Update main.py

main.py

@@ -5,19 +5,28 @@ import numpy as np
 
 app = FastAPI()
 
-# Load the ONNX model (in same folder as this script)
+# Load the ONNX model (assumed in the same folder)
 session = ort.InferenceSession("model.onnx", providers=["CPUExecutionProvider"])
 input_name = session.get_inputs()[0].name
 output_name = session.get_outputs()[0].name
 
+# Optional: print model input shape for debugging
+print("Model expects input shape:", session.get_inputs()[0].shape)
+
 class InputData(BaseModel):
     features: list[float]
 
+@app.get("/")
+def root():
+    return {"message": "ONNX model API is running. Use POST /predict with a JSON payload."}
+
 @app.post("/predict")
 async def predict(data: InputData):
     try:
         arr = np.array([data.features], dtype=np.float32)
+        print("Received input shape:", arr.shape)
         pred = session.run([output_name], {input_name: arr})
         return {"prediction": pred[0].tolist()}
     except Exception as e:
+        print("Prediction error:", str(e))
         raise HTTPException(status_code=500, detail=str(e))