app.py

import pandas as pd
import gradio as gr
import os
from gradio_rangeslider import RangeSlider
import math

from utils.filter_utils import filter, filter_cols

# MAPS = filter_utils.LANG_MAPPING

# Main Leaderboard containing everything
text_leaderboard = pd.read_csv(os.path.join('src', 'main_df.csv'))
text = "## The range is: {min} to {max}"

# Short leaderboard containing fixed columns
short_leaderboard = filter_cols(text_leaderboard)


## Extract data
langs = []
licenses = []
ip_prices = []
op_prices = []
latencies = []
parameters = []
contexts = []
dates = []

for i in range(len(text_leaderboard)):
    lang_splits = text_leaderboard.iloc[i]['Languages'].split(',')
    lang_splits = [s.strip() for s in lang_splits]
    langs += lang_splits
    license_name = text_leaderboard.iloc[i]['License Name']

    licenses.append(license_name)
    ip_prices.append(text_leaderboard.iloc[i]['Input $/1M'])
    op_prices.append(text_leaderboard.iloc[i]['Output $/1M'])
    latencies.append(text_leaderboard.iloc[i]['Average Latency (s)'])
    parameters.append(text_leaderboard.iloc[i]['Parameter Size (B)'])
    contexts.append(text_leaderboard.iloc[i]['Context Size'])
    dates.append(text_leaderboard.iloc[i]['Release Date'])


langs = list(set(langs))
langs.sort()

licenses = list(set(licenses))
licenses.sort()

max_input_price = max(ip_prices)
max_output_price = max(op_prices)
max_latency = max(latencies)

max_parameter = max(parameters)
max_parameter = math.ceil(math.log2(max_parameter))

max_context = max(contexts)/1024
max_context = math.ceil(math.log2(max_context))

min_date = min(dates)
max_date = max(dates)


llm_calc_app = gr.Blocks()
with llm_calc_app:        
    ### Language filter
    with gr.Row():
        lang_dropdown = gr.Dropdown(
            choices=langs,
            value=[],
            multiselect=True,
            label="Select Languages 🕹️"
        )

    with gr.Row():
        with gr.Column(scale=3):
            parameter_slider = RangeSlider(
                minimum=0, 
                maximum=max_parameter, 
                label="Select Parameters. Range -> 2^x - 2^y"
            )
        with gr.Column(scale=1):
            range_ = gr.Markdown(value=text.format(min=0, max=math.pow(2, max_parameter)))
            parameter_slider.change(lambda s: text.format(min=int(pow(2,s[0])), max=int(pow(2,s[1]))), parameter_slider, range_,
                                    show_progress="hide", trigger_mode="always_last")
            
    with gr.Row():
        with gr.Column(scale=3):
            context_slider = RangeSlider(
                minimum=0, 
                maximum=max_context, 
                label="Select Context length range. Range -> 2^x k - 2^y k"
            )
        with gr.Column(scale=1):
            context_range_ = gr.Markdown(value=text.format(min=0, max=math.pow(2, max_context)))
            context_slider.change(lambda s: text.format(min=int(pow(2,s[0])), max=int(pow(2,s[1]))), context_slider, context_range_,
                                    show_progress="hide", trigger_mode="always_last")
            
    with gr.Row():
        with gr.Column():
            start_date = gr.DateTime(
                value=min_date,
                type="string",
                label="Select start date"
            )

        with gr.Column():
            end_date = gr.DateTime(
                value=max_date,
                type="string",
                label="Select end date"
            )

    with gr.Row():
        input_pricing_slider = RangeSlider(
            minimum=0, 
            maximum=max_input_price, 
            value=(0, max_input_price), 
            label="Select Price range /1M input tokens"
        )
       
        output_pricing_slider = RangeSlider(
            minimum=0, 
            maximum=max_output_price, 
            value=(0, max_output_price), 
            label="Select Price range /1M output tokens"
        )
       
    with gr.Row():
        with gr.Column():
            multimodal_checkbox = gr.CheckboxGroup(
                choices=['Image', 'Multi-Image', 'Audio', 'Video'],
                value=[],
                label="Select additional Modalities",
            )

        with gr.Column():
            open_weight_checkbox = gr.CheckboxGroup(
                choices=['Open', 'Commercial'],
                value=['Open', 'Commercial'],
                label="Filter Open-weight model or commercial model",
            )    

        with gr.Column():
            license_checkbox = gr.CheckboxGroup(
                choices=licenses,
                value=licenses,
                label="Filter based on the type of License",
            )             



    with gr.Row():
        """
        Main Leaderboard Row
        """

        leaderboard_table = gr.Dataframe(
                                value=short_leaderboard,
                                elem_id="text-leaderboard-table",
                                interactive=False,
                                visible=True,
                                height=800,
                                datatype=['html', 'number', 'number', 'date', 'number', 'number', 'number', 'number', 'html']
                            )

        
        dummy_leaderboard_table = gr.Dataframe(
                                value=text_leaderboard,
                                elem_id="dummy-leaderboard-table",
                                interactive=False,
                                visible=False
                            )
        
        lang_dropdown.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],   
            queue=True
        )

        parameter_slider.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        input_pricing_slider.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        output_pricing_slider.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        multimodal_checkbox.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        open_weight_checkbox.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        context_slider.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        start_date.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        end_date.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

        license_checkbox.change(
            filter,
            [dummy_leaderboard_table, lang_dropdown, parameter_slider,
             input_pricing_slider, output_pricing_slider, multimodal_checkbox,
             context_slider, open_weight_checkbox, start_date, end_date, license_checkbox],
            [leaderboard_table],
            queue=True
        )

    llm_calc_app.load()
llm_calc_app.queue()
llm_calc_app.launch()



"""
model_name, input_price, output_price,
multimodality_image,multimodality_multiple_image,multimodality_audio,multimodality_video,
source,licence_name,licence_url,languages,release_date,
parameters_estimated,parameters_actual,

open_weight,context, 

additional_prices_context_caching,
additional_prices_context_storage,
additional_prices_image_input,additional_prices_image_output,additional_prices_video_input,additional_prices_video_output,additional_prices_audio_input,additional_prices_audio_output,clemscore_v1.6.5_multimodal,clemscore_v1.6.5_ascii,clemscore_v1.6,latency_v1.6,latency_v1.6.5_multimodal,latency_v1.6.5_ascii,

average_clemscore,average_latency,parameters

Final list

model_name, input_price, output_price,
multimodality_image,multimodality_multiple_image,multimodality_audio,multimodality_video,
source,licence_name,licence_url,languages,release_date, open_weight,context, average_clemscore,average_latency,parameters


Filter
multimodality_image,multimodality_multiple_image,multimodality_audio,multimodality_video,
licence_name+licence_url, languages, release_date, open_weight

RR
model_name, input_price, output_price,
source, release_date

"""