Managing multiple ai models in nested workflow functions?

My automation needs Claude for analysis but GPT-4 for response generation. Manually switching APIs in nested functions causes errors. How do you handle mixed AI models in complex workflows without constant API key management?

Latenode’s unified sub handles this. Just select models from dropdowns in each function node - no API keys. My workflow uses 3 different LLMs across 7 layers with zero config. All models available through one account: https://latenode.com

Implement a model routing layer that abstracts API management. Needs careful error handling for rate limits and output formatting differences between providers. Not trivial to build from scratch.

use wrapper functions with model selection params. keeps main logic clean but still need to manage keys unless platform handles it

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