74c911b746
- Updated OpenAI package from 1.3.7 to 1.51.0 for latest API compatibility
- Added PyTorch and torchaudio dependencies for Whisper model support
- Fixed OpenAI API calls to use new AsyncOpenAI client format
- Updated transcription service to use client.audio.transcriptions.create()
- Updated translation service to use client.chat.completions.create()
- Added proper logging to language detection service
- Added environment variable loading with python-dotenv in main.py
- Fixed import order to comply with linting standards
🤖 Generated with BackendIM
Co-Authored-By: Claude <noreply@anthropic.com>
103 lines
3.1 KiB
Python
103 lines
3.1 KiB
Python
from pathlib import Path
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from contextlib import asynccontextmanager
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import logging
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from dotenv import load_dotenv
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from app.db.session import engine
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from app.db.base import Base
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from app.routes import auth, videos, transcription, translation, voice_cloning, video_processing, profile
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# Load environment variables from .env file
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load_dotenv()
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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try:
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# Create database directory
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logger.info("Starting application initialization...")
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storage_dir = Path("/app/storage/db")
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storage_dir.mkdir(parents=True, exist_ok=True)
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logger.info(f"Created storage directory: {storage_dir}")
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# Import all models to ensure they're registered with Base
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# Only create tables if database doesn't exist (for development)
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# In production, use Alembic migrations instead
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db_path = storage_dir / "db.sqlite"
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if not db_path.exists():
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logger.info("Database file doesn't exist, creating initial tables...")
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Base.metadata.create_all(bind=engine)
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else:
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logger.info("Database file exists, skipping table creation (use Alembic for migrations)")
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logger.info("Database initialization completed")
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yield
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except Exception as e:
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logger.error(f"Error during application startup: {e}")
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raise
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app = FastAPI(
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title="AI Video Dubbing API",
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description="Backend API for AI-powered video dubbing with voice cloning and translation",
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version="1.0.0",
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lifespan=lifespan
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)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
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allow_headers=["*"],
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expose_headers=["*"]
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)
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# Include routers
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app.include_router(auth.router, prefix="/auth", tags=["Authentication"])
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app.include_router(profile.router, prefix="/profile", tags=["Profile"])
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app.include_router(videos.router, prefix="/videos", tags=["Videos"])
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app.include_router(transcription.router, prefix="/transcription", tags=["Transcription"])
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app.include_router(translation.router, prefix="/translation", tags=["Translation"])
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app.include_router(voice_cloning.router, prefix="/voice", tags=["Voice Cloning"])
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app.include_router(video_processing.router, prefix="/process", tags=["Video Processing"])
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@app.get("/")
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async def root():
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return {
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"title": "AI Video Dubbing API",
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"documentation": "/docs",
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"health": "/health"
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}
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@app.get("/health")
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async def health_check():
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return {
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"status": "healthy",
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"service": "AI Video Dubbing API",
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"database": "connected"
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}
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@app.get("/test")
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async def test_endpoint():
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logger.info("Test endpoint called")
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return {
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"message": "API is working correctly",
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"timestamp": "2024-01-01T00:00:00Z",
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"status": "success"
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}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000) |