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User Auth Data

User Auth Data Management​

Manage API key configurations (auth-data) and their associations to AI systems. These methods let you create, view, edit, delete, and map auth-data to specific AI systems.

Create Cloud Auth Data​

create_cloud_auth_data(name, provider_type, api_key)​

Creates a new REMOTE_CLOUD auth-data configuration with a single API key. The server validates and encrypts the key.

Method Parameters​

name | required string

Display name for this auth configuration.

provider_type | required ProviderTypeEnum

Cloud provider. Examples: "openai", "azure", "anthropic", "mistral", "togetherai", "lambdalabs", "databricks", "bedrock", "gemini".

api_key | required string

Plaintext API key. Stored encrypted server‑side.

Returns​

UserAuthDataRecordEntity

Example​

from dynamofl.entities import ProviderTypeEnum

record = dfl.create_cloud_auth_data(
    name="Primary OpenAI",
    provider_type=ProviderTypeEnum.OPENAI,
    api_key="sk-***",
)

Get User Auth Data + Associations​

get_user_auth_data_and_associations(auth_type?, provider_type?)​

Returns the user's auth-data grouped by provider along with the AI system mappings for each entry.

Method Parameters​

auth_type | optional AuthDataAuthTypeEnum

Filter by auth type. Examples: "REMOTE_CLOUD", "REMOTE_CUSTOM".

provider_type | optional ProviderTypeEnum

Filter by provider. Examples: "openai", "azure", "anthropic" …

Returns​

GetUserLevelAuthDataAndModelAssociationEntity

Example​

from dynamofl.entities import AuthDataAuthTypeEnum, ProviderTypeEnum

listing = dfl.get_user_auth_data_and_associations(
    auth_type=AuthDataAuthTypeEnum.REMOTE_CLOUD,
    provider_type=ProviderTypeEnum.OPENAI,
)

Get Auth Data (by ID)​

get_auth_data(auth_id)​

Fetch a single auth-data row and its AI system mappings for the user.

Method Parameters​

auth_id | required int

The auth-data id to fetch.

Returns​

GetAuthDataByIdEntity

Example​

details = dfl.get_auth_data(auth_id=123)

Edit Auth Data​

edit_auth_data(auth_id, name?, api_key?)​

Edit the display name and/or API key on a REMOTE_CLOUD auth-data configuration.

Method Parameters​

auth_id | required int

The auth-data id to edit.

name | optional string

New display name.

api_key | optional string

New plaintext API key (will be validated and encrypted).

Returns​

UserAuthDataRecordEntity

Example​

updated = dfl.edit_auth_data(
    auth_id=123,
    name="Prod OpenAI Key",
    api_key="sk-***",
)

Delete Auth Data​

delete_auth_data(auth_id)​

Delete a user's auth-data row by id.

Method Parameters​

auth_id | required int

The auth-data id to delete.

Returns​

DeleteAuthDataResponseEntity

Example​

resp = dfl.delete_auth_data(auth_id=123)

Update AI System Mappings​

update_auth_mappings_on_auth_data(auth_id, ai_systems_to_add?, ai_systems_to_remove?)​

Associate or remove AI system mappings for a given auth-data id. Use this to link API keys to specific models and set primaries via the server’s policy.

Method Parameters​

auth_id | required int

The auth-data id to update.

ai_systems_to_add | optional List[string]

Model ids to associate with this auth-data.

ai_systems_to_remove | optional List[string]

Model ids to remove from association.

Returns​

UpdateAuthMappingsOnAuthDataResponseEntity

Example​

result = dfl.update_auth_mappings_on_auth_data(
    auth_id=123,
    ai_systems_to_add=["model_key_a", "model_key_b"],
    ai_systems_to_remove=["old_model_key"],
)

Notes​

  • For remote AI systems, the model creation flow requires providing auth_data_ids and a primary_auth_data_id. Do not pass plaintext API keys to model creation; the server resolves keys from your auth-data. This is reflected in the AI Systems creation methods such as create_openai_model, create_azure_model, etc.