This guide explains how models are deployed and executed in Acklix. It focuses on deployment mechanics, lifecycle, and constraints.
What Is a Deployment
A deployment is a versioned, executable instance of a model. Models themselves are configuration objects and cannot be used for inference until they are deployed.
Each deployment is immutable. Any change to model configuration requires creating a new deployment.
Deployment Lifecycle
A model configuration is validated.
A deployment record is created with a version number.
Tool bindings, secrets, and services are resolved.
The deployment is marked active.
The deployment becomes available for inference.
Preconditions
A deployment can only be created if all dependent resources referenced by the model are available.
All required secrets must be configured
Referenced services must be connected
Tool schemas must be valid
After Deployment
Once active, a deployment can be referenced by its deployment_id in inference requests.
Deployments are the only executable targets for:
Inference API
Conversations
Interfaces (Web, WhatsApp, Email)
Automations and scheduled tasks
Versioning
Multiple deployments may exist for the same model. Each deployment has an independent lifecycle and version number.
Existing deployments are not affected when a new deployment is created from an updated model.