app.py

import os

import gradio as gr
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import snapshot_download

from src.about import BENCHMARKS_TEXT, EVALUATION_QUEUE_TEXT, INTRODUCTION_TEXT, TITLE
from src.benchmarks import LongDocBenchmarks, QABenchmarks
from src.display.components import (
    get_anonymous_checkbox,
    get_domain_dropdown,
    get_language_dropdown,
    get_leaderboard_table,
    get_metric_dropdown,
    get_noreranking_dropdown,
    get_reranking_dropdown,
    get_revision_and_ts_checkbox,
    get_search_bar,
    get_version_dropdown,
)
from src.display.css_html_js import custom_css
from src.envs import (
    API,
    BENCHMARK_VERSION_LIST,
    BM25_LINK,
    COL_NAME_RERANKING_MODEL,
    COL_NAME_RETRIEVAL_MODEL,
    DEFAULT_METRIC_LONG_DOC,
    DEFAULT_METRIC_QA,
    EVAL_RESULTS_PATH,
    LATEST_BENCHMARK_VERSION,
    METRIC_LIST,
    REPO_ID,
    RESULTS_REPO,
    TOKEN,
)
from src.loaders import load_eval_results
from src.utils import remove_html, reset_rank, set_listeners, submit_results, update_metric, upload_file


def restart_space():
    API.restart_space(repo_id=REPO_ID)


try:
    if not os.environ.get("LOCAL_MODE", False):
        print("Running in local mode")
        snapshot_download(
            repo_id=RESULTS_REPO,
            local_dir=EVAL_RESULTS_PATH,
            repo_type="dataset",
            tqdm_class=None,
            etag_timeout=30,
            token=TOKEN,
        )
except Exception:
    print("failed to download")
    restart_space()

global data
data = load_eval_results(EVAL_RESULTS_PATH)
global datastore
datastore = data[LATEST_BENCHMARK_VERSION]


def update_metric_qa(
    metric: str,
    domains: list,
    langs: list,
    reranking_model: list,
    query: str,
    show_anonymous: bool,
    show_revision_and_timestamp: bool,
):
    return update_metric(
        datastore,
        "qa",
        metric,
        domains,
        langs,
        reranking_model,
        query,
        show_anonymous,
        show_revision_and_timestamp
    )


def update_metric_long_doc(
    metric: str,
    domains: list,
    langs: list,
    reranking_model: list,
    query: str,
    show_anonymous: bool,
    show_revision_and_timestamp,
):
    return update_metric(
        datastore,
        "long-doc",
        metric,
        domains,
        langs,
        reranking_model,
        query,
        show_anonymous,
        show_revision_and_timestamp,
    )


def update_datastore(version):
    global datastore
    global data
    datastore = data[version]
    selected_domains = get_domain_dropdown(QABenchmarks[datastore.slug])
    selected_langs = get_language_dropdown(QABenchmarks[datastore.slug])
    selected_rerankings = get_reranking_dropdown(datastore.reranking_models)
    leaderboard_table = get_leaderboard_table(datastore.leaderboard_df_qa, datastore.types_qa)
    hidden_leaderboard_table = \
        get_leaderboard_table(datastore.raw_df_qa, datastore.types_qa, visible=False)
    return selected_domains, selected_langs, selected_rerankings, leaderboard_table, hidden_leaderboard_table


def update_datastore_long_doc(version):
    global datastore
    global data
    datastore = data[version]
    selected_domains = get_domain_dropdown(LongDocBenchmarks[datastore.slug])
    selected_langs = get_language_dropdown(LongDocBenchmarks[datastore.slug])
    selected_rerankings = get_reranking_dropdown(datastore.reranking_models)
    leaderboard_table = get_leaderboard_table(datastore.leaderboard_df_long_doc, datastore.types_long_doc)
    hidden_leaderboard_table = \
        get_leaderboard_table(datastore.raw_df_long_doc, datastore.types_long_doc, visible=False)
    return selected_domains, selected_langs, selected_rerankings, leaderboard_table, hidden_leaderboard_table


