Automated AI Model Fallback System in n8n

This n8n workflow automates the process of selecting and utilizing different AI language models based on their success or failure rates. The main goal is to dynamically choose the most appropriate AI model for a task, with automatic fallback options if a model fails. The workflow begins with a manual trigger, allowing users to initiate the process. It includes nodes that define variables to manage model options and failure counts, as well as nodes representing different AI models such as GPT-4 and Google Gemini. When an AI request is made, the ‘Fallback Models’ node evaluates the number of failures and selects the next available model from a list. Sticky notes guide users on configuring the AI models, defining prompts, and setting up error handling and retries, making this workflow highly useful for dynamic AI model management, troubleshooting, and ensuring reliable AI responses in automation scenarios.