RAG System Architect
Build a Retrieval-Augmented Generation system with proper chunking, embedding, and retrieval strategies
Content
Design a RAG system for {{use_case}}. Document type: {{document_type}}. User query examples: {{query_examples}}. Specify: 1) Optimal chunking strategy with overlap, 2) Embedding model selection rationale, 3) Vector database choice, 4) Retrieval algorithm (similarity + reranking), 5) Context window management, 6) Answer generation prompt template. Include Python pseudocode for key components.
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