routing

To route inputs to specialized prompts or models, you can classify the input type to select the most suitable processing path. This ensures each request is handled by the appropriate prompt, tool, or agent for optimal results.

Model routing handles fallbacks by outputting a route label alongside a confidence score. When confidence is low, the router directs the input to a predefined fallback path to ensure the request is still processed reliably.

The best way to classify heterogeneous user queries is to implement a router that evaluates the input type and outputs a route label. This approach applies across classification and tool chaining to direct each query to the right specialized agent.

Yes, you can easily add new routes to the input classification system. The routing mechanism is designed for extensibility, allowing you to append new paths while maintaining guardrails like confidence scores and fallbacks to control quality.

You optimize cost and latency by routing customer queries to specialized models or tools based on their classified intent. Directing inputs to the most suitable path prevents overprocessing and reduces unnecessary computational overhead.

You should use a fallback path in automated decision routing when the router outputs a low confidence score for a classified input. This guardrail ensures unclassified or ambiguous requests are handled correctly without breaking the workflow.