LangChain

Build context-aware reasoning applications

★ 4.3

Framework for developing applications powered by language models. Chain LLMs together with tools, memory, and agents. The standard for LLM apps.

93K

GitHub Stars

supported

TypeScript

medium

Learning Curve

4.0

DX Score

Visitar Sitio Web → Ver Documentación GitHub

Precios

Model

free

Plan Gratuito

MIT licensed, fully open source

Paid

LangSmith for observability

Características

✓ LLM chains
✓ Agents and tools
✓ Memory systems
✓ RAG support
✓ Vector store integrations
✓ Document loaders
✓ Output parsers
✓ Callbacks and tracing
✓ LangGraph for workflows

Ventajas

+ Most popular LLM framework
+ Huge integration ecosystem
+ Active development
+ Great documentation
+ Strong community

Desventajas

- Abstraction can be heavy
- Frequent breaking changes
- Can be overkill for simple apps
- Performance overhead

Mejor Para

startup enterprise

llm ai agents rag chains