# Internalize

Source: https://convergingthought.com/docs

> Learn knowledge into model weights. Keep the source out of subsequent prompts.



Internalize turns a passage of knowledge into a versioned adapter for GLM 5.3. Call `internalize` for a subject, wait for training and validation, then send questions to the same subject. Internalize hosts the adapter and routes new requests to its active version.

The source is used during learning. It is **not appended to later inference messages**. Your application still sends the question and any instructions or conversation it needs; the learned knowledge is carried by the adapter weights.

<Callout title="Hosted preview">
  The console is currently open for exploration. Billing is a preview and model
  execution is disabled. The guides below describe the implemented API contract
  for enabled projects. See [availability](/docs/getting-started/availability)
  before running examples.
</Callout>

## Start here [#start-here]

<Cards>
  <Card title="Make your first call" href="/docs/getting-started/quickstart" description="Internalize a policy, wait for activation, and ask without the source." />

  <Card title="Understand the system" href="/docs/concepts/how-it-works" description="Subjects, context distillation, validation, and managed weights." />

  <Card title="API reference" href="/docs/api-reference" description="Every endpoint, request field, response, limit, and error." />

  <Card title="Connect an agent" href="/docs/integrations/agents" description="A durable tool call with explicit learning and activation outcomes." />
</Cards>

## The three operations [#the-three-operations]

| Operation | Your application sends                            | Internalize returns                                        |
| --------- | ------------------------------------------------- | ---------------------------------------------------------- |
| Learn     | A subject and a self-contained knowledge passage  | A job that can produce a validated adapter candidate       |
| Activate  | A candidate and the version you expect to replace | A new active version, if the subject has not changed       |
| Ask       | The same subject and inference messages           | A job with the answer, resolved adapter, usage, and charge |

Learning activates automatically by default. Explicit activation is useful for reviewed releases and rollback. In both cases, already-running requests keep the version chosen when they were admitted.

## Find the right guide [#find-the-right-guide]

Use [Getting started](/docs/getting-started/onboarding) to prepare a project and credentials. The [Product guide](/docs/product/overview) explains each console workspace. [Concepts](/docs/concepts) covers the model and state boundaries; [Guides](/docs/guides/knowledge) shows how to structure knowledge, evaluate updates, and deploy them.

For an integration, choose [TypeScript](/docs/sdk-reference/typescript), [Python over HTTP](/docs/sdk-reference/python), or the [endpoint reference](/docs/api-reference). For operations, start with [billing](/docs/billing), [job recovery](/docs/troubleshooting/jobs), and [safe diagnostics](/docs/troubleshooting/diagnostics).

Validation is evidence about the checks run for one candidate. It is not a guarantee of perfect recall or general understanding. Test the questions, applications, and failure cases your product depends on before relying on a new version.

## Machine-readable documentation [#machine-readable-documentation]

Agents can discover these same guides through [/llms.txt](/llms.txt), read the complete set at [/llms-full.txt](/llms-full.txt), or fetch individual [Markdown pages](/docs/integrations/agent-docs). The [OpenAPI specification](/openapi.json) describes the public HTTP interface. These surfaces share the documentation source used by this site.