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rag-infrastructure
Build and operate Retrieval-Augmented Generation (RAG) infrastructure with vector stores, embedding pipelines, and hybrid search. Covers ingestion, chunking strategies, reranking, and production deployment patterns.
infrastructure/local-ai/rag-infrastructure/SKILL.md
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# RAG Infrastructure
Production infrastructure for Retrieval-Augmented Generation: ingest documents, generate embeddings, store in vector databases, and serve grounded LLM responses.
## When to Use This Skill
Use this skill when:
- Building a knowledge base Q&A system over internal documents
- Implementing semantic search over large document collections
- Reducing LLM hallucinations with retrieved context
- Setting up embedding pipelines and vector store infrastructure
- Deploying hybrid search (dense + sparse/BM25)
## Prerequisites