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("Results", elem_id="results-tab-table"):
            with gr.Row():
                selected_version = get_version_dropdown()

            with gr.TabItem("QA", elem_id="qa-benchmark-tab-table", id=0):
                with gr.Row():
                    with gr.Column(min_width=320):
                        # select domain
                        with gr.Row():
                            selected_domains = get_domain_dropdown(QABenchmarks[datastore.slug])
                        # select language
                        with gr.Row():
                            selected_langs = get_language_dropdown(QABenchmarks[datastore.slug])
                    with gr.Column():
                        # select the metric
                        selected_metric = get_metric_dropdown(METRIC_LIST, DEFAULT_METRIC_QA)
                        with gr.Row():
                            show_anonymous = get_anonymous_checkbox()
                        with gr.Row():
                            show_revision_and_timestamp = get_revision_and_ts_checkbox()
                with gr.Tabs(elem_classes="tab-buttons") as sub_tabs:
                    with gr.TabItem("Retrieval + Reranking", id=10):
                        with gr.Row():
                            # search retrieval models
                            with gr.Column():
                                search_bar = get_search_bar()
                            # select reranking models
                            with gr.Column():
                                selected_rerankings = get_reranking_dropdown(datastore.reranking_models)
                        #  shown_table
                        lb_table = get_leaderboard_table(datastore.leaderboard_df_qa, datastore.types_qa)
                        # Dummy leaderboard for handling the case when the user uses backspace key
                        hidden_lb_table = get_leaderboard_table(datastore.raw_df_qa, datastore.types_qa, visible=False)

                        selected_version.change(
                            update_datastore,
                            [
                                selected_version,
                            ],
                            [selected_domains, selected_langs, selected_rerankings, lb_table, hidden_lb_table],
                        )

                        set_listeners(
                            "qa",
                            lb_table,
                            hidden_lb_table,
                            search_bar,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_rerankings,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )

                        # set metric listener
                        selected_metric.change(
                            update_metric_qa,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_rerankings,
                                search_bar,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table,
                            queue=True,
                        )

                    with gr.TabItem("Retrieval Only", id=11):
                        with gr.Row():
                            with gr.Column(scale=1):
                                search_bar_retriever = get_search_bar()
                            with gr.Column(scale=1):
                                selected_noreranker = get_noreranking_dropdown()

                        lb_df_retriever = datastore.leaderboard_df_qa[
                            datastore.leaderboard_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"
                        ]
                        lb_df_retriever = reset_rank(lb_df_retriever)
                        lb_table_retriever = get_leaderboard_table(lb_df_retriever, datastore.types_qa)

                        # Dummy leaderboard for handling the case when the user uses backspace key
                        hidden_lb_df_retriever = datastore.raw_df_qa[
                            datastore.raw_df_qa[COL_NAME_RERANKING_MODEL] == "NoReranker"
                        ]
                        hidden_lb_df_retriever = reset_rank(hidden_lb_df_retriever)
                        hidden_lb_table_retriever = get_leaderboard_table(
                            hidden_lb_df_retriever, datastore.types_qa, visible=False
                        )

                        selected_version.change(
                            update_datastore,
                            [
                                selected_version,
                            ],
                            [
                                selected_domains,
                                selected_langs,
                                selected_noreranker,
                                lb_table_retriever,
                                hidden_lb_table_retriever,
                            ],
                        )

                        set_listeners(
                            "qa",
                            lb_table_retriever,
                            hidden_lb_table_retriever,
                            search_bar_retriever,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_noreranker,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )

                        # set metric listener
                        selected_metric.change(
                            update_metric_qa,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_noreranker,
                                search_bar_retriever,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table_retriever,
                            queue=True,
                        )
                    with gr.TabItem("Reranking Only", id=12):
                        lb_df_reranker = datastore.leaderboard_df_qa[
                            datastore.leaderboard_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK
                        ]
                        lb_df_reranker = reset_rank(lb_df_reranker)
                        reranking_models_reranker = (
                            lb_df_reranker[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
                        )
                        with gr.Row():
                            with gr.Column(scale=1):
                                selected_rerankings_reranker = get_reranking_dropdown(reranking_models_reranker)
                            with gr.Column(scale=1):
                                search_bar_reranker = gr.Textbox(show_label=False, visible=False)
                        lb_table_reranker = get_leaderboard_table(lb_df_reranker, datastore.types_qa)

                        hidden_lb_df_reranker = datastore.raw_df_qa[
                            datastore.raw_df_qa[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK
                        ]
                        hidden_lb_df_reranker = reset_rank(hidden_lb_df_reranker)
                        hidden_lb_table_reranker = get_leaderboard_table(
                            hidden_lb_df_reranker, datastore.types_qa, visible=False
                        )

                        selected_version.change(
                            update_datastore,
                            [
                                selected_version,
                            ],
                            [
                                selected_domains,
                                selected_langs,
                                selected_rerankings_reranker,
                                lb_table_reranker,
                                hidden_lb_table_reranker,
                            ],
                        )

