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()