app.py

import streamlit as st
from dotenv import load_dotenv
from streamlit_extras.add_vertical_space import add_vertical_space
from PyPDF2 import PdfReader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import HuggingFaceEmbeddings
from langchain.vectorstores import FAISS
import pickle
from langchain import HuggingFaceHub
from langchain.chains.question_answering import load_qa_chain
import os

def main(pdf):
    st.header('Chat With PDF')

    if pdf is not None:
        pdf_reader = PdfReader(pdf)

        text = ''
        for page in pdf_reader.pages:
            text += page.extract_text()

        text_splitter = RecursiveCharacterTextSplitter(
            chunk_size=1000,
            chunk_overlap=200,
            length_function=len
        )

        chunks = text_splitter.split_text(text=text)

        store_name = pdf.name[:-4]

        if os.path.exists(f'{store_name}.pkl'):
            with open(f'{store_name}.pkl', 'rb') as f:
                VectorStore = pickle.load(f)
        else:
            embeddings = HuggingFaceEmbeddings()
            VectorStore = FAISS.from_texts(chunks, embedding=embeddings)
            with open(f'{store_name}.pkl', 'wb') as f:
                pickle.dump(VectorStore, f)

        ask_query = st.text_input('Ask question about PDF: ')

        if ask_query:
            docs = VectorStore.similarity_search(query=ask_query, k=3)
            llm = HuggingFaceHub(repo_id="Salesforce/xgen-7b-8k-base", model_kwargs={"temperature": 0, "max_length": 64})
            chain = load_qa_chain(llm=llm, chain_type='stuff')
            response = chain.run(input_documents=docs, question=ask_query)
            st.write(response)

if __name__ == "__main__":
    load_dotenv()

    st.sidebar.title('LLM PDF Chats')
    st.sidebar.markdown('''
        ## About
        - This is LLM power chatbot
        - By [Prathamesh Shete]('https://www.linkedin.com/in/prathameshshete')
    ''')
    add_vertical_space(5)
    st.sidebar.write('Made By Prathamesh')

    pdf = st.file_uploader('Upload Your PDF', type='pdf')
    main(pdf)