                        set_listeners(
                            "qa",
                            lb_table_reranker,
                            hidden_lb_table_reranker,
                            search_bar_reranker,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_rerankings_reranker,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )
                        # set metric listener
                        selected_metric.change(
                            update_metric_qa,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_rerankings_reranker,
                                search_bar_reranker,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table_reranker,
                            queue=True,
                        )
            with gr.TabItem("Long Doc", elem_id="long-doc-benchmark-tab-table", id=1):
                with gr.Row():
                    with gr.Column(min_width=320):
                        # select domain
                        with gr.Row():
                            selected_domains = get_domain_dropdown(LongDocBenchmarks[datastore.slug])
                        # select language
                        with gr.Row():
                            selected_langs = get_language_dropdown(LongDocBenchmarks[datastore.slug])
                    with gr.Column():
                        # select the metric
                        with gr.Row():
                            selected_metric = get_metric_dropdown(METRIC_LIST, DEFAULT_METRIC_LONG_DOC)
                        with gr.Row():
                            show_anonymous = get_anonymous_checkbox()
                        with gr.Row():
                            show_revision_and_timestamp = get_revision_and_ts_checkbox()
                with gr.Tabs(elem_classes="tab-buttons"):
                    with gr.TabItem("Retrieval + Reranking", id=20):
                        with gr.Row():
                            with gr.Column():
                                search_bar = get_search_bar()
                            with gr.Column():
                                selected_rerankings = get_reranking_dropdown(datastore.reranking_models)

                        lb_table_long_doc = get_leaderboard_table(
                            datastore.leaderboard_df_long_doc, datastore.types_long_doc
                        )

                        # Dummy leaderboard for handling the case when the user uses backspace key
                        hidden_lb_table_long_doc = get_leaderboard_table(
                            datastore.raw_df_long_doc, datastore.types_long_doc, visible=False
                        )

                        selected_version.change(
                            update_datastore_long_doc,
                            [
                                selected_version,
                            ],
                            [
                                selected_domains,
                                selected_langs,
                                selected_rerankings,
                                lb_table_long_doc,
                                hidden_lb_table_long_doc,
                            ],
                        )

                        set_listeners(
                            "long-doc",
                            lb_table_long_doc,
                            hidden_lb_table_long_doc,
                            search_bar,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_rerankings,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )

                        # set metric listener
                        selected_metric.change(
                            update_metric_long_doc,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_rerankings,
                                search_bar,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table_long_doc,
                            queue=True,
                        )
                    with gr.TabItem("Retrieval Only", id=21):
                        with gr.Row():
                            with gr.Column(scale=1):
                                search_bar_retriever = get_search_bar()
                            with gr.Column(scale=1):
                                selected_noreranker = get_noreranking_dropdown()
                        lb_df_retriever_long_doc = datastore.leaderboard_df_long_doc[
                            datastore.leaderboard_df_long_doc[COL_NAME_RERANKING_MODEL] == "NoReranker"
                        ]
                        lb_df_retriever_long_doc = reset_rank(lb_df_retriever_long_doc)
                        lb_table_retriever_long_doc = get_leaderboard_table(
                            lb_df_retriever_long_doc, datastore.types_long_doc
                        )

                        hidden_lb_df_retriever_long_doc = datastore.raw_df_long_doc[
                            datastore.raw_df_long_doc[COL_NAME_RERANKING_MODEL] == "NoReranker"
                        ]
                        hidden_lb_df_retriever_long_doc = reset_rank(hidden_lb_df_retriever_long_doc)
                        hidden_lb_table_retriever_long_doc = get_leaderboard_table(
                            hidden_lb_df_retriever_long_doc, datastore.types_long_doc, visible=False
                        )

                        selected_version.change(
                            update_datastore_long_doc,
                            [
                                selected_version,
                            ],
                            [
                                selected_domains,
                                selected_langs,
                                selected_noreranker,
                                lb_table_retriever_long_doc,
                                hidden_lb_table_retriever_long_doc,
                            ],
                        )

                        set_listeners(
                            "long-doc",
                            lb_table_retriever_long_doc,
                            hidden_lb_table_retriever_long_doc,
                            search_bar_retriever,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_noreranker,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )

