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

TITLE = """<h1 align="center" id="space-title">🇲🇾 Malaysian RAG Embedding Leaderboard</h1>"""

INTRODUCTION_TEXT = """
📐 The 🇲🇾 Malaysian RAG Embedding Leaderboard aims to track, rank and evaluate Top-k retrieval using embedding models. All notebooks at https://github.com/mesolitica/embedding-benchmarks, feel free to submit your own score at https://huggingface.co/spaces/mesolitica/Malaysian-Embedding-Leaderboard/discussions with link to the notebook.

## Dataset

📈 We evaluate models based on 2 datasets,

1. Research paper keyword `melayu` using Crossref, https://huggingface.co/datasets/mesolitica/malaysian-ultrachat/resolve/main/ultrachat-crossref-melayu-malay.jsonl
2. lom.agc.gov.my PDF files, https://huggingface.co/datasets/mesolitica/malaysian-ultrachat/resolve/main/ultrachat-lom-agc.jsonl
"""

close_source = [
    {
        'model': 'OpenAI ADA-002',
        'Crossref Melayu top-1': 0.3155939351340496,
        'Crossref Melayu top-3': 0.5120996083944171,
        'Crossref Melayu top-5': 0.5878100210864544,
        'Crossref Melayu top-10': 0.6721558389396526,
        'lom.agc.gov.my top-1': 0.19168533731640527,
        'lom.agc.gov.my top-3': 0.2827981080408265,
        'lom.agc.gov.my top-5': 0.322504356484939,
        'lom.agc.gov.my top-10': 0.36855862584017923,
    }
]

open_source = [
    {
        'model': '[mesolitica/llama2-embedding-600m-8k](https://huggingface.co/mesolitica/llama2-embedding-600m-8k)',
        'Crossref Melayu top-1': 0.09549151521237072,
        'Crossref Melayu top-3': 0.1834521538307059,
        'Crossref Melayu top-5': 0.23375840947886334,
        'Crossref Melayu top-10': 0.3098704689225826,
        'lom.agc.gov.my top-1': 0.05215334826985312,
        'lom.agc.gov.my top-3': 0.09932785660941,
        'lom.agc.gov.my top-5': 0.12969878018421707,
        'lom.agc.gov.my top-10': 0.1797361214836943,
    },
    {
        'model': '[mesolitica/llama2-embedding-1b-8k](https://huggingface.co/mesolitica/llama2-embedding-1b-8k)',
        'Crossref Melayu top-1': 0.06777788934631991,
        'Crossref Melayu top-3': 0.142584596847073,
        'Crossref Melayu top-5': 0.18817150316296816,
        'Crossref Melayu top-10': 0.25715433276433375,
        'lom.agc.gov.my top-1': 0.06870799103808813,
        'lom.agc.gov.my top-3': 0.1343042071197411,
        'lom.agc.gov.my top-5': 0.1717699775952203,
        'lom.agc.gov.my top-10': 0.23089370176748816,
    },
    {
        'model': '[mesolitica/mistral-embedding-191m-8k-contrastive](https://huggingface.co/mesolitica/mistral-embedding-191m-8k-contrastive)',
        'Crossref Melayu top-1': 0.08001654088700506,
        'Crossref Melayu top-3': 0.17378269409697095,
        'Crossref Melayu top-5': 0.232192701333609,
        'Crossref Melayu top-10': 0.32482166856197664,
        'lom.agc.gov.my top-1': 0.041075429424943986,
        'lom.agc.gov.my top-3': 0.09148618371919343,
        'lom.agc.gov.my top-5': 0.12758277321384118,
        'lom.agc.gov.my top-10': 0.18707991038088126,
    },
    {
        'model': '[mesolitica/mistral-embedding-349m-8k-contrastive](https://huggingface.co/mesolitica/mistral-embedding-349m-8k-contrastive)',
        'Crossref Melayu top-1': 0.09045797580895276,
        'Crossref Melayu top-3': 0.18742892587615012,
        'Crossref Melayu top-5': 0.2444949860436266,
        'Crossref Melayu top-10': 0.3398118474103174,
        'lom.agc.gov.my top-1': 0.039581777445855115,
        'lom.agc.gov.my top-3': 0.08849887976101568,
        'lom.agc.gov.my top-5': 0.12335075927308937,
        'lom.agc.gov.my top-10': 0.18558625840179238,
    },
    {
        'model': '[mesolitica/llama2-embedding-600m-8k-contrastive](https://huggingface.co/mesolitica/llama2-embedding-600m-8k)',
        'Crossref Melayu top-1': 0.11650987284193115,
        'Crossref Melayu top-3': 0.25235190737103275,
        'Crossref Melayu top-5': 0.340225369585444,
        'Crossref Melayu top-10': 0.45632172025224854,
        'lom.agc.gov.my top-1': 0.059870550161812294,
        'lom.agc.gov.my top-3': 0.12683594722429675,
        'lom.agc.gov.my top-5': 0.1696539706248444,
        'lom.agc.gov.my top-10': 0.2534229524520787,
    },
    {
        'model': '[mesolitica/llama2-embedding-1b-8k-contrastive](https://huggingface.co/mesolitica/llama2-embedding-1b-8k)',
        'Crossref Melayu top-1': 0.19600951101002792,
        'Crossref Melayu top-3': 0.39853199627830044,
        'Crossref Melayu top-5': 0.5006719735345808,
        'Crossref Melayu top-10': 0.6356869637134291,
        'lom.agc.gov.my top-1': 0.11115260144386357,
        'lom.agc.gov.my top-3': 0.21807318894697536,
        'lom.agc.gov.my top-5': 0.2891461289519542,
        'lom.agc.gov.my top-10': 0.3940751804829475,
    },
    {
        'model': '[mesolitica/llama2-embedding-2b-8k-contrastive](https://huggingface.co/mesolitica/llama2-embedding-2b-8k)',
        'Crossref Melayu top-1': 0.21130983148971363,
        'Crossref Melayu top-3': 0.4032875012922568,
        'Crossref Melayu top-5': 0.5028429649539956,
        'Crossref Melayu top-10': 0.6231779179158482,
        'lom.agc.gov.my top-1': 0.11725168035847648,
        'lom.agc.gov.my top-3': 0.23226288274831963,
        'lom.agc.gov.my top-5': 0.2977346278317152,
        'lom.agc.gov.my top-10': 0.3975603684341548,
    },
]

data = pd.DataFrame(close_source + open_source)

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

demo.launch()