, limit, sort_by, sort_order, filters = result | ||
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| voices, total_count = await self.vfm.retrieve_voices( | ||
| limit=limit, | ||
| offset=offset, | ||
| sort_by=sort_by, | ||
| sort_order=sort_order, | ||
| filters=filters | ||
| ) | ||
| headers = { | ||
| 'X-Total-Count': str(total_count), | ||
| 'Content-Range': f'voices {offset}-{offset + len(voices) - 1}/{total_count}' | ||
| } | ||
| return JSONResponse([voice.dict() for voice in voices], status_code=200, headers=headers) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,150 @@ | ||
| from threading import Lock | ||
| import os | ||
| import requests | ||
| from backend.schemas import VoiceCreateSchema | ||
| from backend.db import db_session_context | ||
| from uuid import uuid4 | ||
| from backend.models import Voice | ||
| from typing import List, Tuple, Optional, Dict, Any | ||
| from sqlalchemy import select, func | ||
| from backend.schemas import VoiceSchema | ||
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| class VoicesFacesManager: | ||
| _instance = None | ||
| _lock = Lock() | ||
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| def __new__(cls, *args, **kwargs): | ||
| if not cls._instance: | ||
| with cls._lock: | ||
| if not cls._instance: | ||
| cls._instance = super(VoicesFacesManager, cls).__new__(cls, *args, **kwargs) | ||
| return cls._instance | ||
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| def __init__(self): | ||
| if not hasattr(self, '_initialized'): | ||
| with self._lock: | ||
| if not hasattr(self, '_initialized'): | ||
| self._initialized = True | ||
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| async def map_xi_to_voice(self): | ||
| xi_voices = [] | ||
| xi_api_key = os.environ.get('XI_API_KEY') | ||
| xi_url = "https://api.elevenlabs.io/v1/voices" | ||
| headers = { | ||
| "Accept": "application/json", | ||
| "xi-api-key": xi_api_key, | ||
| "Content-Type": "application/json" | ||
| } | ||
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| response = requests.get(xi_url, headers=headers) | ||
| data = response.json() | ||
| for voice in data['voices']: | ||
| voice_data = { | ||
| 'xi_id': voice['voice_id'], | ||
| 'name': voice['name'], | ||
| 'image_url': '/voice-icon.png', | ||
| 'sample_url': '/' + voice['name'] + '.mp3' | ||
| } | ||
| xi_voices.append(voice_data) | ||
| return xi_voices | ||
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| async def create_voice(self, voice_data: VoiceCreateSchema) -> str: | ||
| async with db_session_context() as session: | ||
| new_voice = Voice(id=str(uuid4()), xi_id=voice_data['xi_id'], name=voice_data['name'], image_url=voice_data['image_url'], sample_url=voice_data['sample_url']) | ||
| session.add(new_voice) | ||
| await session.commit() | ||
| await session.refresh(new_voice) | ||
| return new_voice.id | ||
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| async def retrieve_voice(self, voice_id: str) -> Optional[VoiceSchema]: | ||
| async with db_session_context() as session: | ||
| query = select(Voice).filter(Voice.id == voice_id) | ||
| result = await session.execute(query) | ||
| voice = result.scalar_one_or_none() | ||
| if voice: | ||
| return VoiceSchema.from_orm(voice) | ||
| return None | ||
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| async def retrieve_voices(self, offset: int = 0, limit: int = 100, sort_by: Optional[str] = None, | ||
| sort_order:str = 'asc', filters: Optional[Dict[str, Any]] = None) -> Tuple[List[VoiceSchema], int]: | ||
| async with db_session_context() as session: | ||
| query = select(Voice) | ||
| result = await session.execute(query) | ||
| db_voice = result.scalars().all() | ||
| if db_voice == []: | ||
| xi_voices = await self.map_xi_to_voice() | ||
| for voice in xi_voices: | ||
| await self.create_voice(voice) | ||
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| if filters: | ||
| for key, value in filters.items(): | ||
| if key == 'name': | ||
| query = query.filter(Voice.name.ilike(f"%{value}%")) | ||
| elif isinstance(value, list): | ||
| query = query.filter(getattr(Voice, key).in_(value)) | ||
| else: | ||
| query = query.filter(getattr(Voice, key) == value) | ||
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| if sort_by and sort_by in ['id','xi_id', 'name','image_url','sample_url']: | ||
| order_column = getattr(Voice, sort_by) | ||
| query = query.order_by(order_column.desc() if sort_order.lower() == 'desc' else order_column) | ||
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| query = query.offset(offset).limit(limit) | ||
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| result = await session.execute(query) | ||
| voices = [VoiceSchema.from_orm(voice) for voice in result.scalars().all()] | ||
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| # Get total count | ||
| count_query = select(func.count()).select_from(Voice) | ||
| if filters: | ||
| for key, value in filters.items(): | ||
| if key == 'name': | ||
| count_query = count_query.filter(Voice.name.ilike(f"%{value}%")) | ||
| elif isinstance(value, list): | ||
| count_query = count_query.filter(getattr(Voice, key).in_(value)) | ||
| else: | ||
| count_query = count_query.filter(getattr(Voice, key) == value) | ||
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| total_count = await session.execute(count_query) | ||
| total_count = total_count.scalar() | ||
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| return voices, total_count | ||
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| async def text_to_speech(self, voice_id: str, body) -> str: | ||
| xi_api_key = os.environ.get('XI_API_KEY') | ||
| xi_id = body['xi_id'] | ||
| OUTPUT_PATH = f"{xi_id}.mp3" # Path to save the output audio file | ||
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| tts_url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}/stream" | ||
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| headers = { | ||
| "Accept": "application/json", | ||
| "xi-api-key": xi_api_key | ||
| } | ||
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| data = { | ||
| "text": "Hola" , | ||
| "model_id": "eleven_multilingual_v2", | ||
| "voice_settings": { | ||
| "stability": 0.5, | ||
| "similarity_boost": 0.8, | ||
| "style": 0.0, | ||
| "use_speaker_boost": True | ||
| } | ||
| } | ||
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| response = requests.post(tts_url, headers=headers, json=data, stream=True) | ||
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| if response.ok: | ||
| with open(OUTPUT_PATH, "wb") as f: | ||
| for chunk in response.iter_content(chunk_size=os.environ.get('XI_CHUNK_SIZE')): | ||
| f.write(chunk) | ||
| print("Audio stream saved successfully.") | ||
| else: | ||
| print(response.text) | ||
| return response.text | ||
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