# import gradio as gr
# import ast
# import requests
#
# # Using Gradio Demos as API - This is Hot!
# API_URL_INITIAL = "https://ysharma-playground-ai-exploration.hf.space/run/initial_dataframe"
# API_URL_NEXT10 = "https://ysharma-playground-ai-exploration.hf.space/run/next_10_rows"
#
#
# # define inference function
# # First: Get initial images for the grid display
# def get_initial_images():
#     response = requests.post(API_URL_INITIAL, json={
#         "data": []
#     }).json()
#     # data = response["data"][0]['data'][0][0][:-1]
#     response_dict = response['data'][0]
#     return response_dict  # , [resp[0][:-1] for resp in response["data"][0]["data"]]
#
#
# # Second: Process response dictionary to get imges as hyperlinked image tags
# def process_response(response_dict):
#     return [resp[0][:-1] for resp in response_dict["data"]]
#
#
# response_dict = get_initial_images()
# initial = process_response(response_dict)
# initial_imgs = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);">\n' + "\n".join(
#     initial[:-1])
#
#
# # Third: Load more images for the grid
# def get_next10_images(response_dict, row_count):
#     row_count = int(row_count)
#     # print("(1)",type(response_dict))
#     # Convert the string to a dictionary
#     if isinstance(response_dict, dict) == False:
#         response_dict = ast.literal_eval(response_dict)
#     response = requests.post(API_URL_NEXT10, json={
#         "data": [response_dict, row_count]  # len(initial)-1
#     }).json()
#     row_count += 10
#     response_dict = response['data'][0]
#     # print("(2)",type(response))
#     # print("(3)",type(response['data'][0]))
#     next_set = [resp[0][:-1] for resp in response_dict["data"]]
#     next_set_images = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); ">\n' + "\n".join(
#         next_set[:-1])
#     return response_dict, row_count, next_set_images  # response['data'][0]
#
#
# # get_next10_images(response_dict=response_dict, row_count=9)
# # position: fixed; top: 0; left: 0; width: 100%; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
#
# # Defining the Blocks layout
# with gr.Blocks(css="""#img_search img {width: 100%; height: 100%; object-fit: cover;}""") as demo:
#     gr.HTML(value="top of page", elem_id="top", visible=False)
#     gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
#         <div
#         style="
#             display: inline-flex;
#             align-items: center;
#             gap: 0.8rem;
#             font-size: 1.75rem;
#         "
#         >
#         <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
#             Using Gradio Demos as API - 2 </h1><br></div>
#         <div><h4 style="font-weight: 500; margin-bottom: 7px; margin-top: 5px;">
#             Stream <a href="https://github.com/playgroundai/liked_images" target="_blank">PlaygroundAI Images</a> ina beautiful grid</h4><br>
#         </div>""")
#     # with gr.Accordion(label="Details about the working:", open=False, elem_id='accordion'):
#     #     gr.HTML("""
#     #     <p style="margin-bottom: 10px; font-size: 90%"><br>
#     #     ▶️Do you see the "view api" link located in the footer of this application?
#     #     By clicking on this link, a page will open which provides documentation on the REST API that developers can use to query the Interface function / Block events.<br>
#     #     ▶️In this demo, I am making such an API request to the <a href="https://huggingface.co./spaces/ysharma/Playground_AI_Exploration" target="_blank">Playground_AI_Exploration</a> Space.<br>
#     #     ▶️I am exposing an API endpoint of this Gradio app as well. This can easily be done by one line of code, just set the api_name parameter of the event listener.
#     #     </p></div>""")
#
#     with gr.Column():  # (elem_id = "col-container"):
#         b1 = gr.Button("Load More Images").style(full_width=False)
#         df = gr.Textbox(visible=False, elem_id='dataframe', value=response_dict)
#         row_count = gr.Number(visible=False, value=19)
#         img_search = gr.HTML(label='Images from PlaygroundAI dataset', elem_id="img_search",
#                              value=initial_imgs)  # initial[:-1] )
#
#     gr.HTML('''<center><a href="https://huggingface.co./spaces/ysharma/Stream_PlaygroundAI_Images?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a></center>
#     #     </p></div>''')
#     b1.click(get_next10_images, [df, row_count], [df, row_count, img_search], api_name="load_playgroundai_images")
#
# demo.launch(debug=True)

import pandas as pd
import gradio as gr

df = pd.read_csv("/Users/yonatanbitton/Downloads/whoops_dataset.csv")
df['image_url'] = df['image_url'].apply(lambda x: '<a href= "' + str(x) + '" target="_blank"> <img src= "' + str(
    x) + '"/> </a>')
df['designer_explanation'] = df['designer_explanation'].apply(lambda x: str(x))
df['selected_caption'] = df['selected_caption'].apply(lambda x: str(x))
df['crowd_captions'] = df['crowd_captions'].apply(lambda x: str(x))
df['crowd_underspecified_captions'] = df['crowd_underspecified_captions'].apply(lambda x: str(x))
df['question_answering_pairs'] = df['question_answering_pairs'].apply(lambda x: str(x))
df['commonsense_category'] = df['commonsense_category'].apply(lambda x: str(x))
df['image_id'] = df['image_id'].apply(lambda x: str(x))
df['image_designer'] = df['image_designer'].apply(lambda x: str(x))
df = df[['image_url', 'designer_explanation', 'selected_caption', 'crowd_captions', 'crowd_underspecified_captions',
         'question_answering_pairs', 'commonsense_category', 'image_id', 'image_designer']]

LINES_NUMBER = 20

def display_df():
    df_images = df.head(LINES_NUMBER)
    return df_images


def display_next10(dataframe, end):
    start = (end or dataframe.index[-1]) + 1
    end = start + (LINES_NUMBER-1)
    df_images = df.loc[start:end]
    return df_images, end


# Gradio Blocks
with gr.Blocks() as demo:
    gr.Markdown("<h1><center>WHOOPS! Dataset Viewer</center></h1>")

    with gr.Row():
        num_end = gr.Number(visible=False)
        b1 = gr.Button("Get Initial dataframe")
        b2 = gr.Button("Next 10 Rows")

    with gr.Row():
        out_dataframe = gr.Dataframe(wrap=True, max_rows=LINES_NUMBER, overflow_row_behaviour="paginate",
                                     datatype=["markdown", "markdown", "str", "str", "str", "str", "str", "str","str","str"],
                                     interactive=False)

    b1.click(fn=display_df, outputs=out_dataframe, api_name="initial_dataframe")
    b2.click(fn=display_next10, inputs=[out_dataframe, num_end], outputs=[out_dataframe, num_end],
             api_name="next_10_rows")

demo.launch(debug=True, show_error=True)