Build a RAG Pipeline with PyMuPDF4LLM, LlamaIndex, and LangChain | PDF Chatbot Tutorial скачать в хорошем качестве

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