Build RAG AI App with Gradio UI | Refactor Console Code to Web App(Pinec...

Build RAG AI App with Gradio UI | Refactor Console Code to Web App(Pinecone + Gemini + LangChain)| Part6

In Part 6 of this hands-on RAG (Retrieval-Augmented Generation) AI series, we refactor the console-based code from Part 4 and bring it to life with an interactive Gradio UI! 🛠️💻

You'll learn: 

✅ How to modularize and clean your RAG code

✅ How to build an interactive Gradio app

✅ How to query PDF documents using Pinecone + Gemini models

✅ Step-by-step integration of LangChain/PineCone Vector Database components with Gradio

📌 This video builds on Code wrote in Part4 & Decision made in Part 5, where we compared Streamlit vs. Gradio. Now, we take the Gradio path and implement it fully.

🔗 Watch previous parts here:

Part 1 (Theory & Concepts) 👉 https://youtu.be/E2YsOkIsihQ

Part 2 (Env Setup) 👉 https://youtu.be/DO_crG2LdOo

Part 3 (PDF to Vector DB) 👉 https://youtu.be/CJ9C00nj4X4

Part 4 (Console RAG Code) 👉 https://youtu.be/bXo7Few4gbU

Part 5 (Streamlit vs Gradio) 👉 https://youtu.be/KmRl1gjJq68

💡 Whether you're a beginner or an AI enthusiast, this project-based series will guide you to build your own AI-powered document Q&A system.

Upcoming Video : Part7 : Adding PDF upload with Followup question on uploaded pdf with Resolving Context Issue Of repeating same response