Core concepts
The objects and boundaries behind a persistent model memory.
Internalize gives an application a stable subject to learn into and ask through. The subject stays the same while its active adapter version changes. Each operation is a durable job, so execution can continue after the HTTP connection or browser closes.
Objects
| Object | What it represents | Lifetime |
|---|---|---|
| Project | Access, subjects, credits, and spending controls | Shared across the application's requests |
| API key | A scoped server credential for one project | Until expiration or revocation |
| Subject | A stable knowledge identity within a project and optional tenant | Across inference and learning calls |
| Adapter version | An immutable trained candidate with validation metadata | While its checkpoints are retained |
| Active version | The subject's current routing choice | Until a later activation |
| Job | One admitted inference or internalization | From admission through settlement and inspection |
An adapter version is not an API key, a conversation, or a project. Keeping these identities distinct makes failures easier to diagnose. For example, using a different key for the same project does not create a fresh subject; using a new subject ID does.
One passage, two contexts
During learning, the teacher receives the source passage. Training transfers the resulting behavior into adapter weights. During later inference, the model receives your question and messages, with the active adapter loaded. Internalize does not add the source passage back to those messages.
This is the meaning of “knowledge without source context.” It does not mean inference has an empty prompt, that earlier chats are automatically remembered, or that every possible question will be answered correctly.
State you can inspect
Every admitted job records the subject and the adapter selected at admission. It also records status, phase, usage, reservation, settlement, and the final result or error. Internalization results expose the candidate version, validation totals, and whether activation happened.
The subject listing exposes the current active version, revision number, and recent retained versions. The revision changes on activation; it is not a count of successful learning jobs.
Read next
Read Subjects to design knowledge boundaries, How learning works for the training sequence, and Versions and routing for deployment behavior. Job lifecycle explains asynchronous execution, while Data handling describes what is retained for execution and recovery.