Building a Streamlit PDF Chat App: Chatting with PDFs Using RAG, LangChain, and Ollama

Building a Streamlit PDF Chat App: Chatting with PDFs Using RAG

In this episode of Just Code It, we take you step-by-step through the process of creating a dynamic PDF chat application using Streamlit and Retrieval-Augmented Generation (RAG).

Here’s what you’ll learn:
✅ Setting up the app configuration and page structure.
✅ Initializing state variables for seamless interaction.
✅ Handling PDF uploads and processing documents efficiently.
✅ Creating vector databases for document search and retrieval.
✅ Developing the chat interface for real-time interaction.

With detailed explanations and hands-on coding, this tutorial ensures you understand each component of the app. Follow along with the complete source code available on GitHub and see how to debug and optimize your application using helpful tips and techniques.

Highlights of the video:
🎯 Comprehensive walkthrough of RAG-based chat functionality.
🎯 Practical implementation of Streamlit features.
🎯 Guidance on managing vector databases for enhanced search performance.
⏰ Video Chapters

00:00 Introduction to the Streamlit Chat App
00:22 Overview of the Template Structure
01:58 Configuring the App and State Variables
03:07 Setting Up the Model
03:42 Processing the PDF
06:38 Creating the Chat Interface
06:49 Handling the Sidebar and User Inputs
09:57 Final Touches and Debugging
14:51 Walkthrough and Testing the App
15:21 Conclusion and Next Steps


🛠️ Resources & Links
🔗 Source Code: https://github.com/jamesbmour/blog_tutorials
🔗 More Streamlit Tutorials: https://www.youtube.com/@justcodeit77
🍻 Support My Work: https://buymeacoffee.com/bmours

💡 Tags
#python #streamlit #chatbots #AI #LangChain #OpenAI #webappdevelopment #interactiveapps #codingtutorial #webdevelopment #coding #langchain #openai #ollama