| import gradio as gr |
| from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns |
|
|
| from src.about import ( |
| CITATION_BUTTON_LABEL, |
| CITATION_BUTTON_TEXT, |
| INTRODUCTION_TEXT, |
| LLM_BENCHMARKS_TEXT, |
| TITLE, |
| ) |
| from src.display.css_html_js import custom_css |
| from src.display.utils import ( |
| CATEGORY_ACCURACY_COLS, |
| CATEGORY_F1_COLS, |
| OVERALL_TIER_COLS, |
| CategoryAccuracyColumn, |
| CategoryF1Column, |
| OverallTierColumn, |
| fields, |
| ) |
| from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN |
| from src.populate import get_leaderboard_df |
|
|
|
|
| def restart_space(): |
| API.restart_space(repo_id=REPO_ID) |
|
|
|
|
| OVERALL_TIER_LEADERBOARD_DF = get_leaderboard_df( |
| EVAL_RESULTS_PATH + "/ARFBench_leaderboard.csv", |
| EVAL_REQUESTS_PATH, |
| OVERALL_TIER_COLS, |
| OVERALL_TIER_COLS, |
| sort_by="accuracy", |
| ) |
|
|
| CATEGORY_F1_LEADERBOARD_DF = get_leaderboard_df( |
| EVAL_RESULTS_PATH + "/ARFBench_leaderboard_category_f1.csv", |
| EVAL_REQUESTS_PATH, |
| CATEGORY_F1_COLS, |
| CATEGORY_F1_COLS, |
| sort_by="overall_f1", |
| ) |
|
|
| CATEGORY_ACCURACY_LEADERBOARD_DF = get_leaderboard_df( |
| EVAL_RESULTS_PATH + "/ARFBench_leaderboard_category_accuracy.csv", |
| EVAL_REQUESTS_PATH, |
| CATEGORY_ACCURACY_COLS, |
| CATEGORY_ACCURACY_COLS, |
| sort_by="overall_accuracy", |
| ) |
|
|
|
|
| def init_custom_leaderboard(dataframe, column_class, filter_column_name, filter_label): |
| if dataframe is None or dataframe.empty: |
| raise ValueError("Leaderboard DataFrame is empty or None.") |
| return Leaderboard( |
| value=dataframe, |
| datatype=[c.type for c in fields(column_class)], |
| select_columns=SelectColumns( |
| default_selection=[c.name for c in fields(column_class) if c.displayed_by_default], |
| cant_deselect=[c.name for c in fields(column_class) if c.never_hidden], |
| label="Select Columns to Display:", |
| ), |
| search_columns=[column_class.model.name], |
| hide_columns=[c.name for c in fields(column_class) if c.hidden], |
| filter_columns=[ |
| ColumnFilter( |
| filter_column_name, |
| type="slider", |
| min=0, |
| max=100, |
| label=filter_label, |
| ), |
| ], |
| bool_checkboxgroup_label="Hide models", |
| interactive=False, |
| ) |
|
|
|
|
| demo = gr.Blocks(css=custom_css) |
| with demo: |
| gr.HTML(TITLE) |
| gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") |
|
|
| with gr.Tabs(elem_classes="tab-buttons") as tabs: |
| with gr.TabItem("π
ARFBench Leaderboard", elem_id="arfbench-tab-table", id=0): |
| with gr.Tabs(selected=0): |
| with gr.TabItem("Overall + Tier (Default)", id=0): |
| leaderboard_overall_tier = init_custom_leaderboard( |
| OVERALL_TIER_LEADERBOARD_DF, |
| OverallTierColumn, |
| OverallTierColumn.overall_f1.name, |
| "Overall F1 score", |
| ) |
|
|
| with gr.TabItem("Per-Category F1", id=1): |
| leaderboard_category_f1 = init_custom_leaderboard( |
| CATEGORY_F1_LEADERBOARD_DF, |
| CategoryF1Column, |
| CategoryF1Column.overall_f1.name, |
| "Overall F1 score", |
| ) |
|
|
| with gr.TabItem("Per-Category Accuracy", id=2): |
| leaderboard_category_accuracy = init_custom_leaderboard( |
| CATEGORY_ACCURACY_LEADERBOARD_DF, |
| CategoryAccuracyColumn, |
| CategoryAccuracyColumn.overall_accuracy.name, |
| "Overall Accuracy score", |
| ) |
|
|
| with gr.TabItem("π About", elem_id="about-tab-table", id=1): |
| gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text") |
|
|
| with gr.Row(): |
| with gr.Accordion("π Citation", open=False): |
| citation_button = gr.Textbox( |
| value=CITATION_BUTTON_TEXT, |
| label=CITATION_BUTTON_LABEL, |
| lines=20, |
| elem_id="citation-button", |
| show_copy_button=True, |
| ) |
|
|
| scheduler = None |
| demo.queue(default_concurrency_limit=40) |
| if __name__ == "__main__": |
| demo.launch() |
|
|