app.py

import streamlit as st
from dotenv import load_dotenv
from PyPDF2 import PdfReader
from langchain.text_splitter import CharacterTextSplitter
from langchain.embeddings import OpenAIEmbeddings
from langchain_community.vectorstores import FAISS
from langchain.memory import ConversationBufferMemory
from langchain_community.chat_models import ChatOpenAI
from langchain.chains.conversational_retrieval.base import ConversationalRetrievalChain
from htmlTemplates import css, bot_template, user_template

def get_pdf_text(pdf_docs):
    text = ""
    for pdf in pdf_docs:
        pdf_reader = PdfReader(pdf) #creates a pdf object that has pages
        for page in pdf_reader.pages:
            text += page.extract_text()
    return text

def get_text_chunks(raw_text):
    text_splitter = CharacterTextSplitter(
        separator="\n",
        chunk_size = 1000,
        chunk_overlap = 200,
        length_function = len
    )
    chunks = text_splitter.split_text(raw_text)
    return chunks

def get_vector_store(text_chunks):
    embeddings = OpenAIEmbeddings()
    vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
    return vectorstore

def get_conversation_chain(vectorstore):
    llm = ChatOpenAI()
    memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
    conversation_chain = ConversationalRetrievalChain.from_llm(
        llm=llm,
        retriever=vectorstore.as_retriever(),
        memory=memory
    )
    return conversation_chain

def handle_user_input(user_question):
    response = st.session_state.conversation({'question':user_question})
    st.session_state.chat_history = response['chat_history']

    for i, message in enumerate(st.session_state.chat_history):
        if i % 2 == 0:
            st.write(user_template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
        else:
            st.write(bot_template.replace("{{MSG}}", message.content), unsafe_allow_html=True)

def main():
    load_dotenv()
    st.set_page_config(page_title="Chat with Multiple PDFs", page_icon=":books:")
    st.write(css, unsafe_allow_html=True)

    if "conversation" not in st.session_state:
        st.session_state.conversation = None

    if "chat_history" not in st.session_state:
        st.session_state.chat_history = None

    st.header("Chat with Multiple PDFs :books:")
    user_question = st.text_input("Ask a question about your documents:")
    if user_question:
        handle_user_input(user_question)

    with st.sidebar:
        st.subheader("Your documents")
        pdf_docs = st.file_uploader("Upload your files here and click on 'Process'", accept_multiple_files=True)
        if st.button("Process"):
            with st.spinner("Processing"):   #shows a spinner making it user friendly
                #get the raw text from pdfs
                raw_text = get_pdf_text(pdf_docs)
                #get the text chunks from raw text
                text_chunks = get_text_chunks(raw_text)
                vectorstore = get_vector_store(text_chunks)
                st.session_state.conversation = get_conversation_chain(vectorstore)
                #session_state ensures variable does not get re intialize after a reload for same session

if __name__ == "__main__":
    main()