studio-backend-models

Integrating new AI models into the Studio backend requires implementing an anticorruption layer for the model client, declaring its capabilities, registering it in the dependency context, and wiring it into the Flutter UI dropdown.

The anticorruption layer when adding audio model clients isolates external AI model APIs from the Studio backend, ensuring standardized field names and consistent capability declaration across diverse audio and text models.

Declaring model capabilities for UI dropdown integration in Flutter involves defining model features, task types, and standardized parameter names. This capability declaration allows the Studio frontend to automatically populate selection dropdowns with the new AI model.

Yes, you can use this guide to add a text-to-speech model to Studio. The documentation covers creating a TextModelClient, defining its capabilities, registering it in the backend dependency context, and integrating it into the Flutter UI dropdown.

Backend dependency registration of a new AI model requires creating the appropriate model client, implementing the anticorruption layer, and adding the service to the Studio backend dependency context to ensure the model is available for capability declaration and UI integration.

Yes, reference implementations for existing audio models like Bark, ACE-Step 1.5, and MIDI are available. These examples demonstrate how to build the model client architecture, declare capabilities, and handle standardized field names within the Studio backend.