import asyncio

import gradio as gr
import pandas as pd

import src.constants as constants
from src.hub import glob, load_jsonlines_file


def update_task_description_component(task):
    base_description = constants.TASK_DESCRIPTIONS.get(task, "")
    additional_info = "A higher score is a better score."
    description = f"{base_description}\n\n{additional_info}" if base_description else additional_info
    return gr.Textbox(
        description,
        label="Task Description",
        lines=6,
        visible=True,
    )


def update_subtasks_component(task, profile: gr.OAuthProfile | None):
    visible_login_btn = True if task == "leaderboard_gpqa" else False
    subtasks = None if task == "leaderboard_gpqa" and not profile else constants.SUBTASKS.get(task)
    return (
        gr.LoginButton(size="sm", visible=visible_login_btn),
        gr.Radio(
            choices=subtasks,
            info="Evaluation subtasks to be loaded",
            value=None,
        ),
    )


def update_load_details_component(model_id, subtask):
    if model_id and subtask:
        return gr.Button("Load Details", interactive=True)
    else:
        return gr.Button("Load Details", interactive=False)


def fetch_details_paths(model_id, subtask):
    model_name_sanitized = model_id.replace("/", "__")
    dataset_id = constants.DETAILS_DATASET_ID.format(model_name_sanitized=model_name_sanitized)
    filename = constants.DETAILS_FILENAME.format(subtask=subtask)
    path = f"{dataset_id}/**/{filename}"
    return glob(path)


async def load_details_dataframe(model_id, subtask):
    if not model_id or not subtask:
        return
    paths = fetch_details_paths(model_id, subtask)
    if not paths:
        return
    path = max(paths)
    data = await load_jsonlines_file(path)
    df = pd.json_normalize(data)
    # Keep model_name:
    df["model_name"] = model_id
    return df.sort_values("doc_id").set_index("doc_id", drop=False).set_index("model_name", append=True)


async def load_details(model_ids, subtask):
    dfs = await asyncio.gather(*[load_details_dataframe(model_id, subtask) for model_id in model_ids])
    if dfs:
        return pd.concat(dfs)


def display_details(df, sample_idx, show_only_differences):
    if df is None:
        return
    df = df.loc[df.index.levels[0][sample_idx]]
    df = df.T.rename_axis(columns=None)

    # Style
    # - Option: Show only differences
    any_difference = pd.Series(False, index=df.index)
    if show_only_differences:
        any_difference = df.ne(df.iloc[:, 0], axis=0).any(axis=1)

    return (
        df.style.format(escape="html", na_rep="")
        # .hide(axis="index")
        # Hide non-different rows
        .hide([row for row in df.index if show_only_differences and not any_difference[row]])
        # Fix overflow
        .set_table_styles(
            [
                {
                    "selector": "td",
                    "props": [("overflow-wrap", "break-word"), ("max-width", "1px")],
                },
                {
                    "selector": ".col_heading",
                    "props": [("width", f"{100 / len(df.columns)}%")],
                },
            ]
        )
        .to_html()
    )


def update_sample_idx_component(df):
    if df is None:
        return
    maximum = len(df) - 1
    return gr.Number(
        label="Sample Index",
        info="Index of the sample to be displayed",
        value=0,
        minimum=0,
        maximum=maximum,
        visible=True,
    )


def clear_details():
    # model_ids, details_dataframe, details_task, subtask, load_details_btn, sample_idx
    return (
        gr.Dropdown(value=[]),
        None,
        None,
        None,
        gr.Button("Load Details", interactive=False),
        gr.Number(label="Sample Index", info="Index of the sample to be displayed", value=0, minimum=0, visible=False),
    )


def display_loading_message_for_details():
    return "<h3 style='text-align: center;'>Loading...</h3>"