Dynamic LLM Switching & Intelligent Fallback
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This workflow enables dynamic selection and switching between multiple Large Language Models (LLMs) based on input, providing intelligent fallback mechanisms in case of errors. Optimize performance and ensure resilience in your AI applications.
About This Workflow
In today's fast-evolving AI landscape, relying on a single Large Language Model can lead to rigidity and potential service disruptions. This n8n workflow offers a sophisticated solution by allowing you to dynamically switch between different LLMs, such as various OpenAI models, based on specific criteria from your input. Beyond simple selection, it incorporates an intelligent fallback system: if a chosen LLM encounters an error, the workflow automatically attempts to use the next available model, ensuring uninterrupted service. This design is crucial for A/B testing different models, optimizing costs by prioritizing cheaper options, or simply guaranteeing the highest possible uptime for your AI-powered applications.
Key Features
- Dynamic LLM Selection: Choose between multiple configured Large Language Models (e.g., OpenAI's
gpt-4o-mini,gpt-4o) based on anllm_indexprovided in your chat input. - Intelligent Fallback System: Automatically switch to an alternative LLM if the initially selected model fails or returns an error, ensuring continuous operation and resilience.
- Multi-Model Support: Easily integrate and manage a diverse portfolio of LLMs, allowing for flexibility in your AI strategy.
- Code-Driven Routing Logic: Utilize a custom code node to implement precise logic for model selection and error handling.
How To Use
- Configure LLM Credentials: Ensure you have your OpenAI API credentials set up in n8n and linked to the
OpenAI Chat Modelnodes. - Add/Remove LLMs: Duplicate or remove the
OpenAI Chat Modelnodes (e.g.,OpenAI 4o-mini,OpenAI 4o) to adjust your available LLM pool. Ensure they are connected as inputs to theSwitch Modelnode. - Adjust
Switch ModelLogic (Optional): TheSwitch Modelnode uses anllm_indexto select an LLM. The code reverses the input list of LLMs, so be mindful of the order if you reorder or add many LLMs. - Trigger with
llm_index: Send a chat message (via theWhen chat message receivedtrigger) includingllm_indexin the payload (e.g.,{"text": "Hello", "llm_index": 1}) to explicitly choose an LLM. Ifllm_indexis not provided, it defaults to0. - Monitor Fallback: Observe the workflow execution to see the intelligent fallback in action if an LLM fails, potentially increasing the
llm_indexand retrying with the next model.
Apps Used
Workflow JSON
{
"id": "25c60c23-531f-44b5-b0ff-2175a5b70b84",
"name": "Dynamic LLM Switching & Intelligent Fallback",
"nodes": 13,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 25c60c23-531f...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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