app.py

import gradio as gr
import pandas as pd
from mock_models.crop_model import MockCropModel
from mock_models.chat_engine import AgriculturalChatEngine

# Initialize mock models
crop_model = MockCropModel()
chat_engine = AgriculturalChatEngine()

# ----------------------
# Core functionality
# ----------------------
def get_crop_recommendation(soil_type, climate, file_input):
    """Process inputs and generate recommendations"""
    df = crop_model.predict(soil_type, climate)
    
    if file_input:
        try:
            uploaded_data = pd.read_csv(file_input.name)
            df['Uploaded Data'] = uploaded_data.mean().to_dict()
        except:
            pass
            
    return df

def handle_chat(query, history):
    """Process chat queries"""
    response = chat_engine.generate_response(query)
    history.append((query, response))
    return history, ""

# ----------------------
# UI Components
# ----------------------
with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald"), title="CropSeek-LLM") as demo:
    # ----------------------
    # Enhanced Header
    # ----------------------
    gr.HTML("""
    <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:100px; filter: drop-shadow(2px 2px 4px #00000060);">
    </div>
    """)
    
    # Chat Interface
    with gr.Tab("🗣️ Agronomist"):
        chatbot = gr.Chatbot(height=400, label="Crop Insight Engine")
        chat_input = gr.Textbox(placeholder="Input agricultural parameters...Ask about crops, pests, or farming practices...")
        chat_input.submit(handle_chat, [chat_input, chatbot], [chatbot, chat_input])
    
    # Data Analysis Interface
    with gr.Tab("📊 Crop Advisor"):
        with gr.Row():
            soil_type = gr.Dropdown(
                ["Loamy", "Clay", "Sandy"],
                label="Soil Type",
                value="Loamy"
            )
            climate_zone = gr.Dropdown(
                ["Tropical", "Temperate", "Arid"],
                label="Climate Zone",
                value="Tropical"
            )
        upload_btn = gr.UploadButton("📁 Upload Soil Analysis (CSV)", file_types=[".csv"])
        analyze_btn = gr.Button("🚜 Analyze Conditions", variant="primary")
        results = gr.Dataframe(
            headers=["Crop", "Confidence", "Soil Type", "Climate Zone"],
            interactive=False,
            wrap=True
        )
        
        analyze_btn.click(
            fn=get_crop_recommendation,
            inputs=[soil_type, climate_zone, upload_btn],
            outputs=results
        )
    
    # Footer
    gr.Markdown("---")
    with gr.Row():
        gr.Markdown("**System Status:** ✅ Operational")
        gr.Markdown("**Version:** 1.0.0")
        gr.Markdown("**Data Updated:** 2025-05-15")

# ----------------------
# Launch Application
# ----------------------
if __name__ == "__main__":
    demo.launch()