import streamlit as st
import numpy as np
import random
import pandas as pd
import glob
import csv
from PIL import Image
from datasets import load_dataset, Dataset, load_from_disk
from huggingface_hub import login
import os


class GalleryApp:
    def __init__(self, promptBook):
        self.promptBook = promptBook
        st.set_page_config(layout="wide")


    def gallery(self, items, col_num, info):
        cols = st.columns(col_num)
        # # sort items by brisque score
        # items = items.sort_values(by=['brisque'], ascending=True).reset_index(drop=True)
        for idx in range(len(items)):
            with cols[idx % col_num]:
                image = st.session_state.images[items.iloc[idx]['row_idx'].item()]['image']
                st.image(image,
                         use_column_width=True,
                )
                for key in info:
                    st.write(f"**{key}**: {items.iloc[idx][key]}")

    def app(self):
        st.title('Model Coffer Gallery')
        st.write('This is a gallery of images generated by the models in the Model Coffer')

        metadata, images = st.columns([1, 3])
        # with images:
            # prompt_tags = self.promptBook['tag'].unique()
            # # sort tags by alphabetical order
            # prompt_tags = np.sort(prompt_tags)
            #
            # selecters = st.columns(3)
            # with selecters[0]:
            #     tag = st.selectbox('Select a tag', prompt_tags)

        with metadata:
            prompt_tags = self.promptBook['tag'].unique()
            # sort tags by alphabetical order
            prompt_tags = np.sort(prompt_tags)

            tag = st.selectbox('Select a tag', prompt_tags)

            items = self.promptBook[self.promptBook['tag'] == tag].reset_index(drop=True)

            prompts = [', '.join(x.split(', ')[4:]) for x in items['prompt'].unique()]
            prompt = st.selectbox('Select prompt', prompts)

            idx = prompts.index(prompt)
            prompt_full = ', '.join(items['prompt'].unique()[idx].split(', ')[:4]) + ', ' + prompt

            prompt_id = items[items['prompt'] == prompt_full]['prompt_id'].unique()[0]
            items = items[items['prompt_id'] == prompt_id].reset_index(drop=True)

            st.write('**Prompt ID**')
            st.caption(f"{prompt_id}")
            st.write('**Prompt**')
            st.caption(f"{items['prompt'][0]}")
            st.write('**Negative Prompt**')
            st.caption(f"{items['negativePrompt'][0]}")
            st.write('**Sampler**')
            st.caption(f"{items['sampler'][0]}")
            st.write('**cfgScale**')
            st.caption(f"{items['cfgScale'][0]}")
            st.write('**Size**')
            st.caption(f"width: {items['size'][0].split('x')[0]}, height: {items['size'][0].split('x')[1]}")
            st.write('**Seed**')
            st.caption(f"{items['seed'][0]}")

        with images:
            selecters = st.columns([1, 1, 2])
            # with selecters[0]:
            with selecters[0]:
                sort_by = st.selectbox('Sort by', items.columns[11: -1])

            with selecters[1]:
                order = st.selectbox('Order', ['Ascending', 'Descending'], index=1 if sort_by == 'clip_score' or sort_by == 'model_download_count' else 0)
                if order == 'Ascending':
                    order = True
                else:
                    order = False

            items = items.sort_values(by=[sort_by], ascending=order).reset_index(drop=True)
            with selecters[2]:
                info = st.multiselect('Show Info',
                                      ['brisque_score', 'clip_score', 'model_download_count', 'model_name', 'model_id',
                                       'modelVersion_name', 'modelVersion_id'],
                                      default=sort_by)
            # if sort_by not in info:
            #     info.append(sort_by)

            col_num = st.slider('Number of columns', min_value=1, max_value=9, value=4, step=1, key='col_num')
            self.gallery(items, col_num, info)
        # st.write(items)


if __name__ == '__main__':
    login(token=os.environ.get("HF_TOKEN"))

    if 'roster' not in st.session_state:
        print('loading roster')
        # st.session_state.roster = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferRoster', split='train'))
        st.session_state.roster = pd.DataFrame(load_from_disk(os.path.join(os.getcwd(), 'data', 'roster')))
        st.session_state.roster = st.session_state.roster[['model_id', 'model_name', 'modelVersion_id', 'modelVersion_name',
                                          'model_download_count']].drop_duplicates().reset_index(drop=True)
    # add model download count from roster to promptbook dataframe
    if 'promptBook' not in st.session_state:
        print('loading promptBook')

        st.session_state.promptBook = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferMetadata', split='train'))
        st.session_state.images = load_from_disk(os.path.join(os.getcwd(), 'data', 'promptbook'))
        print('images loaded')
        # st.session_state.promptBook = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferPromptBook', split='train'))
        st.session_state.promptBook = st.session_state.promptBook.merge(st.session_state.roster[['model_id', 'model_name', 'modelVersion_id', 'modelVersion_name', 'model_download_count']], on=['model_id', 'modelVersion_id'], how='left')

        # add column to record current row index
        st.session_state.promptBook['row_idx'] = st.session_state.promptBook.index
        print('promptBook loaded')
    # print(st.session_state.promptBook)

    check_roster_error = False
    if check_roster_error:
        # print all rows with the same model_id and modelVersion_id but different model_download_count in roster
        print(st.session_state.roster[st.session_state.roster.duplicated(subset=['model_id', 'modelVersion_id'], keep=False)].sort_values(by=['model_id', 'modelVersion_id']))

    app = GalleryApp(promptBook=st.session_state.promptBook)
    app.app()