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Runtime error
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import pickle
import tensorflow as tf
from tensorflow import keras
from fastapi import FastAPI
from pydantic import BaseModel
import uvicorn
# Load the model
model_path = 'doctor_ai_model.h5'
model = keras.models.load_model(model_path)
# Create FastAPI app
app = FastAPI()
# Define the request model
class InputData(BaseModel):
input_data: list
# Define the prediction endpoint
@app.post('/predict')
async def predict(data: InputData):
# Prepare input data
input_array = tf.convert_to_tensor(data.input_data)
# Check if input shape matches the model's input shape
expected_shape = (None, 27)
if input_array.shape[1] != expected_shape[1]:
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
predicted_class = tf.argmax(prediction, axis=1).numpy().tolist()
return {'predicted_class': predicted_class}
# Start the FastAPI server (this will run offline)
if __name__ == '__main__':
uvicorn.run(app, host='127.0.0.1', port=8000) # Use localhost for offline mode
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