Langchain: PDF Chat App (GUI) | ChatGPT for Your PDF FILES | Step-by-Step Tutorial

Introduction

In this tutorial, you will learn how to create a ChatGPT-powered PDF assistant using Langchain and Streamlit. This step-by-step guide will help you build an interactive application that allows users to ask questions about PDF documents and receive accurate answers, leveraging the capabilities of OpenAI's ChatGPT and Langchain's powerful features.

Step 1: Set Up Your Environment

To begin, ensure you have the necessary tools installed on your system.

1. Install Python: Make sure you have Python 3.7 or higher.
2. Install Necessary Libraries:
   • Open your terminal or command prompt.
   • Run the following command to install required libraries:

     pip install langchain streamlit openai PyPDF2
     

Step 2: Obtain OpenAI API Key

You will need an API key from OpenAI to access their LLM.

1. Sign Up: Go to the OpenAI website and create an account if you don't have one.
2. Generate API Key:
   • Navigate to the API section of your account.
   • Copy your API key, as you will need it in your application.

Step 3: Create the Streamlit App

Now, you will create a basic Streamlit application to handle the PDF interaction.

1. Create a New Python File: Create a file named app.py.
2. Set Up the Streamlit Interface:
   • Add the following code to your app.py file:

     import streamlit as st
     from langchain.embeddings import OpenAIEmbeddings
     from langchain.vectorstores import Chroma
     from langchain.chains import RetrievalQA
     from langchain.llms import OpenAI
     from PyPDF2 import PdfReader
     
     st.title("PDF Chat Assistant")
     uploaded_file = st.file_uploader("Choose a PDF file", type="pdf")
     
     if uploaded_file is not None:
         reader = PdfReader(uploaded_file)
         text = ""
         for page in reader.pages:
             text += page.extract_text()
         
         embeddings = OpenAIEmbeddings()
         vector_store = Chroma.from_texts([text], embeddings)
         qa_chain = RetrievalQA.from_chain_type(llm=OpenAI(temperature=0), retriever=vector_store.as_retriever())
     
         user_question = st.text_input("Ask a question about the PDF:")
         if user_question:
             answer = qa_chain.run(user_question)
             st.write(answer)
     

Step 4: Run Your Application

With the app set up, it's time to run it.

1. Run Streamlit: Use the following command in your terminal:

   streamlit run app.py
   

2. Access the App: Open a web browser and go to http://localhost:8501 to view your PDF Chat Assistant.

Step 5: Test the Application

Now that your application is running, test its functionality.

1. Upload a PDF: Choose a PDF file using the upload button in your app.
2. Ask Questions: Enter questions related to the content of the PDF.
3. View Responses: Check the answers provided by the ChatGPT model.

Conclusion

You have successfully built a ChatGPT-powered PDF assistant using Langchain and Streamlit. This application allows users to interact with PDF documents, leveraging advanced language processing capabilities. As next steps, consider refining the application by adding features such as:

• Support for multiple file types.
• Enhanced error handling.
• User authentication for secure access.

By exploring these enhancements, you can further improve the functionality and usability of your PDF Chat Assistant. Happy coding!