Create web service

web service

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+ Import necessary libraries
+import tensorflow as tf
+from keras.models import load_model
+from flask import Flask, request
+
+# Initialize the Flask app
+app = Flask(_name_)
+
+# Define the API endpoint
+@app.route('/greet', methods=['GET'])
+def greet():
+
+    #get response value
+    data = request.args.get('name')
+    # Load the model
+    model = load_model('model.h5')
+
+    # Define any preprocessing functions
+    def preprocess_data(data):
+        # Perform necessary preprocessing steps
+        return processed_data
+
+    # Extract the input data from the API request
+    data = request.get_json()
+
+    # Preprocess the data
+    processed_data = preprocess_data(data)
+
+    # Make a prediction using the model
+    prediction = model.predict(processed_data)
+
+    return jsonify(prediction)
+
+if _name_ == '_main_':
+    app.run()