Developer documentation > API reference > App framework

App framework utilities¶

Settings¶

DataRobotAppFrameworkBaseSettings¶

class datarobot.core.DataRobotAppFrameworkBaseSettings

Base settings class that reads each setting from the first source that defines it:

Environment variables, including runtime parameters
The .env file
File secrets
pulumi_config.json (fallback)

However a variable is set, it is picked up, so the same settings class works both locally and once deployed in DataRobot. This covers credentials and plain variables for runtime parameters in both custom applications and custom models.

Examples

   class Config(DataRobotAppFrameworkBaseSettings):
       my_variable: str = "default_value"
       another_variable: Optional[int]

config = Config()
assert config.my_variable == "value_from_env_or_pulumi_or_default"

settings_customise_sources()¶

classmethod settings_customise_sources()

Define the sources and their order for loading the settings values.

Parameters

Parameter	Type	Description
`settings_cls`	`Type`[`BaseSettings`]	The Settings class.
`init_settings`	`PydanticBaseSettingsSource`	The InitSettingsSource instance.
`env_settings`	`PydanticBaseSettingsSource`	The EnvSettingsSource instance.
`dotenv_settings`	`PydanticBaseSettingsSource`	The DotEnvSettingsSource instance.
`file_secret_settings`	`PydanticBaseSettingsSource`	The SecretsSettingsSource instance.

Return type: Tuple[PydanticBaseSettingsSource, ...]

Returns

Returns	Description
A tuple containing the sources and their order for loading the settings values.

resolve_datarobot_endpoint()¶

method resolve_datarobot_endpoint()

Resolve the DataRobot endpoint from this config, or fall back to the public default.

Return type: str

resolve_datarobot_api_token()¶

method resolve_datarobot_api_token()

Resolve the DataRobot API token from this config, treating an empty value as unset.

Return type: Optional[str]

resolve_llm_config()¶

method resolve_llm_config()

Build the config for one named LLM instance from this settings object.

Call this once per configured LLM to support more than one LLM in a single app.

Parameters

Parameter	Type	Description
`name`	`str`	Name of the LLM component instance, used as the prefix of its `{name}_*` fields. Defaults to `"llm"`.

Returns

Returns	Description
That instance’s routing fields, combined with the endpoint and API token
resolved from this config.

Return type: LLMConfig

OpenTelemetry¶

datarobot.core.create_dr_resource(entity_type, entity_id, , service_priority='p1', extra_attrs=None)¶

Build an OpenTelemetry Resource with DataRobot-standard attributes.

Parameters

Parameter	Type	Description
`entity_type`	`str`	DataRobot entity type (e.g. `"experiment_container"`).
`entity_id`	`str`	DataRobot entity ID.
`service_priority`	`str`	Value for `datarobot.service.priority`. Defaults to `"p1"`.
`extra_attrs`	`Optional[Dict[str, str]]`	Additional or override attributes merged last, taking precedence over all computed values.

Return type: Resource

Returns

Returns	Description
An `opentelemetry.sdk.resources.Resource` ready to pass to a
`TracerProvider` / `MeterProvider` / `LoggerProvider`.

Raises

Exception	Description
ImportError	If `opentelemetry-sdk` is not installed. Install the `datarobot[otel]` extra to add it.

NOTE¶

service.name is only set when OTEL_SERVICE_NAME is absent from the environment — Resource.create() merges env vars at lower precedence than explicit attrs, so setting it here would shadow any platform-provided value.

LLM configuration¶

LLMConfig¶

class datarobot.core.LLMConfig

Resolved connection parameters for a single LLM instance.

An app can hold one of these per configured LLM. Each carries the routing fields for its own LLM plus a copy of the DataRobot endpoint and API token, so building a client from it never requires reading a global config.

Variables

Attribute	Type	Description
`datarobot_endpoint`	`str` or `None`	DataRobot API endpoint. Defaults to `DEFAULT_DATAROBOT_ENDPOINT` when unset.
`datarobot_api_token`	`str` or `None`	DataRobot API token used to authenticate LLM requests.
`llm_deployment_id`	`str` or `None`	ID of the deployment serving the LLM, when routing to a deployment.
`llm_nim_deployment_id`	`str` or `None`	ID of the deployment serving a NIM model, when routing to a NIM.
`llm_use_datarobot_llm_gateway`	`bool`	Whether to route through the DataRobot LLM gateway. Takes precedence over both deployment IDs. Defaults to `True`.
`llm_default_model`	`str` or `None`	Model name to request. Defaults to `DEFAULT_MODEL_NAME_FOR_DEPLOYED_LLM`.

Notes

This is intentionally a plain model rather than a DataRobotAppFrameworkBaseSettings subclass. The settings class is the single app-wide source of configuration, so keeping LLMConfig separate is what lets one app configure several LLMs, including fallbacks.

get_llm_type()¶

method get_llm_type()

Report which route this config uses, checking the routing fields in precedence order.

Return type: LLMType

to_litellm_params()¶

method to_litellm_params()

Render this config as a litellm_params entry for a litellm.Router model list.

Returns

Returns	Description
The `litellm` connection parameters: `model`, `api_key`, and, for every
route other than an external provider, `api_base`.

Return type: dict

LLMType¶

class datarobot.core.LLMType

How an LLMConfig routes its requests.