AI Engineer's Guide to Langchain
The Langchain library is a powerful tool for AI engineering, acting as the foundation of the broader LangChain-ecosystem (that is, LangGraph, LangSmith, LangServe, etc). In this course, you'll learn the fundamentals of building with LLMs and the essentials of LangChain — allowing you to build modern agentic systems and potentially move onto other components in the ecosystem such as LangGraph.
by Joshua & James Briggs
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Chapter 1
When to Use LangChain
Guidelines for when we should use LangChain and what problems the framework does and does not solve.
Chapter 2
Getting Started with LangChain
LangChain is one of the most popular open source libraries for AI Engineers. Here we will introduce the library.
Chapter 3
AI Observability with LangSmith
An introduction to LangSmith, an observability service for the LangChain-ecosystem.
Chapter 4
Prompt Templating and Techniques in LangChain
Prompting is a critical part of building AI software. Here we'll learn general prompting techniques and specific LangChain tooling for prompting.
Chapter 5
Conversational Memory in LangChain
Exploring the various types of conversational memory and best practices for implementing them in LangChain v0.3 and beyond.
Chapter 6
Introduction to LangChain Agents
An introduction to LangChain's agents in v0.3 and up using both traditional and LCEL syntax.
Chapter 7
LangChain Agent Executor Deep Dive
A deep dive into LangChain's Agent Executor, exploring how to build your custom agent execution loop in LangChain v0.3.
Chapter 8
LangChain Expression Language (LCEL)
An introduction to LangChain's Expression Language (LCEL), the recommended syntax for building agents and chains.
Chapter 9
LangChain Streaming
All you need to know about streaming, allowing us to receive, parse, and send LLM-generated data in real-time.