import gradio as gr
import pandas as pd

from src.about import (
    CITATION_BUTTON_LABEL,
    CITATION_BUTTON_TEXT,
    EVALUATION_QUEUE_TEXT,
    INTRODUCTION_TEXT,
    LLM_BENCHMARKS_TEXT,
    TITLE,
)

# Simplified DataFrame for the leaderboard
data = {
    "Model": [
        "Handwritten TAG",
        "Zero-shot Text2SQL",
        "Zero-shot Text2SQL + LM Generation",
        "RAG (E5)",
        "RAG (E5) + LM Rerank"
    ],
    "Code": [
        "",  # Handwritten TAG doesn't have a code link
        "",  # Zero-shot Text2SQL doesn't have a code link
        "",  # Zero-shot Text2SQL + LM Generation doesn't have a code link
        "",  # RAG (E5) doesn't have a code link
        ""   # RAG (E5) + LM Rerank doesn't have a code link
    ],
    "Execution Accuracy": [
        "55%",  # Handwritten TAG
        "17%",  # Zero-shot Text2SQL
        "13%",  # Zero-shot Text2SQL + LM Generation
        "0%",   # RAG (E5)
        "2%"    # RAG (E5) + LM Rerank
    ]
}

leaderboard_df = pd.DataFrame(data)

# Simplified Gradio app
with gr.Blocks() as demo:
    gr.HTML(TITLE)
    gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")

    with gr.Tabs(elem_classes="tab-buttons") as tabs:
        with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
            # Highlight the top row in green for "Handwritten TAG"
            with gr.Row():
                gr.Dataframe(
                    value=leaderboard_df,
                    headers=["Model", "Code", "Execution Accuracy"],
                    datatype=["str", "str", "str"],
                    row_count=(5, "dynamic"),
                    wrap=True,
                    elem_id="leaderboard",
                    type="pandas"
                )

        with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
            gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")

        with gr.TabItem("🚀 Submission Instructions ", elem_id="llm-benchmark-tab-table", id=3):
            gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")


demo.launch()