The gradio_leaderboard package helps you build fully functional and performant leaderboard demos with gradio.

Place the gradio_leaderboard.Leaderboard component anywhere in your Gradio application (and optionally pass in some configuration). That's it!

For example usage, please see the Usage section.

For details on configuration, please see the Configuration section.

For the API reference, see the Initialization section.

pip install gradio_leaderboard

or add gradio_leaderboard to your requirements.txt.

import gradio as gr
from gradio_leaderboard import Leaderboard
from pathlib import Path
import pandas as pd

abs_path = Path(__file__).parent

# Any pandas-compatible data
df = pd.read_json(str(abs_path / "leaderboard_data.json"))

with gr.Blocks() as demo:
    gr.Markdown("""
    # 🥇 Leaderboard Component
    """)
    Leaderboard(
        value=df,
        select_columns=["T", "Model", "Average ⬆️", "ARC",
            "HellaSwag", "MMLU", "TruthfulQA",
            "Winogrande", "GSM8K"],
        search_columns=["model_name_for_query", "Type"],
        hide_columns=["model_name_for_query", "Model Size"],
        filter_columns=["T", "Precision", "Model Size"],
    )

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

When column selection is enabled, a checkboxgroup will be displayed in the top left corner of the leaderboard that lets users select which columns are displayed.

You can disable/configure the column selection behavior of the Leaderboard with the select_columns parameter. It's value can be:

• None: Column selection is not allowed and all of the columns are displayed when the leaderboard loads.
• list of column names: All columns can be selected and the elements of this list correspond to the initial set of selected columns.
• SelectColumns instance: You can import SelectColumns from gradio_leaderboard for full control of the column selection behavior as well as the checkboxgroup appearance. See an example below.

import pandas as pd
import gradio as gr
from gradio_leaderboard import Leaderboard, SelectColumns

with gr.Blocks() as demo:
    Leaderboard(
        value=pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [7, 8, 9]}),
        select_columns=SelectColumns(default_selection=["a", "b"],
                                    cant_deselect="a",
                                    label="Select The Columns",
                                    info="Helpful information")
    )

demo.launch()

When searching is enabled, a textbox will appear in the top left corner of the leaderboard. Users will be able to display rows that match their search query.

Searching follows the following rules:

1. Multiple queries can be separated by a semicolon ;.
2. Any subquery is matched against the primary search column by default.
3. To match against a secondary search column, the query must be preceded by the column name and a colon (:), e.g. Name: Maria.
4. The returned rows are those that match against ANY primary search column and ALL secondary search columns.

You can configure searching with the search_columns parameter. It's value can be:

• a list: In which case the first element is the primary search column and the remaining are the secondary search columns.
• A SearchColumns instance. This lets you specify the primary and secondary columns explicitly as well as customize the search textbox appearance.

import pandas as pd
import gradio as gr
from gradio_leaderboard import Leaderboard, SearchColumns

with gr.Blocks() as demo:
    Leaderboard(
        value=pd.DataFrame({"name": ["Freddy", "Maria", "Mark"], "country": ["USA", "Mexico", "USA"]}),
        search_columns=SearchColumns(primary_column="name", secondary_columns="country",
                                     placeholder="Search by name or country. To search by country, type 'country:<query>'",
                                     label="Search"),
    )

demo.launch()

You can let users filter out rows from the leaderboard with the filter_columns parameter. This will display a series of form elements that users can use to select/deselect which rows are displayed.

This parameter must be a list but it's elements must be:

• a string: Corresponding to the column name you'd like to add a filter for
• a ColumnFilter: A special class for full control of the filter's type, e.g. checkboxgroup, checkbox, slider, or dropdown, as well as it's appearance in the UI.

If the type of the ColumnFilter is not specified, a heuristic will be used to choose the most appropriate type. If the data in the column is boolean-valued, a checkbox will be used. If it is numeric, a slider will be used. For all others, a checkboxgroup will be used.

import pandas as pd
import gradio as gr
from gradio_leaderboard import Leaderboard, ColumnFilter

with gr.Blocks() as demo:
    Leaderboard(
        value=pd.DataFrame({"name": ["Freddy", "Maria", "Mark"], "country": ["USA", "Mexico", "USA"],
                            "age": [25, 30, 35], "score": [100, 200, 300]}),
        filter_columns=[
            "name",
            ColumnFilter("country", type="dropdown", label="Select Country 🇺🇸🇲🇽"),
            ColumnFilter("age", type="slider", min=20, max=40, greater_than=True),
            ColumnFilter("score", type="slider", min=50, max=350, greater_than=True)],
    )

demo.launch()

pd.DataFrame | None

str | list[str]

list[str] | SearchColumns

list[str] | SelectColumns

list[str | ColumnFilter] | None

list[str] | None

list[dict[str, str | bool]] | None

str | None

bool | None

float | None

int

int | None

int

bool | None

bool

str | None

list[str] | str | None

bool

bool

bool

list[str | int] | None