RAG Essentials



RAG Essentials :

  • How to split documents for embedding
  • How to Create high-quality embeddings.
  • How to choose vector store
  • How to search in order to retrieve most useful and relevance document from embedding (vector store)
  • How to retrieve the useful documents (filtering, compressing) before sending to LLM
  • How to efficiently splitting and chunking multiple documents for LLM input
  • How to create prompt to retrieve the answers