Automated AI Routing With OpenRouter
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Intelligently route user queries to the optimal Large Language Model (LLM) using AI. This workflow ensures the most accurate and efficient response by dynamically selecting the best-suited model for each specific task.
About This Workflow
This n8n workflow, "Automated AI Routing with OpenRouter," empowers you to build sophisticated AI-powered communication systems. It leverages the power of AI to analyze incoming chat messages and intelligently select the most appropriate LLM from a diverse pool available through OpenRouter. By understanding the nuances of each query, the workflow directs it to a model optimized for the task – whether it's web research, complex coding, creative writing, or data analysis. This dynamic routing ensures you get the best possible results, enhancing efficiency and accuracy in your AI interactions.
Key Features
- Dynamic LLM Selection: Automatically chooses the best AI model for any given query.
- Intelligent Routing Agent: Analyzes user intent and task requirements to make optimal model choices.
- Diverse Model Support: Integrates with a wide range of LLMs via OpenRouter, including models specialized for coding, research, and creative tasks.
- Structured Output: Guarantees consistent and predictable output format from the routing agent.
How To Use
- Trigger: Configure the 'When chat message received' node to listen for incoming chat messages.
- Initial Routing: Connect the trigger to the 'Routing Agent' node. This node is pre-configured with a system message that defines available models and their strengths. It will analyze the incoming message and determine the best model.
- Model Selection & Prompting: The 'Routing Agent' outputs a JSON object containing the user's prompt and the selected model name. This is then fed into the 'AI Agent' node.
- Execute Task: The 'AI Agent' node (or potentially another 'OpenRouter Chat Model' node, as shown in the second model instance) will then execute the prompt using the model specified by the 'Routing Agent'.
- Output: The final response from the LLM can then be processed or sent back to the user.
Apps Used
Workflow JSON
{
"id": "a8777431-51bd-4299-aa9a-35b285fda740",
"name": "Automated AI Routing With OpenRouter",
"nodes": 9,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: a8777431-51bd...
About the Author
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