Update app.py

app.py

@@ -1,12 +1,15 @@
-import pickle
+import os
 import tensorflow as tf
 from tensorflow import keras
 from fastapi import FastAPI
 from pydantic import BaseModel
 import uvicorn
 
+# Suppress TensorFlow logging
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+
 # Load the model
-model_path = 'doctor_ai_model.h5'
+model_path = '/content/drive/MyDrive/DoctorAi/doctor_ai_model.h5'
 model = keras.models.load_model(model_path)
 
 # Create FastAPI app
@@ -28,11 +31,11 @@ async def predict(data: InputData):
         return {'error': f'Input data must have shape: {expected_shape}'}
     
     # Make a prediction
-    prediction = model.predict(tf.expand_dims(input_array, axis=0))  # Expand dims to match batch size
+    prediction = model.predict(tf.expand_dims(input_array, axis=0))
     predicted_class = tf.argmax(prediction, axis=1).numpy().tolist()
     
     return {'predicted_class': predicted_class}
 
-# Start the FastAPI server (this will run offline)
+# Start the FastAPI server
 if __name__ == '__main__':
-    uvicorn.run(app, host='127.0.0.1', port=8000)  # Use localhost for offline mode
+    uvicorn.run(app, host='127.0.0.1', port=8000)