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LLM Router

The LLM Router component intelligently routes inputs to appropriate language models based on defined criteria and optimization settings.

LLM Router Component

LLM Router interface and configuration

Component Inputs

  • Language Models: Available LLM options

    List of language models to route between

  • Input: Query or task input

    The input to be processed by the selected model

  • Judge LLM: Model selection criteria

    Logic for selecting the appropriate model

  • Optimization: Routing strategy

    Settings for optimizing model selection (e.g., balanced)

Component Outputs

  • Output: Processing result

    The result from the selected model

  • Selected Model: Chosen LLM

    Information about which model was selected

Implementation Example

const llmRouter = { languageModels: [ { name: "gpt-4", capabilities: ["complex-reasoning", "code"] }, { name: "gpt-3.5", capabilities: ["general", "fast"] } ], input: "Explain quantum computing", judgeLLM: { criteria: ["complexity", "topic", "length"], threshold: 0.8 }, optimization: "balanced" }; // Output: // { // output: "Quantum computing explanation...", // selectedModel: { // name: "gpt-4", // confidence: 0.92, // reason: "Complex technical topic" // } // }

Best Practices

  • Define clear model selection criteria
  • Monitor and log routing decisions
  • Implement fallback strategies
  • Regularly update model capabilities