Update app.py

app.py

@@ -15,12 +15,13 @@ def create_synthetic_dataset():
         'Vizianagaram', 'West Godavari', 'YSR Kadapa'
     ]
     
-    # Common crops in Andhra Pradesh
+    # Common crops in Andhra Pradesh (including new crops)
     crops = [
-        'Rice', 'Maize', 'Cotton', 'Groundnut', 'Red Gram (Toor Dal)',
+        'Rice', 'Maize', 'Corn', 'Cotton', 'Groundnut', 'Red Gram (Toor Dal)',
         'Green Gram (Moong Dal)', 'Black Gram (Urad Dal)', 'Sugarcane',
-        'Chilli', 'Turmeric', 'Tobacco', 'Mango', 'Banana', 'Coconut',
-        'Cashew', 'Soybean', 'Sunflower', 'Jowar (Sorghum)', 'Bajra (Pearl Millet)'
+        'Chilli', 'Pepper', 'Turmeric', 'Tobacco', 'Sweet Potato', 'Mango', 
+        'Banana', 'Coconut', 'Cashew', 'Soybean', 'Sunflower', 
+        'Jowar (Sorghum)', 'Bajra (Pearl Millet)'
     ]
     
     # Months
@@ -75,6 +76,18 @@ def create_synthetic_dataset():
         if crop == 'Rice' and data['Rainfall'][i] < 100:
             data['Suitability'][i] = 0
         
+        # Corn needs moderate water and warm temperature
+        if crop == 'Corn' and (data['Rainfall'][i] < 50 or data['Temperature'][i] < 20):
+            data['Suitability'][i] = 0
+        
+        # Pepper needs warm, humid conditions
+        if crop == 'Pepper' and (data['Temperature'][i] < 20 or data['Rainfall'][i] < 100):
+            data['Suitability'][i] = 0
+        
+        # Sweet Potato grows well in warm conditions with moderate rainfall
+        if crop == 'Sweet Potato' and (data['Temperature'][i] < 20 or data['Rainfall'][i] > 250):
+            data['Suitability'][i] = 0
+        
         # Groundnut grows well in Anantapur
         if crop == 'Groundnut' and district == 'Anantapur':
             data['Suitability'][i] = 1
@@ -86,6 +99,18 @@ def create_synthetic_dataset():
         # Chilli grows well in Guntur
         if crop == 'Chilli' and district == 'Guntur':
             data['Suitability'][i] = 1
+        
+        # Corn grows well in Krishna and Guntur
+        if crop == 'Corn' and district in ['Krishna', 'Guntur', 'West Godavari']:
+            data['Suitability'][i] = 1
+        
+        # Pepper grows well in coastal and hilly areas
+        if crop == 'Pepper' and district in ['Visakhapatnam', 'Srikakulam', 'Vizianagaram']:
+            data['Suitability'][i] = 1
+        
+        # Sweet Potato grows well in various districts
+        if crop == 'Sweet Potato' and district in ['East Godavari', 'West Godavari', 'Krishna']:
+            data['Suitability'][i] = 1
     
     df = pd.DataFrame(data)
     return df, crops, districts, months
@@ -108,7 +133,7 @@ def train_model(df):
 
 model = train_model(df)
 
-# Crop information and precautions
+# Crop information and precautions (updated with new crops)
 crop_info = {
     'Rice': {
         'description': 'Staple food crop requiring abundant water',
@@ -128,6 +153,16 @@ crop_info = {
             'Watch for fall armyworm infestation'
         ]
     },
+    'Corn': {
+        'description': 'Sweet corn variety popular for direct consumption',
+        'precautions': [
+            'Plant in well-drained loamy soil',
+            'Maintain spacing of 60x25 cm',
+            'Harvest when silks turn brown and dry',
+            'Control corn earworm and aphids',
+            'Irrigate regularly during grain filling stage'
+        ]
+    },
     'Cotton': {
         'description': 'Important cash crop known as "white gold"',
         'precautions': [
@@ -191,6 +226,16 @@ crop_info = {
             'Harvest at color break stage'
         ]
     },
+    'Pepper': {
+        'description': 'Black pepper, important spice crop',
+        'precautions': [
+            'Plant in well-drained red loamy soil',
+            'Provide support with standards or trellis',
+            'Control quick wilt and pollu beetle',
+            'Harvest when berries turn orange-red',
+            'Provide shade during initial growth'
+        ]
+    },
     'Turmeric': {
         'description': 'Important spice crop with medicinal value',
         'precautions': [
@@ -209,6 +254,16 @@ crop_info = {
             'Practice crop rotation'
         ]
     },
+    'Sweet Potato': {
+        'description': 'Nutritious root vegetable rich in vitamins',
+        'precautions': [
+            'Plant in well-drained sandy loam soil',
+            'Use vine cuttings for propagation',
+            'Control sweet potato weevil',
+            'Harvest when leaves turn yellow',
+            'Cure properly before storage'
+        ]
+    },
     'Mango': {
         'description': 'Important fruit crop of Andhra Pradesh',
         'precautions': [
@@ -281,7 +336,7 @@ crop_info = {
     }
 }
 
