# Langchain

> Build LLM-powered applications with modular components for chains, agents, memory, and retrieval, supporting Python and JavaScript frameworks.

- Skill: `neuralblitz/langchain` (Agent Skill)
- Install (CLI): `npx skillmds@latest add neuralblitz/langchain`
- Raw SKILL.md: https://api.skillmd.com/api/skills/neuralblitz/langchain/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML, Agent Building, Prompt Engineering, RAG & Embeddings
- Tags: Document Loaders, Embeddings, Langchain, Llm Chains, Prompt Templates, Vector Stores
- Author: NeuralBlitz (https://skillmd.com/u/neuralblitz)
- Updated: 2026-08-22
- Page: https://skillmd.com/skills/neuralblitz/langchain

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# LangChain

LangChain is a framework for developing applications powered by large language models (LLMs). It provides modular components for chains, agents, and memory management.

## Key Concepts

- LLM interfaces
- Prompt templates
- Chains and agents
- Document loaders
- Vector stores and embeddings

## Common Use Cases

- Chatbot applications
- RAG (Retrieval Augmented Generation)
- Question answering systems
- Autonomous agents
- Document processing

## Best Practices

- Use proper prompt engineering
- Implement proper memory
- Handle errors gracefully
- Cache LLM responses
- Test with mock LLMs

## Resources

- Python: python.langchain.com
- JS: js.langchain.com
- Related Skills: llm, rag, openai