Workflow Diagram
Visual workflow diagrams for LLM pipelines
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What are LLM Workflow Diagrams?
LLM workflows visualize how data flows through AI pipelines—from user input through processing steps to final output. Understanding these patterns helps you design, debug, and optimize your AI applications.
This tool showcases three common workflow patterns used in production AI systems.
Workflow Patterns
RAG Pipeline
Query embedding → Vector search → Context building → Generation. The most common pattern for knowledge-grounded AI.
Agent Loop
Plan → Execute → Observe → Decide. Iterative pattern for autonomous task completion.
Prompt Chain
Sequential LLM calls where each step's output feeds the next. Good for complex multi-step transformations.
FAQ
When to use RAG vs Agents?
RAG for knowledge retrieval tasks. Agents for multi-step tasks requiring tool use and decision-making.
What's an optional step?
Steps like reranking can be skipped for simpler use cases but improve quality in production. Start simple, add complexity as needed.