import pandas as pd
from pathlib import Path
from ..styles import highlight_color


abs_path = Path(__file__).parent.parent.parent

def replace_models_names(model_name):
    if "gpt" in model_name:
        return model_name
    replaces = {'meta-llama': 'meta_llama',
        'epfl-llm':'epfl_llm',
        '01-ai':'01_ai'}
    new_name = model_name.replace('model-', '')
    for k, v in replaces.items():
        if new_name.startswith(k):
            new_name = new_name.replace(k, v)
    new_name = new_name.replace('-','/',1)
    new_name = new_name.replace('_','-',1)
    new_name = f"[{new_name}](https://huggingface.co/{new_name})"
    return new_name


def generate_order_list_and_data_types(json_data):
    order_list = ["model_name", "overall_accuracy"]
    data_types = ["markdown", "number"]

    for key in json_data.keys():
        if key not in ["model_name", "overall_accuracy"]:
            order_list.append(key)
            data_types.append("number")
    order_list[2:] = sorted(order_list[2:])
    return order_list, data_types

def filter_data(selected_columns, search_query):
    df = PES_ACCS[selected_columns]
    if search_query:
        df = df[df['model_name'].str.contains(search_query, case=False, na=False)]
    return df

def filter_columns(column_choices):
    selected_columns = [col for col in ORDER_LIST if col in column_choices]
    filtered_df = PES_ACCS[selected_columns]
    return filtered_df.style.highlight_max(color=highlight_color, subset=filtered_df.columns[1:]).format(precision=2)


def load_json_data(file_path, order_list):
    PES_ACCS = pd.read_json(file_path)
    for column in PES_ACCS.columns:
        if PES_ACCS[column].apply(type).eq(dict).any():
            PES_ACCS[column] = PES_ACCS[column].apply(str)

    PES_ACCS["model_name"] = PES_ACCS["model_name"].apply(
        lambda name: replace_models_names(name)
    )

    for column in PES_ACCS.select_dtypes(include='number').columns:
            PES_ACCS[column] = PES_ACCS[column].round(2)
    ordered_columns = [col for col in order_list if col in PES_ACCS.columns]
    PES_ACCS = PES_ACCS[ordered_columns]

    if "overall_accuracy" in PES_ACCS.columns:
        PES_ACCS = PES_ACCS.sort_values(by="overall_accuracy", ascending=False)

    return PES_ACCS
# file_path = str(abs_path / "leaderboards/pes_accuracy.json")
file_path = str(abs_path / "leaderboards/pes_accs.json")
with open(file_path, 'r', encoding='utf-8') as file:
    sample_data = pd.read_json(file_path).iloc[0].to_dict()  # Load the first row as a dict

ORDER_LIST, DATA_TYPES = generate_order_list_and_data_types(sample_data)
PES_ACCS = load_json_data(file_path, ORDER_LIST)
STYLED_PES_ACCS = PES_ACCS.style.highlight_max(
    color = highlight_color,
    subset=PES_ACCS.columns[1:]).format(precision=2)
COLUMN_HEADERS = ORDER_LIST

print('test')