app.py

import streamlit as st
import re

from transformers import pipeline



st.title("Docs Answering AI App")
st.write("---")
st.write("### Give Doc Receipt Images to the AI and ask it whats on the receipt.")
st.warning("**Powered by AI Language Models...**")

st.write("---")

import streamlit as st
import pandas as pd
from io import StringIO

uploaded_file = st.file_uploader("Choose a file")
if uploaded_file is not None:
    # To read file as bytes:
    bytes_data = uploaded_file.getvalue()
    st.write(bytes_data)

    # To convert to a string based IO:
    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
    st.write(stringio)

    # To read file as string:
    string_data = stringio.read()
    st.write(string_data)

    # Can be used wherever a "file-like" object is accepted:
    dataframe = pd.read_csv(uploaded_file)
    st.write(dataframe)


nlp = pipeline(
    "document-question-answering",
    model="impira/layoutlm-document-qa",
)

res = nlp(
    "https://templates.invoicehome.com/invoice-template-us-neat-750px.png",
    "What is the invoice number?"
)

st.write(res['answer'])
# {'score': 0.9943977, 'answer': 'us-001', 'start': 15, 'end': 15}

res = nlp(
    "https://miro.medium.com/max/787/1*iECQRIiOGTmEFLdWkVIH2g.jpeg",
    "What is the purchase amount?"
)

st.write(res['answer'])