Langchain Rag
langchain-ai/langchain-skillsRetrieval Augmented Generation (RAG) makes AI answers smarter by adding your own documents. Instead of guessing, the AI pulls relevant facts from a knowledge base. This skill helps you build that pipeline step by step.
You load files, split them into small chunks, and turn each chunk into a vector. A vector store keeps these numbers ready for fast search. When a question comes in, the system finds the best matching chunks and feeds them to the language model.
The result is a grounded answer based on your data. You can use tools like LangChain, OpenAI embeddings, and vector stores such as Chroma, FAISS, or Pinecone. No need to be a machine learning expert to get started.
Add Langchain Rag skill to your workflow
Global
mkdir -p ~/.claude/skills/langchain-ragProject
mkdir -p .claude/skills/langchain-ragSource Repository
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