RAG (pour débutants)
RAG = Retrieval-Augmented Generation. Before answering, the LLM 'reads' relevant documents from your base. Result: it answers from YOUR data, not its training memory.
Strengths
- No fine-tuning, instant data updates, no retraining
Limitations
- Quality depends on chunking and the embedding model
Best for
- Any project that needs to answer from a private knowledge base