LLM Configuration

Under Settings → Intelligence → Kaiya & AI → LLM Configuration, admins can register the large language model providers Tellius is allowed to call. Each entry holds one provider's connection details — which model service to reach, how to authenticate, and any parameters that shape the request. Once a configuration is saved here, it becomes available in LLM Assignments, where you decide which parts of Tellius use it.

The configuration list

Every saved configuration appears as a card. The card shows the reference name you gave it and a chip underneath naming the underlying provider, so several configurations can point at the same provider without confusion. For example, three separate Anthropic entries named for the specific models they target.

Each card has a three-dot menu with two actions:

• Edit: opens the configuration for changes.

• Delete: removes the configuration.

Deleting opens a warning that names the configuration being removed and states the action can't be undone. Choose Yes, Remove to confirm or Cancel to back out.

Editing a configuration

Choosing Edit on a card opens the Edit Provider dialog with the same fields, populated with the saved values. Secrets such as API keys are masked. Switching the deployment or authentication type swaps the credential fields below it, and the new fields start empty — you'll need to re-enter credentials for the method you've moved to.

The Edit Provider dialog offers Validate and Save only; there's no draft option once a configuration exists.

Adding a configuration

Click Add Configuration. The dialog opens with a default provider selected and a reference name pre-filled (Configuration 1, Configuration 2, and so on) — change both to suit.

Fields shared by every provider

LLM Model: the provider you want to connect to. This choice determines the rest of the form, since each provider authenticates differently. The available providers are:

• OpenAI

• Gemini

• Vertex AI

• Azure OpenAI

• Bedrock

• LLMaaS

• Anthropic

Reference Name (required): the label this configuration carries everywhere else in Tellius.

Model Parameter (required): the request settings, written as JSON. This is where the specific model and its behavior are pinned down. Typical entries include the model or deployment name, a temperature value, an API version, and a request timeout. The exact keys depend on the provider.

Default Header: any extra HTTP headers the provider needs, also written as JSON, such as authorization tokens or custom headers your gateway requires. Leave it as {} if none are needed.

Fields that depend on the provider

OpenAI, Gemini, Anthropic

• API Key (required): the key issued by that provider.

Vertex AI

• Service Account JSON (required): paste the Google Cloud service account JSON key.

Azure OpenAI

• Azure Deployment Type: choose Azure OpenAI API Key or Azure OpenAI Service Principal. Use the API key method for a standard Azure OpenAI resource; use a service principal when your organization authenticates through Microsoft Entra ID instead of shared keys.

• With Azure OpenAI API Key: Azure OpenAI API Key (required).

• With Azure OpenAI Service Principal: Azure Tenant ID, Azure Client ID, and Azure Client Secret (all required).

Bedrock

• Bedrock Authentication Type: choose Bedrock API Key or AWS Access/Secret Keys.

• With Bedrock API Key: Bedrock API Key (required).

• With AWS Access/Secret Keys: Access Key ID and Secret Access Key (both required).

LLMaaS

• API Key, Client Secret, and Client ID (all required).

Saving

Three buttons sit at the bottom of the Add Configuration dialog:

• Save as Draft: keeps a partly filled configuration without committing it. Useful when you're waiting on a key from another team.

• Validate: sends a test request using the details you entered and reports whether the provider accepts them. Validate before saving so a bad key or wrong endpoint surfaces here.

• Save: commits the configuration and adds it to the list.

Validate and Save stay unavailable until the required fields are filled in.