Modern AI Engineering

Lesson 12.5 · 27 min · video lesson

LangChain: Composable Components for LLM Applications

Every LLM app needs the same plumbing (prompts, model calls, parsing, memory, retrieval, tools), so why write it from scratch every time?

In short: LangChain is an open-source framework (Python and JavaScript) that gives standard building blocks for LLM apps: models, prompt templates, output parsers, retrievers, memory helpers and tools, all sharing one interface so they can be snapped together into chains with the | operator. Under the hood a chain is just function composition: each component's output becomes the next one's input. We will see real LangChain code and then rebuild the core idea in 30 lines of plain Python.

What you will learn

  • What is LangChain?
  • Why do we need LangChain?
  • The core idea behind LangChain
  • LLM and Prompt Template
  • What is a Chain?
  • Output Parser
  • Memory
  • Retrieval and RAG
  • Tools and Agents
  • A complete flow of how LangChain works

In this lesson

  1. What is LangChain?
  2. Why do we need LangChain?
  3. The core idea: everything is a Runnable
  4. LLM and prompt template
  5. What is a chain? And output parsers
  6. Memory
  7. Retrieval and RAG
  8. Tools and agents
  9. Going one level deeper
  10. Practice: try it yourself
  11. A complete flow, and how LangChain compares

Key terms in this lesson

LangChain
An open-source framework of standard, composable components for building LLM applications.
Runnable
LangChain's common interface with invoke, batch and stream; prompts, models, parsers and chains are all Runnables.
LCEL
LangChain Expression Language: composing Runnables with the | operator.
Prompt template
A reusable prompt with named blanks that are filled from a dictionary at run time.
Output parser
A component that turns a model's reply into a string, JSON or typed object.
Retriever
A component that takes a query and returns relevant documents, often from a vector store.

This lesson is part of the Generative AI Engineering and Complete AI Engineer tracks. See plans and pricing to open the full lesson, its video, labs and quiz, or try the free lesson first (free account needed).

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