                        selected_metric.change(
                            update_metric_long_doc,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_noreranker,
                                search_bar_retriever,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table_retriever_long_doc,
                            queue=True,
                        )
                    with gr.TabItem("Reranking Only", id=22):
                        lb_df_reranker_ldoc = datastore.leaderboard_df_long_doc[
                            datastore.leaderboard_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK
                        ]
                        lb_df_reranker_ldoc = reset_rank(lb_df_reranker_ldoc)
                        reranking_models_reranker_ldoc = (
                            lb_df_reranker_ldoc[COL_NAME_RERANKING_MODEL].apply(remove_html).unique().tolist()
                        )
                        with gr.Row():
                            with gr.Column(scale=1):
                                selected_rerankings_reranker_ldoc = get_reranking_dropdown(
                                    reranking_models_reranker_ldoc
                                )
                            with gr.Column(scale=1):
                                search_bar_reranker_ldoc = gr.Textbox(show_label=False, visible=False)
                        lb_table_reranker_ldoc = get_leaderboard_table(lb_df_reranker_ldoc, datastore.types_long_doc)
                        hidden_lb_df_reranker_ldoc = datastore.raw_df_long_doc[
                            datastore.raw_df_long_doc[COL_NAME_RETRIEVAL_MODEL] == BM25_LINK
                        ]
                        hidden_lb_df_reranker_ldoc = reset_rank(hidden_lb_df_reranker_ldoc)
                        hidden_lb_table_reranker_ldoc = get_leaderboard_table(
                            hidden_lb_df_reranker_ldoc, datastore.types_long_doc, visible=False
                        )

                        selected_version.change(
                            update_datastore_long_doc,
                            [
                                selected_version,
                            ],
                            [
                                selected_domains,
                                selected_langs,
                                selected_rerankings_reranker_ldoc,
                                lb_table_reranker_ldoc,
                                hidden_lb_table_reranker_ldoc,
                            ],
                        )

                        set_listeners(
                            "long-doc",
                            lb_table_reranker_ldoc,
                            hidden_lb_table_reranker_ldoc,
                            search_bar_reranker_ldoc,
                            selected_version,
                            selected_domains,
                            selected_langs,
                            selected_rerankings_reranker_ldoc,
                            show_anonymous,
                            show_revision_and_timestamp,
                        )
                        selected_metric.change(
                            update_metric_long_doc,
                            [
                                selected_metric,
                                selected_domains,
                                selected_langs,
                                selected_rerankings_reranker_ldoc,
                                search_bar_reranker_ldoc,
                                show_anonymous,
                                show_revision_and_timestamp,
                            ],
                            lb_table_reranker_ldoc,
                            queue=True,
                        )

        with gr.TabItem("🚀Submit here!", elem_id="submit-tab-table", id=2):
            with gr.Column():
                with gr.Row():
                    gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
                with gr.Row():
                    gr.Markdown("## ✉️Submit your model here!", elem_classes="markdown-text")
                with gr.Row():
                    with gr.Column():
                        model_name = gr.Textbox(label="Retrieval Method name")
                    with gr.Column():
                        model_url = gr.Textbox(label="Retrieval Method URL")
                with gr.Row():
                    with gr.Column():
                        reranking_model_name = gr.Textbox(
                            label="Reranking Model name", info="Optional", value="NoReranker"
                        )
                    with gr.Column():
                        reranking_model_url = gr.Textbox(label="Reranking Model URL", info="Optional", value="")
                with gr.Row():
                    with gr.Column():
                        benchmark_version = gr.Dropdown(
                            BENCHMARK_VERSION_LIST,
                            value=LATEST_BENCHMARK_VERSION,
                            interactive=True,
                            label="AIR-Bench Version",
                        )
                with gr.Row():
                    upload_button = gr.UploadButton("Click to upload search results", file_count="single")
                with gr.Row():
                    file_output = gr.File()
                with gr.Row():
                    is_anonymous = gr.Checkbox(
                        label="Nope. I want to submit anonymously 🥷",
                        value=False,
                        info="Do you want to shown on the leaderboard by default?",
                    )
                with gr.Row():
                    submit_button = gr.Button("Submit")
                with gr.Row():
                    submission_result = gr.Markdown()
                upload_button.upload(
                    upload_file,
                    [
                        upload_button,
                    ],
                    file_output,
                )
                submit_button.click(
                    submit_results,
                    [
                        file_output,
                        model_name,
                        model_url,
                        reranking_model_name,
                        reranking_model_url,
                        benchmark_version,
                        is_anonymous,
                    ],
                    submission_result,
                    show_progress="hidden",
                )

        with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=3):
            gr.Markdown(BENCHMARKS_TEXT, elem_classes="markdown-text")

if __name__ == "__main__":
    scheduler = BackgroundScheduler()
    scheduler.add_job(restart_space, "interval", seconds=1800)
    scheduler.start()
    demo.queue(default_concurrency_limit=40)
    demo.launch()