Build a RAG Pipeline with PyMuPDF4LLM, LlamaIndex, and LangChain | PDF Chatbot Tutorial

#learnpython #programming #pdfautomation

In this tutorial, we’ll build a complete Retrieval-Augmented Generation (RAG) pipeline using PyMuPDF4LLM, LlamaIndex, LangChain, and a Large Language Model (LLM).

You’ll learn how to transform PDF documents into searchable, intelligent data sources that can answer natural language questions using their content.

Chapters
0:00 Introduction
0:27 Installing Required Packages
2:05 Converting PDFs with PyMuPDF4LLM
2:32 Chunking and Validating Text
3:21 Defining the Embedding Model
3:33 Creating the Vector Index and Retriever
3:55 Setting Up the LLM API
4:08 Building the RAG Chain
5:06 Running the QA Chain
5:30 Testing Source-Based Responses

Whether you’re building an AI assistant or exploring document-based retrieval systems, this step-by-step tutorial will help you master PDF-based RAG workflows in Python.

🔗 Helpful Resources:
• PyMuPDF Documentation: https://pymupdf.readthedocs.io/en/latest
• Code Examples: https://github.com/pymupdf/PyMuPDF-Ut...

#pymupdf4llm #langchain #llamaindex #rag #pythonai #pdfextraction #llmapplications #aiintegration #documentai #pymupdf #llm #pdfchatbot