Learning LangChain (for True Epub)

Brief Table of Contents (Not Yet Final)
Preface
	Brief Primer on LLMs
		Instruction-tuned LLMs
	Dialogue-tuned LLMs
		Fine-tuned LLMs
	Brief Primer on Prompting
		Zero-shot Prompting
		Chain-of-thought
		Retrieval-augmented Generation
		Tool-calling
		Few-shot Prompting
	LangChain and Why It’s Important
	What to Expect from This Book
1. LLM Fundamentals with LangChain
	Getting Set Up with LangChain
	Using LLMs in LangChain
	Making LLM prompts reusable
	Getting Specific Formats out of LLMs
		JSON Output
		Other Machine-Readable Formats with Output Parsers
	Assembling the Many Pieces of an LLM Application
		Using the Runnable Interface
		Imperative Composition
		Declarative Composition
	Summary
2. Indexing: Preparing Your Documents for LLMs
	The Goal: Picking Relevant Context for LLMs
	Embeddings: Converting Text to Numbers
		Embeddings Before LLMs
		LLM-based Embeddings
		Semantic Embeddings Explained
	Converting Your Documents into Text
	Splitting Your Text Into Chunks
	Generating Text Embeddings
	Storing Embeddings in a Vector Store
		Getting set up with Pgvector
		Working with Vector Stores
	Tracking Changes to your Documents
	Summary