app.py

import pandas as pd

import gradio as gr
from gradio_leaderboard import Leaderboard

from utils import fetch_hf_results, show_output_box
from constants import (
    ASSAY_LIST,
    ASSAY_RENAME,
    ASSAY_EMOJIS,
    ASSAY_DESCRIPTION,
    EXAMPLE_FILE_DICT,
    ANONYMOUS_SUBMISSION_USERNAME,
)
from about import ABOUT_TEXT, FAQS
from submit import make_submission


def format_leaderboard_table(df_results: pd.DataFrame, assay: str | None = None):
    # Previous things that were nice in the constellaration leaderboard:
    # Having a submission time column, and a user column where the username is clickable (this is a pro for usability but con for anonymity)
    # full_df.rename(columns={'submission_time': 'submission time', 'problem_type': 'problem type'}, inplace=True)
    # to_show['user'] = to_show['user'].apply(lambda x: make_user_clickable(x)).astype(str)
    column_order = ["model", "property", "spearman", "spearman_cross_val"]
    df = df_results.query("assay.isin(@ASSAY_RENAME.keys())").copy()
    if assay is not None:
        df = df[df["assay"] == assay]
    df = df[column_order]
    return df.sort_values(by="spearman", ascending=False)


# Cache the results to avoid multiple downloads
_cached_results = None


def get_cached_results():
    global _cached_results
    if _cached_results is None:
        _cached_results = fetch_hf_results()
    return _cached_results


def get_leaderboard_object(assay: str | None = None):
    filter_columns = ["model"]
    if assay is None:
        filter_columns.append("property")
    # TODO how to sort filter columns alphabetically?
    Leaderboard(
        # TODO(Lood) check that this actually refreshes using the function
        value=format_leaderboard_table(df_results=get_cached_results(), assay=assay),
        datatype=["str", "str", "str", "number"],
        select_columns=["model", "property", "spearman", "spearman_cross_val"],
        search_columns=["model"],
        filter_columns=filter_columns,
        every=60,
        render=True,
    )


with gr.Blocks() as demo:
    gr.Markdown("""
        ## Welcome to the Ginkgo Antibody Developability Benchmark!

        **Beta version, not publicly launched yet**

        Participants can submit their model to the leaderboard by uploading a CSV file (see the "✉️ Submit" tab).
        See more details in the "❔About" tab.
        """)
    with gr.Tabs(elem_classes="tab-buttons"):
        with gr.TabItem("❔About", elem_id="abdev-benchmark-tab-table"):
            gr.Image(
                value="./assets/competition_logo.jpg",
                show_label=False,
                # elem_classes=["resized-image"],
                show_download_button=False,
                width="50vw",  # 50% of the "viewport width"
            )
            gr.Markdown(ABOUT_TEXT)
            for question, answer in FAQS.items():
                with gr.Accordion(question):
                    gr.Markdown(answer)

        # Procedurally make these 5 tabs
        for assay in ASSAY_LIST:
            with gr.TabItem(
                f"{ASSAY_EMOJIS[assay]} {ASSAY_RENAME[assay]}",
                elem_id="abdev-benchmark-tab-table",
            ):
                gr.Markdown(f"# {ASSAY_DESCRIPTION[assay]}")
                get_leaderboard_object(assay=assay)

        with gr.TabItem("🚀 Overall", elem_id="abdev-benchmark-tab-table"):
            gr.Markdown(
                "# Antibody Developability Benchmark Leaderboard over all properties"
            )
            get_leaderboard_object()

        with gr.TabItem("✉️ Submit", elem_id="boundary-benchmark-tab-table"):
            gr.Markdown(
                """
            # Antibody Developability Submission
            Upload a CSV to get a score!

            Please use your Hugging Face account name to submit your model - we use this to track separate submissions, but only Hugging Face/Ginkgo will see these usernames (unless you choose to make them public).
            Your submission will be evaluated and added to the leaderboard.
            """
            )
            filename = gr.State(value=None)
            eval_state = gr.State(value=None)
            user_state = gr.State(value=None)
            submission_type_state = gr.State(value="GDPa1")
            download_file_state = gr.State(value=EXAMPLE_FILE_DICT["GDPa1"])

            with gr.Row():
                with gr.Column():
                    username_input = gr.Textbox(
                        label="Username",
                        placeholder="Enter your Hugging Face username or leave blank for anonymous submissions",
                        info="This will be used to track your submissions, and to update your results if you submit again.",
                    )
                    model_name_input = gr.Textbox(
                        label="Model Name",
                        placeholder="Enter your model name (e.g., 'MyProteinLM-v1')",
                        info="This will be displayed on the leaderboard.",
                    )
                    model_description_input = gr.Textbox(
                        label="Model Description",
                        placeholder="Brief description of your model and approach",
                        info="Describe your model, training data, or methodology.",
                        lines=3,
                    )
                with gr.Column():
                    submission_type_dropdown = gr.Dropdown(
                        choices=["GDPa1", "GDPa1_cross_validation"],
                        value="GDPa1",
                        label="Submission Type",
                    )
                    download_button = gr.DownloadButton(
                        label="📥 Download example submission CSV",
                        value=EXAMPLE_FILE_DICT["GDPa1"],
                        variant="secondary",
                    )
                    submission_file = gr.File(label="Submission CSV")

            # If username is empty, set to anonymous submission
            username_input.change(
                fn=lambda x: x if x.strip() else ANONYMOUS_SUBMISSION_USERNAME,
                inputs=username_input,
                outputs=user_state,
            )

            def update_submission_type_and_file(submission_type):
                """
                Based on the submission type selected in the dropdown,
                    Update the submission type state
                    Dynamically update example file for download
                """
                download_file = EXAMPLE_FILE_DICT.get(
                    submission_type, EXAMPLE_FILE_DICT["GDPa1"]
                )
                return (
                    submission_type,
                    download_file,
                    gr.DownloadButton(
                        label="📥 Download example submission CSV",
                        value=download_file,
                        variant="secondary",
                    ),
                )

            # Update submission type state and download button when dropdown changes
            submission_type_dropdown.change(
                fn=update_submission_type_and_file,
                inputs=submission_type_dropdown,
                outputs=[submission_type_state, download_file_state, download_button],
            )

            submit_btn = gr.Button("Evaluate")
            message = gr.Textbox(label="Status", lines=1, visible=False)
            # help message
            gr.Markdown(
                "If you have issues with submission or using the leaderboard, please start a discussion in the Community tab of this Space."
            )

            submit_btn.click(
                make_submission,
                inputs=[
                    submission_file,
                    user_state,
                    submission_type_state,
                    model_name_input,
                    model_description_input,
                ],
                outputs=[message],
            ).then(
                fn=show_output_box,
                inputs=[message],
                outputs=[message],
            )
    # Footnote
    gr.Markdown(
        """
        <div style="text-align: center; font-size: 14px; color: gray; margin-top: 2em;">
        📬 For questions or feedback, contact <a href="mailto:[email protected]">[email protected]</a> or visit the Community tab at the top of this page.
        </div>
        """,
        elem_id="contact-footer",
    )

if __name__ == "__main__":
    demo.launch()