LangChain

Open-source framework for building applications on language models

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What is LangChain?

LangChain is an open-source framework for building applications on top of language models, published in Python and JavaScript by the company of the same name. It supplies the plumbing those apps need: prompt templates, model wrappers that swap between providers, document loaders and splitters for retrieval, output parsers and memory for multi-turn state. LangGraph extends this to stateful, branching agent workflows, while LangSmith traces and evaluates runs so prompts can be compared rather than guessed at. You still host and scale the result yourself.

Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.

Key features

Python and JavaScript libraries for chaining model calls and tools
LangGraph for stateful agent workflows with checkpointing
Document loaders, splitters and retrievers for retrieval pipelines
Provider-agnostic model wrappers that swap between vendors
LangSmith tracing and evaluation over prompts and agent runs
Prompt templates, output parsers and structured response helpers

Pros & cons

Strengths

Saves real time when an app needs retrieval and tools
Swapping model providers is close to a config change
Tracing makes prompt changes measurable instead of guessed

Watch out for

Abstractions shift between releases and break old examples
It is a library: hosting and scaling remain your problem
Simple API calls often need no framework at all

Best for & use cases

llm application development, retrieval pipelines, agent orchestration and prompt evaluation

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FAQ

Do I need LangChain to call a model?

No. A single API call is fine with a vendor SDK. The framework earns its place when an application needs retrieval, multi-step tool use, conversation state or tracing across many calls, and even then it is a choice rather than a requirement.

Is it free to use?

The libraries are open source and free. Related hosted services for tracing, evaluation and deployment have their own free allowances and paid tiers, so budget separately if you use those rather than running the open components yourself.

Why do tutorials break so often?

The project moves quickly and abstractions get renamed between releases, so older examples stop working. Pin versions in a project, read the changelog before upgrading, and expect to rewrite parts of a chain on a major release.