import gradio as gr
import pandas as pd
from css_html_js import custom_css

demo = gr.Blocks(css=custom_css)

TITLE = """<h1 align="center" id="space-title">🇲🇾 Malay LLM Leaderboard</h1>"""

INTRODUCTION_TEXT = """
📐 The 🇲🇾 Malay LLM Leaderboard aims to track, rank and evaluate open LLMs on Malay tasks.\n
🤗 All notebooks at https://github.com/mesolitica/llm-benchmarks, feel free to submit your own score at https://huggingface.co/spaces/mesolitica/malay-llm-leaderboard/discussions with link to the notebook.

## Dataset

📈 We evaluate models based on 3 datasets,

1. BM-PT3 Paper 1, contains 54 questions, https://github.com/mesolitica/malaysian-dataset/tree/master/llm-benchmark/BM-pt3
2. Tatabahasa, contains 349 questions, https://github.com/mesolitica/malaysian-dataset/tree/master/llm-benchmark/tatabahasabm.tripod.com
3. Translated IndoNLI to Malay, tested on `test_expert` dataset, https://huggingface.co/datasets/mesolitica/translated-indonli
"""

data = [
    {
        'model': 'gpt-3.5-turbo-0613',
        'BM-PT3 0-shot': 36.53846153846153,
        'BM-PT3 1-shot': 28.846153846153843,
        'BM-PT3 3-shots': 24.528301886792452,
        'Tatabahasa 0-shot': 59.530791788856305,
        'Tatabahasa 1-shot': 60.80691642651297,
        'Tatabahasa 3-shots': 63.03724928366762,
    },
    {
        'model': 'gpt-4-1106-preview',
        'Tatabahasa 0-shot': 75.64469914040114,
        'Tatabahasa 1-shot': 73.63896848137536,
        'Tatabahasa 3-shots': 75.64469914040114,
    },
    {
        'model': 'malaysian-llama2-7b-32k',
        'BM-PT3 0-shot': 20.37037037037037,
        'BM-PT3 1-shot': 20.37037037037037,
        'BM-PT3 3-shots': 29.629629629629626,
    },
    {
        'model': 'malaysian-llama2-7b-32k-instructions',
        'BM-PT3 0-shot': 35.294117647058826,
        'BM-PT3 1-shot': 21.153846153846153,
        'BM-PT3 3-shots': 28.30188679245283,
    },
    {
        'model': 'malaysian-llama2-13b-32k',
        'BM-PT3 0-shot': 33.33333333333333,
        'BM-PT3 1-shot': 20.37037037037037,
        'BM-PT3 3-shots': 31.48148148148148,
    },
    {
        'model': 'malaysian-llama2-13b-32k-instructions',
        'BM-PT3 0-shot': 28.57142857142857,
        'BM-PT3 1-shot': 12.244897959183673,
        'BM-PT3 3-shots': 17.307692307692307,
    },
    {
        'model': 'malaysian-mistral-7b-4k',
        'BM-PT3 0-shot': 20.37037037037037,
        'BM-PT3 1-shot': 22.22222222222222,
        'BM-PT3 3-shots': 33.33333333333333,
        'Tatabahasa 0-shot': 21.48997134670487,
        'Tatabahasa 1-shot': 28.939828080229223,
        'Tatabahasa 3-shots': 24.641833810888254,
    },
    {
        'model': 'malaysian-mistral-7b-32k',
        'BM-PT3 0-shot': 16.666666666666664,
        'BM-PT3 1-shot': 16.666666666666664,
        'BM-PT3 3-shots': 25.925925925925924,
    },
    {
        'model': 'malaysian-mistral-7b-32k-instructions',
        'BM-PT3 0-shot': 21.568627450980394,
        'BM-PT3 1-shot': 31.25,
        'BM-PT3 3-shots': 28.000000000000004,
    }
]

data = pd.DataFrame(data)

with demo:
    gr.HTML(TITLE)
    gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
    gr.DataFrame(data)

demo.launch()