Rodrigo Rodriguez (Pragmatismo)
5a43dc81c7
Replace Azure Functions architecture with a modern FastAPI-based REST API providing image, video, speech, and vision capabilities for General Bots. Key changes: - Add FastAPI app with versioned API endpoints and OpenAPI docs - Implement services for Stable Diffusion, Zeroscope, TTS/Whisper, BLIP2 - Add pydantic schemas for request/response validation - Configure structured logging with structlog - Support lazy model loading and GPU acceleration - Update dependencies from Azure/TensorFlow stack to PyTorch/diffusers
85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
from fastapi import APIRouter, Depends, File, UploadFile
|
|
|
|
from ....schemas.generation import (
|
|
GenerationResponse,
|
|
SpeechGenerateRequest,
|
|
SpeechToTextResponse,
|
|
)
|
|
from ....services.speech_service import get_speech_service
|
|
from ...dependencies import verify_api_key
|
|
|
|
router = APIRouter(prefix="/speech", tags=["Speech"])
|
|
|
|
|
|
@router.post("/generate", response_model=GenerationResponse)
|
|
async def generate_speech(
|
|
request: SpeechGenerateRequest,
|
|
api_key: str = Depends(verify_api_key),
|
|
service=Depends(get_speech_service),
|
|
):
|
|
"""
|
|
Generate speech audio from text (Text-to-Speech).
|
|
|
|
Args:
|
|
request: Speech generation parameters including:
|
|
- prompt: Text to convert to speech
|
|
- voice: Voice model to use (optional, default: "default")
|
|
- language: Language code (optional, default: "en")
|
|
api_key: API key for authentication
|
|
service: Speech service instance
|
|
|
|
Returns:
|
|
GenerationResponse with file path to generated audio and generation time
|
|
"""
|
|
result = await service.generate(
|
|
prompt=request.prompt,
|
|
voice=request.voice,
|
|
language=request.language,
|
|
)
|
|
return GenerationResponse(**result)
|
|
|
|
|
|
@router.post("/totext", response_model=SpeechToTextResponse)
|
|
async def speech_to_text(
|
|
file: UploadFile = File(...),
|
|
api_key: str = Depends(verify_api_key),
|
|
service=Depends(get_speech_service),
|
|
):
|
|
"""
|
|
Convert speech audio to text (Speech-to-Text) using Whisper.
|
|
|
|
Supported audio formats: wav, mp3, m4a, flac, ogg
|
|
|
|
Args:
|
|
file: Audio file to transcribe
|
|
api_key: API key for authentication
|
|
service: Speech service instance
|
|
|
|
Returns:
|
|
SpeechToTextResponse with transcribed text, detected language, and confidence
|
|
"""
|
|
audio_data = await file.read()
|
|
result = await service.to_text(audio_data)
|
|
return SpeechToTextResponse(**result)
|
|
|
|
|
|
@router.post("/detect_language")
|
|
async def detect_language(
|
|
file: UploadFile = File(...),
|
|
api_key: str = Depends(verify_api_key),
|
|
service=Depends(get_speech_service),
|
|
):
|
|
"""
|
|
Detect the language of spoken audio using Whisper.
|
|
|
|
Args:
|
|
file: Audio file to analyze
|
|
api_key: API key for authentication
|
|
service: Speech service instance
|
|
|
|
Returns:
|
|
dict with detected language code and confidence score
|
|
"""
|
|
audio_data = await file.read()
|
|
result = await service.detect_language(audio_data)
|
|
return result
|