How to build a Streamlit UI for Local PDF RAG [Ollama models]
In this tutorial, we'll take our local Ollama PDF RAG (Retrieval Augmented Generation) pipeline to the next level by adding a sleek Streamlit UI! 🚀
We'll build on our previous PDF RAG project and create an interactive web application that allows users to upload a PDF, ask questions, and get accurate, context-aware answers. Here's what we'll cover:
✅ Quick recap of our previous RAG pipeline using Ollama and LangChain
✅ Implementing PDF upload functionality with visual feedback
✅ Creating an interactive Q&A interface with real-time responses
✅ Displaying PDF content alongside the Q&A interface
✅ Polishing the UI with error handling and user-friendly features
By the end of this tutorial, you'll have a user-friendly PDF Q&A application that combines the strength of RAG with the interactivity of Streamlit! 🎈
TIMESTAMPS:
============
0:00 - Introduction
0:30 - Project flowchart and recap of the previous project
5:32 - Preview of Streamlit UI for PDF RAG and code walkthrough
31:11 - Conclusion
31:15 - Outro
LINKS:
======
🔗 GitHub repo: https://github.com/tonykipkemboi/olla...
🔗 Streamlit documentation: https://docs.streamlit.io/
🔗 LangChain documentation: https://python.langchain.com/docs/get...
🔗 Be a member of this channel to get access to perks:
/ @tonykipkemboi
Follow me on socials:
==================
𝕏 → https://x.com/tonykipkemboi
LinkedIn → / tonykipkemboi
#Streamlit #RAG #Ollama #LangChain #PDF #NLP #MachineLearning #AI #LLM #WebApp