app.py

import tensorflow as tf
from flask import Flask, request, jsonify

app = Flask(__name__)

# Load the model
model = tf.keras.models.load_model('Erfan11/Neuracraft')

@app.route('/predict', methods=['POST'])
def predict():
    data = request.get_json()
    # Preprocess input data
    inputs = preprocess_data(data)
    # Make prediction
    predictions = model.predict(inputs)
    # Postprocess and return results
    results = postprocess_predictions(predictions)
    return jsonify(results)

def preprocess_data(data):
    # Implement your data preprocessing here
    pass

def postprocess_predictions(predictions):
    # Implement your result postprocessing here
    pass

if __name__ == '__main__':
    app.run(debug=True)
    ## API Endpoints
- **POST /predict**: Receives JSON data, returns model predictions.