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# 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')
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