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| import gradio as gr | |
| from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter | |
| from pathlib import Path | |
| from utils import ABOUT_TEXT, SUBMIT_TEXT, custom_css, jsonl_to_dataframe, add_average_column_to_df, apply_markdown_format_for_columns, submit, PART_LOGO, sort_dataframe_by_column, tasks_and_metrics_table_markdown | |
| abs_path = Path(__file__).parent | |
| # Any pandas-compatible data | |
| leaderboard_df = jsonl_to_dataframe(str(abs_path / "leaderboard_data.jsonl")) | |
| average_column_name = "Average Score" | |
| columns_to_average = ["FarsTail-Pair-Classification", | |
| "MIRACL-Reranking", | |
| "Wikipedia-Multilingual-Reranking", | |
| "NeuCLIR2023-Retrieval", | |
| "MIRACL-Retrieval", | |
| "Wikipedia-Multilingual-Retrieval", | |
| "Massive-Intent-Classification", | |
| "Massive-Scenario-Classification", | |
| "Multilingual-Sentiment-Classification", | |
| "Persian-Food-Sentiment-Classification", | |
| ] | |
| all_columns = ["Model", average_column_name, "Precision", "#Params (M)", "Embedding Dimension", "Context Size"] + columns_to_average | |
| leaderboard_df = add_average_column_to_df(leaderboard_df, columns_to_average, index=3, average_column_name=average_column_name) | |
| leaderboard_df = apply_markdown_format_for_columns(df=leaderboard_df, model_column_name="Model") | |
| leaderboard_df = sort_dataframe_by_column(leaderboard_df, column_name=average_column_name) | |
| columns_data_type = ["markdown" for i in range(len(leaderboard_df.columns))] | |
| NUM_MODELS=len(leaderboard_df) | |
| with gr.Blocks(css=custom_css) as demo: | |
| gr.Markdown(""" | |
| # Persian Text Embedding Benchmark | |
| """) | |
| gr.Markdown(f""" | |
| - **Total Models**: {NUM_MODELS} | |
| """) | |
| with gr.Tab("🎖️ Leaderboard"): | |
| Leaderboard( | |
| value=leaderboard_df, | |
| datatype=columns_data_type, | |
| select_columns=SelectColumns( | |
| default_selection=all_columns, | |
| cant_deselect=["Model"], | |
| label="Select Columns to Show", | |
| ), | |
| search_columns=["model_name_for_query"], | |
| hide_columns=["model_name_for_query",], | |
| filter_columns=["Precision", "#Params (M)"], | |
| ) | |
| gr.Markdown("The tasks and their corresponding metrics are available in the About tab.") | |
| with gr.TabItem("📝 About"): | |
| gr.Markdown(ABOUT_TEXT) | |
| gr.Markdown(tasks_and_metrics_table_markdown) | |
| with gr.Tab("✉️ Submit"): | |
| gr.Markdown(SUBMIT_TEXT) | |
| model_name = gr.Textbox(label="Model name") | |
| model_id = gr.Textbox(label="username/space e.g PartAI/Tooka-SBERT") | |
| contact_email = gr.Textbox(label="Contact E-Mail") | |
| submit_btn = gr.Button("Submit") | |
| submit_btn.click(submit, inputs=[model_name, model_id, contact_email], outputs=[]) | |
| gr.Markdown(""" | |
| Please find more information about Part DP AI on [partdp.ai](https://partdp.ai)""") | |
| if __name__ == "__main__": | |
| demo.launch() | |