import gradio as gr
from utils.model_loader import load_model_and_config, load_ui_text
from tabs.single_prediction import create_single_prediction_tab
from tabs.batch_processing import create_batch_processing_tab

# loadign model
config = load_model_and_config()
intro_md, about_md = load_ui_text()

model = config['model']
class_names = config['class_names']
disease_db = config['disease_db']
device = config['device']


# Custom CSS
custom_css = """
.gradio-container {
    font-family: 'Arial', sans-serif;
}
.output-class {
    font-size: 16px;
}
"""

# Create Gradio Interface
with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
    
    # Intro
    gr.Markdown(intro_md)
    
    # Tab 1: Single Image Prediction
    with gr.Tab("Single Image Prediction"):
        create_single_prediction_tab(model, class_names, disease_db, device)
    
    # Tab 2: Batch Processing
    with gr.Tab("Batch Processing"):
        create_batch_processing_tab(model, class_names, device)
    
    # Tab 3: About
    with gr.Tab("About"):
        gr.Markdown(about_md)


demo.launch(server_name="0.0.0.0", server_port=7860)