Update app.py

app.py

@@ -11,12 +11,11 @@ def get_crop_recommendation(soil_type, climate, history):
     }
     return pd.DataFrame(recommendations)
 
-def chat_response(message, history):
-    # Simple chat handler (connect to your LLM)
-    response = f"Agricultural Assistant: I recommend considering {get_crop_recommendation('Loam', 'Tropical', '').iloc[0]['recommended_crops'][0]} for your conditions."
+def analyze_conditions(query, history):
+    # Condition analysis handler (connect to your LLM)
+    response = f"🌱 CropAI Analysis: Optimal cultivation patterns suggest {get_crop_recommendation('Loam', 'Tropical', '').iloc[0]['recommended_crops'][0]} for these conditions."
     return response
 
-
 with gr.Blocks(theme=gr.themes.Soft(), title="CropSeek LLM") as demo:
     gr.HTML("""
     <div style="text-align:center">
@@ -25,28 +24,59 @@ with gr.Blocks(theme=gr.themes.Soft(), title="CropSeek LLM") as demo:
     </div>
     """)
     
-    gr.Markdown("### AI-Powered Crop Recommendation System")
-    
-    with gr.Tab("Chat Interface"):
-        chatbot = gr.Chatbot(height=400)
-        msg = gr.Textbox(label="Ask about crops...")
-        msg.submit(chat_response, [msg, chatbot], [msg, chatbot])
+    gr.Markdown("### 🌾 AI-Driven Crop Optimization System")
     
-    with gr.Tab("Data Analysis"):
-        file_input = gr.File(label="Upload Farm Data (CSV)")
+    with gr.Tab("🌱 Field Analysis Console"):
         with gr.Row():
-            soil_dd = gr.Dropdown(["Loamy", "Clay", "Sandy"], label="Soil Type")
-            climate_dd = gr.Dropdown(["Tropical", "Temperate", "Arid"], label="Climate Zone")
-        analyze_btn = gr.Button("Analyze Conditions")
-        results = gr.Dataframe(headers=["Parameter", "Value"], interactive=False)
+            with gr.Column(scale=2):
+                analysis_log = gr.Chatbot(
+                    label="Crop Diagnosis History",
+                    avatar_images=("🧑🌾", "🤖"),
+                    height=400
+                )
+            with gr.Column(scale=1):
+                field_input = gr.Textbox(
+                    label="Describe Soil & Climate Conditions:",
+                    placeholder="e.g. 'Clay soil in tropical climate with moderate rainfall...'"
+                )
+                analyze_btn = gr.Button("🌦️ Analyze Agricultural Patterns", variant="primary")
         
         analyze_btn.click(
+            analyze_conditions, 
+            [field_input, analysis_log], 
+            [field_input, analysis_log]
+        )
+    
+    with gr.Tab("📈 Yield Optimization Advisor"):
+        with gr.Row():
+            soil_dd = gr.Dropdown(
+                ["Loamy", "Clay", "Sandy"], 
+                label="Soil Composition",
+                info="Select predominant soil type"
+            )
+            climate_dd = gr.Dropdown(
+                ["Tropical", "Temperate", "Arid"], 
+                label="Climate Profile",
+                info="Select regional climate pattern"
+            )
+        farm_data = gr.File(
+            label="Upload Field Sensor Data (CSV)",
+            file_types=[".csv"]
+        )
+        simulate_btn = gr.Button("🚜 Generate Cultivation Plan", variant="primary")
+        results = gr.Dataframe(
+            headers=["Parameter", "Value", "Recommendation"],
+            interactive=False,
+            wrap=True,
+            datatype=["str", "number", "str"]
+        )
+        
+        simulate_btn.click(
             fn=get_crop_recommendation,
-            inputs=[soil_dd, climate_dd, file_input],
+            inputs=[soil_dd, climate_dd, farm_data],
             outputs=results
         )
 
-    gr.Markdown("---\n*Demo for Preview | v1.2*")
-
-demo.launch()
+    gr.Markdown("---\n*Agricultural Intelligence Platform | v2.1*")
 
+demo.launch()