add simple ml code

app.py

@@ -1,8 +1,36 @@
+# import gradio as gr
+#
+# def greet(name):
+#     return "Hello " + name + "!!"
+#
+# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+# demo.launch()
+#
+
 import gradio as gr
+from sklearn.neighbors import KNeighborsClassifier
+import numpy as np
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Training data
+X = np.array([[1, 2], [2, 3], [3, 1], [6, 5], [7, 7], [8, 6]])
+y = np.array([0, 0, 0, 1, 1, 1])
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Training the model
+model = KNeighborsClassifier(n_neighbors=3)
+model.fit(X, y)
+
+# Define the prediction function
+def classify_point(x, y):
+    prediction = model.predict([[x, y]])
+    return "Class " + str(prediction[0])
 
+# Create a Gradio interface
+demo = gr.Interface(
+    fn=classify_point,
+    inputs=["number", "number"],
+    outputs="text",
+    description="Predict the class of a point based on its coordinates using K-Nearest Neighbors"
+)
+
+# Launch the app
+demo.launch()