Download app.py from Datadog/ARFBench: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/spaces/Datadog/ARFBench/resolve/main/app.py
- Command line
-
hf download hf://spaces/Datadog/ARFBench/app.py
-
curl -L -o app.py https://huggingface.co/spaces/Datadog/ARFBench/resolve/main/app.py
4.35 kB
| 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() | |