Create app.py

app.py

@@ -0,0 +1,29 @@
+from flask import Flask, render_template, request
+from sklearn.linear_model import LogisticRegression
+import joblib
+
+app = Flask(__name__)
+
+# Load model
+model = joblib.load('iris_model1.joblib')
+
+
+@app.route('/')
+def home():
+    return render_template('index.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+  sl = float(request.form['sepal_length'])
+  sw = float(request.form['sepal_width'])
+  pl = float(request.form['petal_length'])
+  pw = float(request.form['petal_width'])
+
+  # Predict species
+  input_data = [[sl, sw, pl, pw]]
+  pred = model.predict(input_data)
+
+  return render_template('index.html', data=pred[0])
+
+if __name__ == '__main__':
+    app.run(debug=True)