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app.py

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+'''
+This is a Flask web application that reads a pickle file to load a machine learning model,
+accepts user input from a web form, and returns a prediction using the model.
+
+'''
+
+# https://flask.palletsprojects.com/en/2.2.x/quickstart/
+from flask import Flask, render_template, request
+import pickle
+import numpy as np
+
+# create flask app
+app = Flask(__name__)
+
+# Load the pickle model file
+def load_model():
+    try:
+        return pickle.load(open("model.pkl", "rb"))
+    except:
+        return None
+
+model = load_model()
+
+@app.route('/')
+def home():
+    return render_template('index.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    if model is None:
+        error_message = "Sorry, an error occurred while loading the model. Please try again later."
+        return render_template('index.html', result=error_message)
+
+    # Get the features from the request form and make a prediction
+    features = [float(x) for x in request.form.values()]
+    final_features = [np.array(features)]
+    prediction = model.predict(final_features)
+    result = round(prediction[0], 1)
+
+    # Create a result string to show to the user
+    result_string = f"The predicted diabetes outcome is {result}."
+    return render_template('index.html', result=result_string)
+
+if __name__ == "__main__":
+    app.run(debug=True)