Update app.py

app.py

@@ -1,82 +1,171 @@
 import gradio as gr
 import pandas as pd
+from datetime import datetime
 
+# ----------------------
+# Mock Model Components
+# ----------------------
 def get_crop_recommendation(soil_type, climate, history):
-    # Replace with your actual model inference logic
+    """Mock recommendation engine"""
     recommendations = {
-        "soil": soil_type,
-        "climate": climate,
-        "recommended_crops": ["Pepper", "Tomato", "Chilli"],
-        "confidence": [0.85, 0.76, 0.68]
+        "Parameter": ["Soil Type", "Climate Zone", "Top Crop", "Alternative 1", "Alternative 2"],
+        "Value": [soil_type, climate, "Pepper (0.85)", "Tomato (0.76)", "Chilli (0.68)"],
+        "Recommendation": [
+            "Optimal for root development",
+            "Ideal temperature range",
+            "High market demand",
+            "Good disease resistance",
+            "Drought tolerant"
+        ]
     }
     return pd.DataFrame(recommendations)
 
 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."
+    """Mock analysis engine"""
+    response = f"🌱 **CropAI Analysis**: Based on '{query}', optimal cultivation patterns suggest **Pepper** (85% confidence) followed by Tomato and Chilli. "
+    response += "Recommended practices: Drip irrigation with weekly pH monitoring."
     return response
 
-with gr.Blocks(theme=gr.themes.Soft(), title="CropSeek LLM") as demo:
+# ----------------------
+# UI Components
+# ----------------------
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald"), title="CropSeek AI") as demo:
+    # ----------------------
+    # Enhanced Header
+    # ----------------------
     gr.HTML("""
-    <div style="text-align:center">
+    <div style="text-align:center; background: linear-gradient(to right, #2c5f2d, #97bc62); padding: 20px; border-radius: 10px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);">
         <img src="https://huggingface.co/spaces/DARJYO/CropSeek-LLM/resolve/main/assets/logo.png" 
-             style="height:80px; margin-bottom:20px;">
+             style="height:100px; filter: drop-shadow(2px 2px 4px #00000060);">
+        <h1 style="color: white; margin: 10px 0; font-family: 'Arial Rounded MT Bold', sans-serif;">CropSeek AI</h1>
+        <h3 style="color: #fafafa; font-weight: 300;">Next-Gen Agricultural Intelligence Platform</h3>
     </div>
     """)
-    
-    gr.Markdown("### 🌾 AI-Driven Crop Optimization System")
-    
+
+    # ----------------------
+    # Main Analysis Interface
+    # ----------------------
     with gr.Tab("🌱 Field Analysis Console"):
         with gr.Row():
             with gr.Column(scale=2):
                 analysis_log = gr.Chatbot(
                     label="Crop Diagnosis History",
                     avatar_images=("🧑🌾", "🤖"),
-                    height=400
+                    height=450,
+                    bubble_full_width=False
                 )
+                
             with gr.Column(scale=1):
+                gr.Markdown("### 🌦️ Environmental Parameters")
                 field_input = gr.Textbox(
-                    label="Describe Soil & Climate Conditions:",
-                    placeholder="e.g. 'Clay soil in tropical climate with moderate rainfall...'"
+                    label="Describe Conditions:",
+                    placeholder="e.g. 'Clay soil in tropical climate with 1200mm rainfall...'",
+                    lines=3
                 )
-                analyze_btn = gr.Button("🌦️ Analyze Agricultural Patterns", variant="primary")
-        
+                
+                gr.Examples(
+                    examples=[
+                        ["Sandy loam soil with temperate climate and irrigation access"],
+                        ["Arid region with limited water resources and alkaline soil"],
+                        ["Volcanic soil in subtropical highland climate"]
+                    ],
+                    inputs=field_input,
+                    label="💡 Try Example Scenarios:"
+                )
+                
+                analyze_btn = gr.Button(
+                    "🔍 Analyze Agricultural Patterns", 
+                    variant="primary",
+                    size="lg"
+                )
+
         analyze_btn.click(
             analyze_conditions, 
             [field_input, analysis_log], 
             [field_input, analysis_log]
         )
-    
+
+    # ----------------------
+    # Data Analysis Interface
+    # ----------------------
     with gr.Tab("📈 Yield Optimization Advisor"):
         with gr.Row():
             soil_dd = gr.Dropdown(
-                ["Loamy", "Clay", "Sandy"], 
+                ["Loamy", "Clay", "Sandy", "Volcanic", "Peaty"],
                 label="Soil Composition",
-                info="Select predominant soil type"
+                info="USDA soil classification",
+                interactive=True
             )
             climate_dd = gr.Dropdown(
-                ["Tropical", "Temperate", "Arid"], 
+                ["Tropical", "Temperate", "Arid", "Mediterranean", "Continental"],
                 label="Climate Profile",
-                info="Select regional climate pattern"
+                info="Köppen climate classification",
+                interactive=True
             )
-        farm_data = gr.File(
-            label="Upload Field Sensor Data (CSV)",
-            file_types=[".csv"]
-        )
-        simulate_btn = gr.Button("🚜 Generate Cultivation Plan", variant="primary")
+            
+        with gr.Row():
+            farm_data = gr.File(
+                label="Upload Field Sensor Data (CSV)",
+                file_types=[".csv"],
+                height=50
+            )
+            simulate_btn = gr.Button(
+                "🚜 Generate Cultivation Plan", 
+                variant="primary",
+                size="lg"
+            )
+            
         results = gr.Dataframe(
             headers=["Parameter", "Value", "Recommendation"],
             interactive=False,
             wrap=True,
-            datatype=["str", "number", "str"]
+            datatype=["str", "markdown", "str"],
+            height=400
         )
-        
+
+        # ----------------------
+        # Data Validation
+        # ----------------------
+        @demo.load(inputs=farm_data, outputs=results)
+        def validate_data(file_input):
+            if file_input:
+                try:
+                    df = pd.read_csv(file_input.name)
+                    required_columns = ['pH', 'Nitrogen', 'Phosphorus', 'Potassium']
+                    if not all(col in df.columns for col in required_columns):
+                        raise ValueError("Missing required soil analysis columns")
+                    return df.head().style.set_properties(**{
+                        'background-color': '#f0f7e4',
+                        'color': '#2c5f2d',
+                        'border-color': '#97bc62'
+                    })
+                except Exception as e:
+                    raise gr.Error(f"⚠️ Data validation error: {str(e)}")
+            return pd.DataFrame()
+
         simulate_btn.click(
             fn=get_crop_recommendation,
             inputs=[soil_dd, climate_dd, farm_data],
             outputs=results
         )
 
-    gr.Markdown("---\n*Agricultural Intelligence Platform | v2.1*")
+    # ----------------------
+    # Footer & Status
+    # ----------------------
+    gr.Markdown("---")
+    with gr.Row():
+        gr.Markdown(f"**Last Updated:** {datetime.now().strftime('%Y-%m-%d %H:%M')}")
+        gr.Markdown("**System Status:** 🟢 Operational")
+        gr.Markdown("**Version:** 2.1.0")
+        
+    gr.Markdown("""
+    <div style="text-align: center; padding: 15px; background-color: #f8f9fa; border-radius: 8px; margin-top: 20px;">
+        <small>© 2023 CropSeek AI | Agricultural Intelligence Platform | Contact: [email protected]</small>
+    </div>
+    """)
 
-demo.launch()
+# ----------------------
+# Launch Application
+# ----------------------
+if __name__ == "__main__":
+    demo.launch()