-# District-wise climate information
+# District-wise climate information (unchanged)
 district_climate = {
     'Anantapur': {
         'description': 'Hot and dry climate with low rainfall',
@@ -363,7 +418,7 @@ district_climate = {
     }
 }
 
-# Prediction function
+# Prediction function (unchanged)
 def predict_crop(district, month, crop_choice=None):
     # Get current temperature and rainfall based on district and month
     temp = df[(df['District'] == district) & (df['Month'] == month)]['Temperature'].mean()
@@ -460,13 +515,12 @@ def get_alternative_crops(district, month):
     crop_scores.sort(key=lambda x: x[1], reverse=True)
     return [crop for crop, score in crop_scores if score > 0.7]
 
-# Custom CSS for styling
+# Custom CSS for styling (unchanged)
 css = """
 .gradio-container {
     font-family: 'Poppins', sans-serif;
     background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
 }
-
 .title {
     text-align: center;
     color: #2c3e50;
@@ -477,14 +531,12 @@ css = """
     -webkit-background-clip: text;
     -webkit-text-fill-color: transparent;
 }
-
 .description {
     text-align: center;
     color: #4a5568;
     margin-bottom: 30px;
     font-size: 16px;
 }
-
 .input-section {
     background: white;
     padding: 20px;
@@ -492,14 +544,12 @@ css = """
     box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
     margin-bottom: 20px;
 }
-
 .input-label {
     font-weight: 500;
     color: #2d3748;
     margin-bottom: 8px;
     display: block;
 }
-
 .output-section {
     background: white;
     padding: 25px;
@@ -510,7 +560,6 @@ css = """
     line-height: 1.6;
     white-space: pre-wrap;
 }
-
 .output-title {
     color: #2c3e50;
     font-weight: 600;
@@ -519,7 +568,6 @@ css = """
     border-bottom: 2px solid #e2e8f0;
     padding-bottom: 8px;
 }
-
 .btn-primary {
     background: linear-gradient(90deg, #4b6cb7 0%, #182848 100%);
     border: none;
@@ -531,12 +579,10 @@ css = """
     transition: all 0.3s ease;
     box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
 }
-
 .btn-primary:hover {
     transform: translateY(-2px);
     box-shadow: 0 7px 14px rgba(0, 0, 0, 0.1);
 }
-
 .select-dropdown, .text-input {
     width: 100%;
     padding: 12px;
@@ -545,28 +591,23 @@ css = """
     font-size: 16px;
     transition: all 0.3s ease;
 }
-
 .select-dropdown:focus, .text-input:focus {
     border-color: #4b6cb7;
     box-shadow: 0 0 0 3px rgba(75, 108, 183, 0.2);
     outline: none;
 }
-
 .footer {
     text-align: center;
     margin-top: 30px;
     color: #718096;
     font-size: 14px;
 }
-
 .success {
     color: #2e7d32;
 }
-
 .warning {
     color: #d32f2f;
 }
-
 .recommendation {
     background: #f0f4f8;
     padding: 15px;
@@ -574,7 +615,6 @@ css = """
     margin-top: 15px;
     border-left: 4px solid #4b6cb7;
 }
-
 .crop-image {
     max-width: 100%;
     border-radius: 8px;