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import streamlit as st
from utils import st_def, ai
import openai, PyPDF2, os, time, pandas as pd
st_def.st_logo(title='👋 e-Recepit Extract')
tab1, tab2 = st.tabs(["Upload Receipt", "Display the Data"])
page_text = [] #array for page
with tab1:
st.markdown('An electronic receipt, commonly known as an e-receipt, is a digital version of a traditional paper receipt that is generated and delivered electronically. Instead of a tangible piece of paper, e-receipts are sent via electronic channels, such as email or mobile applications, as proof of a transaction. They include the same transaction information as paper receipts, such as the date, time, and items purchased.')
st.image("./data/invoice_Aaron Hawkins_38460.jpg")
pdf1 = st.file_uploader('Upload your e-Receipt: ', type='pdf')
#-----------------------------------------------
with st.spinner('loading ...'):
if pdf1:
doc_obj = PyPDF2.PdfReader(pdf1)
summary=' '
with st.spinner('Analyzing...'):
for i in range(0,len(doc_obj.pages)):
# creating a page object
pageObj = doc_obj.pages[i].extract_text() # extract one page's text
pageObj = pageObj.replace('\t\r','') # tab, enter
pageObj = pageObj.replace('\xa0','') # non-breaking spaces
# extracting text from page
page_text.append(pageObj) # the whole pdf --> txt
# st.session_state['page_text'] = page_text
st.success("Load successfully. Continue to next tab: Display")
else:
st.info("waiting for uploading ...")
with tab2:
if page_text is not None:
# st.write(type(page_text))
st.code(f'raw data: {page_text}')
else:
st.warning("Please upload a PDF to display the data.")
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