import os

import gradio as gr

from src.control_panel import create_control_panel, create_control_callback
from src.latency_score_memory import create_lat_score_mem_plot
from src.leaderboard import create_leaderboard_table
from src.flashattentionv2 import create_fa2_plots
from src.bettertransformer import create_bt_plots
from src.llm_perf import get_llm_perf_df
from src.assets import custom_css
from src.text import (
    TITLE,
    ABOUT,
    INTRODUCTION,
    EXAMPLE_CONFIG,
    CITATION_BUTTON,
    CITATION_BUTTON_LABEL,
)


LOGO_URL = "https://huggingface.co/spaces/optimum/llm-perf-leaderboard/resolve/main/logo.png"
MACHINE_TO_HARDWARE = {"hf-dgx-01": "A100-80GB 🖥️"}
HF_TOKEN = os.environ.get("HF_TOKEN", None)


demo = gr.Blocks(css=custom_css)
with demo:
    gr.HTML(TITLE, elem_classes="title")
    gr.HTML(f'<img src="{LOGO_URL}">', elem_classes="logo")
    gr.Markdown(INTRODUCTION, elem_classes="descriptive-text")
    ####################### HARDWARE TABS #######################
    with gr.Tabs(elem_classes="tabs"):
        for id, (machine, hardware) in enumerate(MACHINE_TO_HARDWARE.items()):
            with gr.TabItem(hardware, id=id):
                ####################### CONTROL PANEL #######################
                (
                    filter_button,
                    machine_textbox,
                    search_bar,
                    score_slider,
                    memory_slider,
                    backend_checkboxes,
                    datatype_checkboxes,
                    optimization_checkboxes,
                    quantization_checkboxes,
                ) = create_control_panel()
                ####################### HARDWARE SUBTABS #######################
                with gr.Tabs(elem_classes="subtabs"):
                    llm_perf_df = get_llm_perf_df(machine=machine)
                    ####################### LEADERBOARD TAB #######################
                    with gr.TabItem("Leaderboard 🏅", id=0):
                        leaderboard_table = create_leaderboard_table(llm_perf_df)
                    ####################### LAT. vs. SCORE vs. MEM. TAB #######################
                    with gr.TabItem("Latency vs. Score vs. Memory 📊", id=1):
                        lat_score_mem_plot = create_lat_score_mem_plot(llm_perf_df)
                    ####################### BETTERTRANSFORMER SPEEDUP TAB #######################
                    with gr.TabItem("BetterTransformer Speedup 📈", id=2):
                        bt_prefill_plot, bt_decode_plot = create_bt_plots(llm_perf_df)
                    with gr.TabItem("FlashAttentionV2 Speedup 📈", id=3):
                        fa2_prefill_plot, fa2_decode_plot = create_fa2_plots(llm_perf_df)
                ####################### CONTROL CALLBACK #######################
                create_control_callback(
                    filter_button,
                    # inputs
                    machine_textbox,
                    search_bar,
                    score_slider,
                    memory_slider,
                    backend_checkboxes,
                    datatype_checkboxes,
                    optimization_checkboxes,
                    quantization_checkboxes,
                    # outputs
                    leaderboard_table,
                    lat_score_mem_plot,
                    bt_prefill_plot,
                    bt_decode_plot,
                    fa2_prefill_plot,
                    fa2_decode_plot,
                )
        ####################### ABOUT TAB #######################
        with gr.TabItem("About 📖", id=3):
            gr.HTML(ABOUT, elem_classes="descriptive-text")
            gr.Markdown(EXAMPLE_CONFIG, elem_classes="descriptive-text")
    ####################### CITATION
    with gr.Row():
        with gr.Accordion("📙 Citation", open=False):
            citation_button = gr.Textbox(
                value=CITATION_BUTTON,
                label=CITATION_BUTTON_LABEL,
                elem_id="citation-button",
                show_copy_button=True,
            )

if __name__ == "__main__":
    # Launch demo
    demo.queue().launch()