Ask AI Questions From Your PDF Using Python + RAG - Part2

Description:

In Part 2 of the NotebookLM Clone series, we complete the core feature — asking AI questions from your own PDF or text file.
Using Retrieval-Augmented Generation (RAG), we fetch the most relevant chunks from the stored document and feed them to a small Google model (FLAN-T5) to generate accurate answers.

What we build in this video:

Semantic search with ChromaDB

Retrieving relevant text chunks

Creating a prompt with document context

Answer generation using FLAN-T5

Displaying answers and citation-like sources

By the end, you’ll have a fully working NotebookLM-style feature in Python — upload → store → ask → answer.

📌 Code link:
https://github.com/techXion-code/ai-code-samples/tree/main/Mini%20NotebookLM
📌 Part 1: Upload & Store PDFs (linked below)
https://www.youtube.com/watch?v=6HC8VIedCJw&t=265s&pp=0gcJCSIKAYcqIYzv

#coding #pythonprogramming #pythonprojects #vectordatabase #ChromaDB #aitutorial #notebooklm #learnpythonprogramming #learnai #rag #retrievalaugmentedgeneration #googleai #huggingface #transformers #flan-t5 #nlp #aiagent

Видео Ask AI Questions From Your PDF Using Python + RAG - Part2 канала TechXion