langchain-rag
langchain-aiBuild RAG systems with grounded context.
RAG development
What it does
Builds retrieval-augmented generation systems that fetch relevant context for LLM responses.
When to use it
Invoke this skill when building any retrieval-augmented generation system.
How to use it
Give it a project and a RAG system goal; it returns an end-to-end pipeline that loads, splits, embeds, stores, retrieves, and generates.
What you provide
- a RAG system
- An existing project
Uses
Access · 2
This skill
OpenAI
Sends content to OpenAI
web pages
Reads web pages
What you need · 5
The implementation imports LangChain's OpenAI integration for chat models and embeddings.
The Python implementation imports community document loaders and vector stores.
The implementation imports RecursiveCharacterTextSplitter for chunking documents.
The Python implementation imports LangChain's Document type.
About this skill
- Visibility
- Public
- Repository
- langchain-ai/langchain-skills
- Created
- Oct 8, 2026
- Updated
- Oct 8, 2026
- Files
- 1