# import urllib.request
# import streamlit as st
# import os
# from datasets import load_from_disk
# import requests
# with urllib.request.urlopen('https://huggingface.co/datasets/Seetha/Visualization') as response:
#     data = response.read()

# with open('./level2.json','r+') as fi:
#     data = fi.read()
#     st.write('before change', data)
#     fi.seek(0)
#     fi.write('Hello world!')
#     fi.truncate()
#     st.write(os.path.abspath("./level2.json"))

# with open('./level2.json','w') as dat:
#     dat.write('hello hello')
#     #st.write(data_after)

# # bin_file = open('./level2.json', 'rb')

# # # Execute the request
# # response = requests.post('https://huggingface.co/datasets/Seetha/Visualization', files={'file': bin_file})

# # # Close the file
# # bin_file.close()

# from datasets import load_dataset

# # Load the dataset
# dataset = load_dataset("Seetha/Visualization")

# # Make changes to the dataset
# # ...

# # Save the changed dataset to a file
# dataset.save_to_disk('./level.json')

# # In your Streamlit app, load the dataset from the file
# dataset = load_dataset('json', data_files='./level.json')

import streamlit as st
import urllib # the lib that handles the url stuff
from PyPDF2 import PdfReader
text_list = []

target_url = 'https://huggingface.co/datasets/Seetha/Visualization/raw/main/AFLAC_Wyatt_notag.pdf'
if st.button('PDF1'):
    data = urllib.request.urlopen(target_url)
    for line in data.read():
        st.write(line)
    if data is not None:
        reader = PdfReader(data)
        for page in reader.pages:
            text = page.extract_text()
            text_list.append(text)
            st.write(text_list)
    else:
         st.error("Please upload your own PDF to be analyzed")
         st.stop()
else:
    st.write('Goodbye')