Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+import joblib
+
+# Load the model and label encoder
+model = joblib.load("soil.pkl")
+label_encoder = joblib.load("label_encoder.pkl")
+
+def predict_crop(N, P, K, temperature, humidity, ph, rainfall):
+    input_data = [[N, P, K, temperature, humidity, ph, rainfall]]
+    prediction = model.predict(input_data)
+    crop = label_encoder.inverse_transform(prediction)[0]
+    return f"Recommended Crop: {crop}"
+
+demo = gr.Interface(
+    fn=predict_crop,
+    inputs=[
+        gr.Number(label="Nitrogen"),
+        gr.Number(label="Phosphorus"),
+        gr.Number(label="Potassium"),
+        gr.Number(label="Temperature (°C)"),
+        gr.Number(label="Humidity (%)"),
+        gr.Number(label="pH"),
+        gr.Number(label="Rainfall (mm)")
+    ],
+    outputs="text",
+    title="Crop Recommendation System",
+    description="Enter your soil and weather data to get a crop suggestion!"
+)
+
+demo.launch()