Create app.py

app.py

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+import gradio as gr
+import pickle
+import pandas as pd
+import os
+
+# Load the Rainfall Prediction model
+working_dir = os.path.dirname(os.path.abspath(__file__))
+rainfall_model = pickle.load(open(f'{working_dir}/Rainfall_Ridge.sav', 'rb'))
+
+# Define all subdivisions
+subdivisions = [
+    'ANDAMAN & NICOBAR ISLANDS', 'ARUNACHAL PRADESH', 'ASSAM & MEGHALAYA', 'NAGA MANI MIZO TRIPURA',
+    'SUB HIMALAYAN WEST BENGAL & SIKKIM', 'GANGETIC WEST BENGAL', 'ORISSA', 'JHARKHAND', 'BIHAR',
+    'EAST UTTAR PRADESH', 'WEST UTTAR PRADESH', 'UTTARAKHAND', 'HARYANA DELHI & CHANDIGARH', 'PUNJAB',
+    'HIMACHAL PRADESH', 'JAMMU & KASHMIR', 'WEST RAJASTHAN', 'EAST RAJASTHAN', 'WEST MADHYA PRADESH',
+    'EAST MADHYA PRADESH', 'GUJARAT REGION', 'SAURASHTRA & KUTCH', 'KONKAN & GOA', 'MADHYA MAHARASHTRA',
+    'MATATHWADA', 'VIDARBHA', 'CHHATTISGARH', 'COASTAL ANDHRA PRADESH', 'TELANGANA', 'RAYALSEEMA',
+    'TAMIL NADU', 'COASTAL KARNATAKA', 'NORTH INTERIOR KARNATAKA', 'SOUTH INTERIOR KARNATAKA', 'KERALA',
+    'LAKSHADWEEP'
+]
+
+def predict_rainfall(subdivision, year, may, jun, jul, aug, sep):
+    """Predict rainfall based on user inputs."""
+    try:
+        # Create a DataFrame for prediction
+        rainfall_input = {
+            'SUBDIVISION': [subdivision],
+            'YEAR': [year],
+            'MAY': [may],
+            'JUN': [jun],
+            'JUL': [jul],
+            'AUG': [aug],
+            'SEP': [sep]
+        }
+        rainfall_input_df = pd.DataFrame(rainfall_input)
+
+        # Ensure all rainfall inputs are provided
+        if all(rainfall_input_df.iloc[0, 2:]):
+            rainfall_prediction = rainfall_model.predict(rainfall_input_df)
+            return f"Predicted Rainfall: {rainfall_prediction[0]:.2f} mm"
+        else:
+            return "Error: Please provide valid values for all rainfall inputs."
+    except Exception as e:
+        return f"Error during prediction: {str(e)}"
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=predict_rainfall,
+    inputs=[
+        gr.Dropdown(choices=subdivisions, label="Subdivision"),
+        gr.Number(label="Year", value=2023),
+        gr.Number(label="May Rainfall (mm)", value=0.0),
+        gr.Number(label="June Rainfall (mm)", value=0.0),
+        gr.Number(label="July Rainfall (mm)", value=0.0),
+        gr.Number(label="August Rainfall (mm)", value=0.0),
+        gr.Number(label="September Rainfall (mm)", value=0.0)
+    ],
+    outputs=gr.Textbox(label="Prediction Result"),
+    title="Rainfall Prediction",
+    description="Provide inputs for the selected subdivision, year, and monthly rainfall amounts to predict the total rainfall."
+)
+
+if __name__ == "__main__":
+    interface.launch()
+