pguso/rag-from-scratch

핵심 기능

• 01Step-by-step examples from document loading to LLM answer generation
• 02In-memory vector store with nearest-neighbor search and metadata filtering
• 03Hybrid search combining vector similarity with BM25 keyword scoring
• 04Multi-query retrieval with reciprocal rank fusion and deduplication
• 05Query rewriting with heuristic and local LLM options via node-llama-cpp
• 06Reusable library modules for loaders, splitters, embeddings, and vector stores

활용 사례

• Learning how RAG works internally before adopting a framework like LangChain
• Building a local question-answering prototype over your own documents without cloud APIs
• Experimenting with retrieval strategies such as hybrid search or query rewriting
• Teaching embeddings and vector search to a team of JavaScript developers

토픽

자주 묻는 질문

rag-from-scratch은(는) 무엇인가요?

An educational JavaScript tutorial that builds retrieval-augmented generation step by step with local LLMs and no cloud APIs.

rag-from-scratch은(는) 무료로 사용할 수 있나요? 라이선스는 무엇인가요?

rag-from-scratch은(는) MIT 라이선스의 오픈소스입니다. 상업용 제품에 사용하기 전에 라이선스 조건을 확인하세요.

rag-from-scratch은(는) 아직 유지보수되고 있나요?

6개월 이상 커밋 없음. rag-from-scratch의 마지막 커밋은 2026년 3월 11일입니다.

rag-from-scratch은(는) 어디에 사용할 수 있나요?

Learning how RAG works internally before adopting a framework like LangChain Building a local question-answering prototype over your own documents without cloud APIs Experimenting with retrieval strategies such as hybrid search or query rewriting Teaching embeddings and vector search to a team of JavaScript developers

rag-from-scratch은(는) 어디서 받을 수 있나요?

소스 코드와 설치 방법은 GitHub에 있습니다: https://github.com/pguso/rag-from-scratch