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| 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() |