awdawd

app.py

@@ -1,6 +1,7 @@
 import pandas as pd
 from sklearn.preprocessing import LabelEncoder
 import gradio as gr
+import json
 
 # Load data
 def load_data(file_path):
@@ -65,9 +66,9 @@ def get_fertilizer_recommendation(row, land_size_m2, fallow_years, thresholds, a
             total_amount = base_amount_per_m2 * land_size_m2 * (1 + 0.1 * fallow_years)
             fertilizer_amounts[nutrient_name] = round(total_amount, 2)
     if deficiencies:
-        return 'Fertilizer needed for'', '.join(deficiencies), fertilizer_amounts
+        return {'recommendation': f'Fertilizer needed for {", ".join(deficiencies)}', 'fertilizer_amounts': fertilizer_amounts}
     else:
-        return 'No deficiency, Manure Recommended', {}
+        return {'recommendation': 'No deficiency, Manure Recommended', 'fertilizer_amounts': {}}
 
 # Gradio application
 def gradio_application():
@@ -81,11 +82,11 @@ def gradio_application():
         def fertilizer_recommendation(soil_type_input, crop_type_input, land_size_m2, fallow_years):
             filtered_data = data[(data['Soil_type'] == soil_type_input) & (data['Crop_type'] == crop_type_input)]
             if filtered_data.empty:
-                return "No data available for the given soil type and crop type."
+                return json.dumps({'error': 'No data available for the given soil type and crop type.'})
             else:
                 row = filtered_data.iloc[0]
-                recommendation, amounts = get_fertilizer_recommendation(row, land_size_m2, fallow_years, thresholds, application_rates)
-                return f"Recommendation: {recommendation}\nFertilizer Amounts (in kg):\n" + "\n".join(f"{nutrient}: {amount} kg" for nutrient, amount in amounts.items())
+                recommendation = get_fertilizer_recommendation(row, land_size_m2, fallow_years, thresholds, application_rates)
+                return json.dumps(recommendation)
 
         demo = gr.Interface(
             fn=fertilizer_recommendation,
@@ -95,7 +96,7 @@ def gradio_application():
                 gr.Number(label="Land Size (m2)"),
                 gr.Number(label="Fallow Years")
             ],
-            outputs="text",
+            outputs="json",
             title="Fertilizer Recommendation App",
             description="Enter the soil type, crop type, land size, and fallow years to get a fertilizer recommendation."
         )