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