import gradio as gr
import pandas as pd


#Models:
# IlyaGusev/saiga_llama3_8b
# Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24
# TinyLlama
# Google-gemma-2-27b-it
# mistralai/Mistral-Nemo-Instruct-2407
# Vikhrmodels/Vikhr-Qwen-2.5-0.5b-Instruct


benchmark_data = {
    'Model': ['IlyaGusev/saiga_llama3_8b', 'Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24', "TinyLlama", 'Google-gemma-2-27b-it', 'mistralai/Mistral-Nemo-Instruct-2407', 'Vikhrmodels/Vikhr-Qwen-2.5-0.5b-Instruct'],
    'Creativity Score': [78.5, 82.3, 85.7, 83.1, 85.6, 76.5, ],
    'Coherence Score': [75.2, 80.1, 84.3, 81.9, 88.5, 76.6],
    'Diversity Score': [25.3, 27.8, 31.2, 29.5, 28.4, 24.6]
}

def display_results():
    df = pd.DataFrame(benchmark_data)
    return df

# Create the interface
with gr.Blocks() as demo:
    gr.Markdown("# Model Benchmark Results")
    
    # Display results in a DataFrame
    output = gr.Dataframe(
        headers=["Model", "Creativity Score", "Coherence Score", "Diversity Score"],
        interactive=False
    )
    
    # Button to refresh/display results
    refresh_btn = gr.Button("Show Results")
    refresh_btn.click(fn=display_results, outputs=output)

if __name__ == "__main__":
    demo.launch()