Design a Retrieval-Augmented Generation (RAG) system for a legal document analysis tool. Explain the choice of embedding model for vectorizing legal text, the vector database schema, and the retrieval strategy (e.g., hybrid search with keyword matching). Detail how you will construct the prompt context to manage token limits and minimize hallucinations, and describe how to evaluate the relevance of retrieved chunks.