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
SQL to NoSQL Migration Planner
Plan migration from relational to document databases
On-Device AI App Feature Planner
Plans a mobile app feature set that runs entirely on-device using small AI models like Gemma 4 or Llama, with offline-first architecture and privacy-by-design principles.
AI Debugging Chain-of-Thought Assistant
Apply systematic chain-of-thought reasoning to diagnose and fix complex bugs, with step-by-step analysis, hypothesis testing, and a clear fix with explanation.
Bug Report Triage Assistant
Analyze and categorize bug reports for efficient debugging