from functools import partial import gradio as gr import src.constants as constants from src.details import update_subtasks_component, update_load_details_component, load_details_dataframes, \ display_details, update_sample_idx_component, clear_details, update_task_description_component, \ display_loading_message_for_details from src.results import update_load_results_component, \ load_results_dataframes, display_results, update_tasks_component, clear_results, \ sort_result_paths_per_model, fetch_result_paths, display_loading_message_for_results # if __name__ == "__main__": result_paths_per_model = sort_result_paths_per_model(fetch_result_paths()) load_results_dataframes = partial(load_results_dataframes, result_paths_per_model=result_paths_per_model) with gr.Blocks(fill_height=True, fill_width=True) as demo: gr.HTML("

Compare Results of the 🤗 Open LLM Leaderboard

") gr.HTML("

Select 2 models to load and compare their results

") gr.HTML("

⚠ This demo is a beta version and may contain bugs, performance issues, incomplete features, or unexpected behavior. We appreciate your understanding and welcome any feedback through the Community tab to help improve the final product.

") gr.Markdown("Compare Results of the 🤗 [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard-old/open_llm_leaderboard). " "Check out the [documentation](https://huggingface.co/docs/leaderboards/open_llm_leaderboard/about) 📄 to find explanations on the evaluations used, their configuration parameters and details on the input/outputs for the models." ) with gr.Row(): with gr.Column(): model_id_1 = gr.Dropdown(choices=list(result_paths_per_model.keys()), label="Models") dataframe_1 = gr.Dataframe(visible=False) with gr.Column(): model_id_2 = gr.Dropdown(choices=list(result_paths_per_model.keys()), label="Models") dataframe_2 = gr.Dataframe(visible=False) with gr.Row(): with gr.Tab("Results"): load_results_btn = gr.Button("Load", interactive=False) clear_results_btn = gr.Button("Clear") results_task = gr.Radio( ["All"] + list(constants.TASKS.values()), label="Tasks", info="Evaluation tasks to be displayed", value="All", visible=False, ) results_task_description = gr.Textbox( label="Task Description", lines=3, visible=False, ) results = gr.HTML() with gr.Tab("Configs"): load_configs_btn = gr.Button("Load", interactive=False) clear_configs_btn = gr.Button("Clear") configs_task = gr.Radio( ["All"] + list(constants.TASKS.values()), label="Tasks", info="Evaluation tasks to be displayed", value="All", visible=False, ) configs_task_description = gr.Textbox( label="Task Description", lines=3, visible=False, ) configs = gr.HTML() with gr.Tab("Details"): details_task = gr.Radio( list(value for value in constants.TASKS.values() if value[1] != "leaderboard_gpqa"), label="Tasks", info="Evaluation tasks to be loaded", interactive=True, ) details_task_description = gr.Textbox( label="Task Description", lines=3, ) subtask = gr.Radio( # constants.SUBTASKS.get(details_task.value), label="Subtasks", info="Evaluation subtasks to be loaded (choose one of the Tasks above)", ) load_details_btn = gr.Button("Load Details", interactive=False) clear_details_btn = gr.Button("Clear Details") sample_idx = gr.Number( label="Sample Index", info="Index of the sample to be displayed", value=0, minimum=0, visible=False ) details = gr.HTML() details_dataframe_1 = gr.Dataframe(visible=False) details_dataframe_2 = gr.Dataframe(visible=False) details_dataframe = gr.DataFrame(visible=False) gr.on( triggers=[model_id_1.input, model_id_2.input], fn=update_load_results_component, outputs=[load_results_btn, load_configs_btn], ) gr.on( triggers=[load_results_btn.click, load_configs_btn.click], fn=display_loading_message_for_results, outputs=[results, configs], ).then( fn=load_results_dataframes, inputs=[model_id_1, model_id_2], outputs=[dataframe_1, dataframe_2], ).then( fn=update_tasks_component, outputs=[results_task, configs_task], ) # Synchronize the results_task and configs_task radio buttons results_task.input(fn=lambda task: task, inputs=results_task, outputs=configs_task) configs_task.input(fn=lambda task: task, inputs=configs_task, outputs=results_task) # Update task descriptions results_task.change( fn=update_task_description_component, inputs=results_task, outputs=results_task_description, ).then( fn=update_task_description_component, inputs=results_task, outputs=configs_task_description, ) # Display results gr.on( triggers=[dataframe_1.change, dataframe_2.change, results_task.change], fn=display_results, inputs=[results_task, dataframe_1, dataframe_2], outputs=[results, configs], ) gr.on( triggers=[clear_results_btn.click, clear_configs_btn.click], fn=clear_results, outputs=[model_id_1, model_id_2, dataframe_1, dataframe_2, load_results_btn, load_configs_btn, results_task, configs_task], ) # DETAILS: details_task.change( fn=update_task_description_component, inputs=details_task, outputs=details_task_description, ).then( fn=update_subtasks_component, inputs=details_task, outputs=subtask, ) gr.on( triggers=[model_id_1.input, model_id_2.input, subtask.input, details_task.input], fn=update_load_details_component, inputs=[model_id_1, model_id_2, subtask], outputs=load_details_btn, ) load_details_btn.click( fn=display_loading_message_for_details, outputs=details, ).then( fn=load_details_dataframes, inputs=[subtask, model_id_1, model_id_2], outputs=[details_dataframe_1, details_dataframe_2], ).then( fn=update_sample_idx_component, inputs=[details_dataframe_1, details_dataframe_2], outputs=sample_idx, ) gr.on( triggers=[details_dataframe_1.change, details_dataframe_2.change, sample_idx.change], fn=display_details, inputs=[sample_idx, details_dataframe_1, details_dataframe_2], outputs=details, ) clear_details_btn.click( fn=clear_details, outputs=[model_id_1, model_id_2, details_dataframe_1, details_dataframe_2, details_task, subtask, load_details_btn, sample_idx], ) demo.launch()