Update main.py

main.py

@@ -11,26 +11,11 @@ from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
 import tempfile
 import uuid
 import shutil
+from contextlib import asynccontextmanager
 
 # Disable numba JIT to avoid caching issues
 os.environ["NUMBA_DISABLE_JIT"] = "1"
 
-# Initialize FastAPI app
-app = FastAPI(
-    title="Quran Recitation Comparison API",
-    description="API for comparing similarity between Quran recitations using Wav2Vec2 embeddings",
-    version="1.0.0"
-)
-
-# Add CORS middleware
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],  # Allows all origins
-    allow_credentials=True,
-    allow_methods=["*"],  # Allows all methods
-    allow_headers=["*"],  # Allows all headers
-)
-
 # Global variables
 MODEL = None
 PROCESSOR = None
@@ -59,10 +44,10 @@ def initialize_model():
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         print(f"Loading model on device: {device}")
         
-        # Load model and processor
+        # Load model and processor using the updated parameter `token`
         if hf_token:
-            PROCESSOR = Wav2Vec2Processor.from_pretrained(model_name, use_auth_token=hf_token)
-            MODEL = Wav2Vec2ForCTC.from_pretrained(model_name, use_auth_token=hf_token)
+            PROCESSOR = Wav2Vec2Processor.from_pretrained(model_name, token=hf_token)
+            MODEL = Wav2Vec2ForCTC.from_pretrained(model_name, token=hf_token)
         else:
             PROCESSOR = Wav2Vec2Processor.from_pretrained(model_name)
             MODEL = Wav2Vec2ForCTC.from_pretrained(model_name)
@@ -280,13 +265,24 @@ async def health_check():
         )
     return {"status": "ok", "model_loaded": True}
 
-# Initialize model on startup
-@app.on_event("startup")
-async def startup_event():
+# Use lifespan context manager instead of on_event decorators
+@asynccontextmanager
+async def lifespan(app: FastAPI):
     initialize_model()
+    yield
+
+# Initialize FastAPI app with lifespan handler
+app = FastAPI(
+    title="Quran Recitation Comparison API",
+    description="API for comparing similarity between Quran recitations using Wav2Vec2 embeddings",
+    version="1.0.0",
+    lifespan=lifespan
+)
+
+# Note: Ensure that all route definitions are declared AFTER the app initialization above.
 
 # Run the FastAPI app
 if __name__ == "__main__":
     import uvicorn
     port = int(os.environ.get("PORT", 7860))  # Default to port 7860 for Hugging Face Spaces
-    uvicorn.run("main:app", host="0.0.0.0", port=port, reload=False)
+    uvicorn.run("main:app", host="0.0.0.0", port=port, reload=False)