LangChain and LlamaIndex Projects Lab Book: Hooking Large Language Models Up to the Real World

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The LangChain and LlamaIndex projects contain excellent documentation and examples. The purpose of this book is to present additional material to learn from.

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Preface3 chapters

Begin part
  1. Preface

  2. The Stack We’re Building On

  3. Large Language Model Overview

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Part I: LangChain 1.0 and LangGraph 1.014 chapters

Begin part
  1. LangChain 1.0 in One Hour

  2. Swapping Between Local and Commercial Models

  3. RAG Patterns with LangChain

  4. Running Local LLMs Using Ollama

  5. Extraction of Facts and Relationships from Text Data

  6. Using LLMs to Summarize Text

  7. LangGraph 1.0 Fundamentals

  8. Building a ReAct Agent with LangGraph + Ollama

  9. Durable, Restart-Safe Agents

  10. Human-in-the-Loop Patterns

  11. Multi-Agent Supervisor Pattern

  12. Natural-Language SQLite

  13. DBpedia and Wikidata as Agent Tools

  14. A Perplexity-Style Local Search Agent

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Part II: LlamaIndex 0.14 and the Workflows API12 chapters

Begin part
  1. LlamaIndex

  2. Local Documents and Local Embeddings

  3. Choosing an Index Type

  4. RAG with Reranking

  5. The Workflows API

  6. Building an Agent as a Workflow

  7. Multi-Index Query Pipelines

  8. Structured Extraction

  9. Serving a Workflow with FastAPI

  10. Using LLMs To Organize Information in Our Google Drives

  11. Examples Using Hugging Face Open Source Models

  12. Book Wrap Up