import gradio as gr
import pandas as pd
import random
import plotly.express as px


def greet(name):
    return "Hello " + name + "!"


def get_results_df():
    data = {
        "Model": ["Model A", "Model B", "Model C"],
        "Avg": [0.85, 0.90, 0.88],
        "Gap Read": [0.05, 0.03, 0.04],
        "Gap Spontaneous": [0.07, 0.06, 0.05],
    }

    df = pd.DataFrame(data)
    return df


def get_language_performance():
    languages = [
        "en",
        "es",
        "de",
        "fr",
        "it",
        "pt",
        "nl",
        "ru",
        "zh",
        "ja",
        "ko",
        "ar",
        "hi",
        "bn",
        "ur",
        "tr",
        "sv",
    ]
    data = {
        "Model": ["Model A", "Model B", "Model C"],
    }

    for lang in languages:
        data[lang] = [random.uniform(-100, 100) for _ in range(3)]

    df = pd.DataFrame(data)
    return df


results = get_results_df()

with gr.Blocks() as fm_interface:
    gr.DataFrame(results)

    language_performance = get_language_performance()
    print(language_performance)

    fig1 = px.bar(
        language_performance.melt(
            id_vars="Model", var_name="Language", value_name="Performance"
        ),
        x="Language",
        y="Performance",
        color="Model",
        title="Language Performance Plot 1",
        barmode="group",
    )
    fig2 = px.bar(
        language_performance.melt(
            id_vars="Model", var_name="Language", value_name="Performance"
        ),
        x="Language",
        y="Performance",
        color="Model",
        title="Language Performance Plot 2",
        barmode="group",
    )

    gr.Plot(fig1)
    gr.Plot(fig2)

tabs = [fm_interface]
titles = ["F-M Setup"]

with gr.Blocks() as demo:
    gr.Markdown("# Fair ASR Leadeboard")
    gr.TabbedInterface(tabs, titles)

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