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import random

import gradio as gr
from datasets import load_dataset

whoops = load_dataset("nlphuji/whoops")['test']
whoops = whoops.shuffle()

print(f"Loaded WMTIS, first example:")
print(whoops[0])
dataset_size = len(whoops)
print(f"dataset_size: {dataset_size}")

IMAGE = 'image'
IMAGE_DESIGNER = 'image_designer'
DESIGNER_EXPLANATION = 'designer_explanation'
CROWD_CAPTIONS = 'crowd_captions'
CROWD_EXPLANATIONS = 'crowd_explanations'
CROWD_UNDERSPECIFIED_CAPTIONS = 'crowd_underspecified_captions'
SELECTED_CAPTION = 'selected_caption'
COMMONSENSE_CATEGORY = 'commonsense_category'
QA = 'question_answering_pairs'
IMAGE_ID = 'image_id'
left_side_columns = [IMAGE]
right_side_columns = [x for x in whoops.features.keys() if x not in left_side_columns and x not in [QA]]
enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
emoji_to_label = {IMAGE_DESIGNER: '🎨, πŸ§‘β€πŸŽ¨, πŸ’»', DESIGNER_EXPLANATION: 'πŸ’‘, πŸ€”, πŸ§‘β€πŸŽ¨',
                  CROWD_CAPTIONS: 'πŸ‘₯, πŸ’¬, πŸ“', CROWD_EXPLANATIONS: 'πŸ‘₯, πŸ’‘, πŸ€”', CROWD_UNDERSPECIFIED_CAPTIONS: 'πŸ‘₯, πŸ’¬, πŸ‘Ž',
                  QA: '❓, πŸ€”, πŸ’‘', IMAGE_ID: 'πŸ”, πŸ“„, πŸ’Ύ', COMMONSENSE_CATEGORY: 'πŸ€”, πŸ“š, πŸ’‘', SELECTED_CAPTION: 'πŸ“, πŸ‘Œ, πŸ’¬'}
target_size = (1024, 1024)

columns_number = 3
rows_number = 10

def func(index):
    example = whoops[index]
    values = get_instance_values(example)
    return values


def get_instance_values(example):
    values = []
    for k in left_side_columns + right_side_columns:
        if k in enumerate_cols:
            value = list_to_string(example[k])
        elif k == QA:
            qa_list = [f"Q: {x[0]} A: {x[1]}" for x in example[k]]
            value = list_to_string(qa_list)
        else:
            value = example[k]
        values.append(value)
    return values


def list_to_string(lst):
    return '\n'.join(['{}. {}'.format(i + 1, item) for i, item in enumerate(lst)])

def create_image_accordion_block(index):
    example = whoops[index]
    instance_values = get_instance_values(example)
    assert len(left_side_columns) == len(
        instance_values[:len(left_side_columns)])  # excluding the image & designer
    for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
        if key == IMAGE:
            img = whoops[index]["image"]
            img_resized = img.resize(target_size)
            gr.Image(value=img_resized, label=whoops[index]['commonsense_category'])
        else:
            label = key.capitalize().replace("_", " ")
            gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
    with gr.Accordion("Click for details", open=False):
        assert len(right_side_columns) == len(
            instance_values[len(left_side_columns):])  # excluding the image & designer
        for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
            label = key.capitalize().replace("_", " ")
            gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")



with gr.Blocks() as demo:
    gr.Markdown(f"# Slide to iterate WHOOPS!")
    for row_num in range(0, rows_number):
        with gr.Row():
            for col_num in range(0, columns_number):
                with gr.Column():
                    index = random.choice(range(0, dataset_size))
                    create_image_accordion_block(index)
demo.launch()