AI Agent Architecture With RAG Diagram
This diagram shows how an AI agent combines a planning loop, external tools, and retrieval-augmented generation to answer complex queries. It's useful for designing or explaining agentic AI systems to engineering teams. Tip: draw the planning loop as a cycle to make clear that agents can call tools multiple times before finalizing an answer.
The prompt behind this diagram
Design an AI agent architecture diagram with a User Interface accepting requests, an Agent Orchestrator/Planner deciding next actions, a Tool Selection module connecting to external Tools (Web Search, Calculator, Code Executor), a Retrieval-Augmented Generation module that queries a Vector Database for relevant context, a Large Language Model core reasoning engine, a Memory Store maintaining conversation history, and an Output Formatter returning the final response to the user. Show the orchestrator looping back to the LLM after each tool call until a final answer is produced.
Paste your own description (or Terraform / docker-compose / SQL schema) into draft1 and get a diagram like this for your exact system.
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