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.
Related Prompts
REST API Documentation Writer
Generates complete, developer-friendly REST API documentation from endpoint details including request/response examples, error codes, and authentication.
RAG Knowledge Base Query Optimizer
Optimize queries for retrieval-augmented generation systems
API Endpoint Designer
Design RESTful API endpoints with proper naming, methods, and documentation
Edge Case Explorer
Generate comprehensive edge cases and boundary condition tests for any system