> ## Documentation Index
> Fetch the complete documentation index at: https://docs.threetone.in/llms.txt
> Use this file to discover all available pages before exploring further.

# Custom models

> Prepare a custom language-model endpoint, run the supported dashboard connection probe, and preserve a candidate configuration as a draft.

A custom model configuration identifies an external model endpoint and its credential references. It differs from selecting a managed model in the workspace catalog.

<Note>
  The dashboard has an implemented connection probe for an unsaved custom configuration. Current custom-model publication is rejected with `custom_llm_execution_unavailable`. A successful probe does not publish the configuration or start an agent conversation.
</Note>

## Configure the candidate

<Steps>
  <Step title="Choose the model mode">Open an editable agent's LLM selection and choose **Custom LLM**. Keep the intended agent and workspace selected.</Step>
  <Step title="Set the endpoint">Enter **Server URL** and **Model ID**. The current probe accepts a public HTTPS Chat Completions base URL. Review [endpoint compatibility](/agents-platform/advanced/custom-models/compatible-endpoints).</Step>
  <Step title="Prepare credentials">Select a workspace secret or Secret environment variable for **API Key**, or **None** when the endpoint needs no key. Environment references resolve against production for the probe. Review request headers. Current probe policy rejects auth connections, API-version parameters, and dynamic headers.</Step>
  <Step title="Test the connection">Use **Test connection** with an approved provider account. This makes a real model request. Inspect the returned result and any error before changing other fields.</Step>
  <Step title="Preserve the candidate">Field edits update the editor's local working copy; closing the sheet only dismisses it. For durable review, create a complete [server draft](/agents-platform/deploy/versioning) and read it back. Do not treat a rejected Publish action as a saved version.</Step>
</Steps>

## Configuration relationship

Under `conversation_config.agent.prompt`, custom selection requires `llm: "custom-llm"`, a `custom_llm` definition, and `backup_llm_config.preference: "disabled"`. Managed model selection requires `custom_llm` to be null. Preserve the rest of the selected snapshot when authoring a draft.

## Frequently asked questions

<AccordionGroup>
  <Accordion title="Can a successful test be used as an agent runtime release?" id="faq-custom-model-probe">No. Endpoint probing, draft storage, publication, and conversation execution are different operations.</Accordion>
  <Accordion title="Can I invoke the dashboard probe with my personal API key?" id="faq-custom-model-probe-auth">The probe is dashboard-only. Its implementation is not a public API-key workflow or a reason to copy dashboard credentials into application code.</Accordion>
</AccordionGroup>


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