LangChain

Why It Matters

LangChain emerged as one of the first comprehensive frameworks for building LLM applications. It provides pre-built components for common patterns: chains (sequences of LLM calls), agents (LLMs that decide which tools to use), memory (conversation history management), and integrations with dozens of LLM providers and vector databases.

For new AI engineers, LangChain offers a faster learning curve. Instead of implementing retrieval, prompt templates, and output parsing from scratch, you can use LangChain’s abstractions. This accelerates prototyping and helps you understand the patterns before potentially building custom solutions.

The tradeoff is abstraction overhead. As applications grow more complex, LangChain’s generic interfaces can become limitations. Many experienced engineers start with LangChain for prototyping, then migrate to custom implementations or lighter alternatives for production systems where they need more control.

Implementation Basics

LangChain is organized around a few core concepts:

Chains are sequences of operations. A simple chain might format a prompt, call an LLM, and parse the output. Complex chains combine multiple LLM calls with conditional logic.

Agents let the LLM decide which tools to use. You define available tools (search, calculation, database queries), and the agent reasons about which to invoke based on the user’s question.

Memory maintains conversation context. Options range from simple buffer memory (store everything) to summary memory (LLM summarizes old conversations) to vector memory (semantic search over past messages).

Retrievers connect to data sources for RAG. LangChain integrates with most vector databases and provides document loaders for PDFs, web pages, and other formats.

Start with LangChain Expression Language (LCEL) for new projects since it’s the current recommended approach. Build simple chains first, add agents only when you need dynamic tool selection. Keep your prompts and business logic separate from LangChain’s abstractions so you can migrate easily if needed.