Update app.py

app.py

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+import gradio as gr
+import requests
+
+# Define the function to call the model hosted on Hugging Face
+def get_fertilizer_recommendation(crop_name, target_yield, field_size, ph_water, organic_carbon, total_nitrogen, phosphorus, potassium, soil_moisture):
+    # Replace this with the URL of your Hugging Face model
+    url = "https://api-inference.huggingface.co/models/your-model-name"
+    headers = {"Authorization": "Bearer YOUR_HUGGING_FACE_API_KEY"}
+
+    # Define the input payload
+    payload = {
+        'Crop Name': [crop_name],
+        'Target Yield': [target_yield],
+        'Field Size': [field_size],
+        'pH (water)': [ph_water],
+        'Organic Carbon': [organic_carbon],
+        'Total Nitrogen': [total_nitrogen],
+        'Phosphorus (M3)': [phosphorus],
+        'Potassium (exch.)': [potassium],
+        'Soil moisture': [soil_moisture]
+    }
+
+    # Make the request to the model
+    response = requests.post(url, headers=headers, json=payload)
+    result = response.json()
+
+    # Extract the relevant output fields
+    output = f"""
+    Predicted Fertilizer Requirements:
+    Nitrogen (N) Need: {result['Nitrogen (N) Need']}
+    Phosphorus (P2O5) Need: {result['Phosphorus (P2O5) Need']}
+    Potassium (K2O) Need: {result['Potassium (K2O) Need']}
+    Organic Matter Need: {result['Organic Matter Need']}
+    Lime Need: {result['Lime Need']}
+    Lime Application - Requirement: {result['Lime Application - Requirement']}
+    Organic Matter Application - Requirement: {result['Organic Matter Application - Requirement']}
+    1st Application - Requirement (1): {result['1st Application - Requirement (1)']}
+    1st Application - Requirement (2): {result['1st Application - Requirement (2)']}
+    Lime Application - Instruction: {result['Lime Application - Instruction']}
+    Lime Application: {result['Lime Application']}
+    Organic Matter Application - Instruction: {result['Organic Matter Application - Instruction']}
+    Organic Matter Application: {result['Organic Matter Application']}
+    1st Application: {result['1st Application']}
+    1st Application - Type fertilizer (1): {result['1st Application - Type fertilizer (1)']}
+    1st Application - Type fertilizer (2): {result['1st Application - Type fertilizer (2)']}
+    """
+    return output
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=get_fertilizer_recommendation,
+    inputs=[
+        gr.inputs.Textbox(label="Crop Name"),
+        gr.inputs.Number(label="Target Yield"),
+        gr.inputs.Number(label="Field Size"),
+        gr.inputs.Number(label="pH (water)"),
+        gr.inputs.Number(label="Organic Carbon"),
+        gr.inputs.Number(label="Total Nitrogen"),
+        gr.inputs.Number(label="Phosphorus (M3)"),
+        gr.inputs.Number(label="Potassium (exch.)"),
+        gr.inputs.Number(label="Soil moisture"),
+    ],
+    outputs="text",
+    title="Fertilizer Application Advisor",
+    description="Input the details of your field and get fertilizer recommendations."
+)
+
+# Launch the interface
+interface.launch()