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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.") | |