Update app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import pickle
+import numpy as np
+
+# Load the trained model
+with open("random_forest_model.pkl", "rb") as file:
+    model = pickle.load(file)
+
+# Prediction function
+def predict_rainfall(temperature, humidity, cloud, sunshine, wind_direction):
+    features = np.array([[temperature, humidity, cloud, sunshine, wind_direction]])
+    prediction = model.predict(features)
+    message = "yes Rain is Possibble" if prediction[0] == 1 else "No Rain is not Possibble"
+    return message
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=predict_rainfall,
+    inputs=[
+        gr.Number(label="Temperature (°C)"),
+        gr.Number(label="Humidity (%)"),
+        gr.Number(label="Cloud (%)"),
+        gr.Number(label="Sunshine (hours)"),
+        gr.Number(label="Wind Direction (°)")
+    ],
+    outputs=gr.Text(label="Rain Prediction"),
+    title="Rainfall Prediction App",
+    description="Enter weather data to predict if rain is possible"
+)
+
+interface.launch()