Deploy a self-hosted large language model
Tier: For a limited time, Ultimate. On October 17, 2024, Ultimate with GitLab Duo Enterprise.
Offering: Self-managed
Status: Beta
Offering: Self-managed
Status: Beta
History
-
Introduced in GitLab 17.1 with a flag named
ai_custom_model
. Disabled by default.
The availability of this feature is controlled by a feature flag.
For more information, see the history.
When you deploy a self-hosted model, you can:
- Manage the end-to-end transmission of requests to enterprise-hosted large language model (LLM) backends for GitLab Duo features.
- Keep all of these requests within that enterprise network, ensuring no calls to external architecture.
- Isolate the GitLab instance, AI Gateway, and self-hosted model within their own environment, ensuring complete privacy and high security for using AI features, with no reliance on public services.
When you use self-hosted models, you:
- Can choose any GitLab-approved LLM.
- Can keep all data and request/response logs in your own domain.
- Can select specific GitLab Duo features for your users.
- Do not have to rely on the GitLab shared AI Gateway.
You can connect supported models to LLM features. Model-specific prompts and GitLab Duo feature support is provided by the GitLab Duo Self-Hosted Models feature. For more information about this offering, see subscriptions and the Blueprint.
Prerequisites
- You must be able to manage your own LLM infrastructure.
- You must have GitLab Enterprise Edition.
Deploy a self-hosted model
To deploy a self-hosted large language model:
- Set up your self-hosted model infrastructure and connect it to your GitLab instance.
- Configure your GitLab instance to access self-hosted models using instance and group settings.