Structured Code Objects, Not Text Strings, Power This n8n Workflow Generator

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A developer building an n8n automation generator chose to represent workflows as typed Python objects — N8NWorkflow, N8NNode, and connection records — rather than assembling raw text or JSON strings. The approach enforces strict enumeration of supported node types and agent templates, meaning unsupported configurations fail visibly in Python before any broken file can be exported. Agent configurations are defined through a dedicated AgentConfig dataclass, keeping fields like system prompt, tools, model choice, and temperature explicitly separated rather than bundled loosely. This structure slows down quick experiments but eliminates a category of silent errors where an importable workflow file looks valid yet behaves incorrectly. The generator ultimately maps discovered automations to concrete n8n nodes only when sufficient context exists, and computes canvas positioning independently from node identity to keep layouts readable.

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