app.py

import pdfminer
from pdfminer.high_level import extract_pages
from transformers import pipeline

import streamlit as st


def get_openai_response(question):
    response = pipeline("summarization", model="stevhliu/my_awesome_billsum_model")
    return response



## streamlit app

st.set_page_config(page_title="Trail Demo")
st.header("Sample")
st.write("UPDATE: This app uses the 'gpt-3.5-turbo-instruct' model through Langchain")


# input = st.text_input("Enter your query: ", key=input)
st.write(pdfminer.__version__)  

uploaded_file = st.file_uploader("Choose a file", "pdf")
if uploaded_file is not None:
    for page_layout in extract_pages(uploaded_file):
        for element in page_layout:
            df = element
response = get_openai_response(df)


submit = st.button("Generate")
if submit:
    st.subheader("The response is")
    st.write(response)