Agentic Node Graph Generator

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AI Summary

Summary: Agentic Workflow for Node Graph Generation

• Introduction:
  • Demonstrated an agentic workflow for creating node graphs.
  • Used Magpie workflow automation tool.
  • Aimed to clarify user intent and build a node graph from it.
• Process Overview:
  • Clarify Intent:
    • User provides an initial statement.
    • Chatbot clarifies the goal and suggests steps.
    • User confirms or adjusts the goal and steps.
  • Generate Graph:
    • Based on clarified intent, a node graph is suggested.
    • Graph includes potential steps and is validated by the user.
  • Validate Graph:
    • Checks if nodes exist, types match, and connections are correct.
    • Outputs a YAML file representing the graph.
• Tools and Techniques:
  • Used Claude from Anthropic for prompt engineering.
  • Implemented a step-by-step approach (Thought, Act, Observe).
  • Included reference workflows for context.
  • Used YAML for human-readable node and graph representation.
• Challenges and Solutions:
  • Initially struggled with node selection using RAG.
  • Moved to a simpler Python-based approach without LangChain.
  • Used a combination of handpicked nodes and reference workflows for graph generation.
• Potential Applications:
  • Can be adapted for various node-based applications like Houdini.
  • Encourages exploration of agentic workflows in different contexts.
• Conclusion:
  • The workflow serves as an onboarding tool for node graph creation.
  • It’s a starting point for users to refine and customize their workflows.
  • The code and methodology will be shared for further development and integration.