Module `adcp.types.domains.account.sync_governance_request`

Classes

class Account (**data: Any)

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class Account(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    account: Annotated[
        account_ref.AccountReference,
        Field(
            description='Account to sync governance agents for. Use account_id for account-id namespaces or brand + operator for buyer-declared accounts.'
        ),
    ]
    governance_agents: Annotated[
        list[GovernanceAgent],
        Field(
            description="Governance agent endpoint for this account. Exactly one entry — the single agent that owns the account's full governance lifecycle. The seller calls this agent via check_governance during media buy lifecycle events. The array shape is preserved for wire compatibility with 3.0 senders; `maxItems: 1` is load-bearing and mirrors the singular `governance_context` on the protocol envelope.",
            max_length=1,
            min_length=1,
        ),
    ]

Base model for AdCP types with spec-compliant serialization.

Defaults to extra='ignore' so unknown fields from newer spec versions are silently dropped rather than causing validation errors. Generated types whose schemas set additionalProperties: true override this with extra='allow' in their own model_config.

Set ADCP_STRICT_VALIDATION=1 in the environment ("1", "true", "yes", "on" are accepted) to flip the default to extra='forbid'. Use this during spec upgrades to catch silently-dropped renamed fields in tests. See :func:_resolve_extra_policy.

Important

The env var is resolved once at module import time. Set it in your shell or CI environment before import adcp runs — mutating os.environ["ADCP_STRICT_VALIDATION"] after the first adcp import has no effect on already-imported model classes (they captured the policy at class-body evaluation).

Consumers who want per-model strict validation can override model_config on their subclass.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors

AdCPBaseModel
pydantic.main.BaseModel

Class variables

var account : AccountReference1 | AccountReference2
var governance_agents : list[GovernanceAgent]
var model_config

Inherited members

AdCPBaseModel:
- model_dump
- model_dump_json
- model_summary

class Authentication (**data: Any)

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class Authentication(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    schemes: Annotated[
        list[Literal['Bearer']],
        Field(
            description='The seller authenticates outbound check_governance calls with the registered Bearer credential. Other shared webhook authentication schemes are not valid for this agent-to-agent call.',
            max_length=1,
            min_length=1,
        ),
    ]
    credentials: Annotated[
        str, Field(description='Authentication credential (e.g., Bearer token).', min_length=32)
    ]

Base model for AdCP types with spec-compliant serialization.

Important

Consumers who want per-model strict validation can override model_config on their subclass.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors

AdCPBaseModel
pydantic.main.BaseModel

Class variables

var credentials : str
var model_config
var schemes : list[typing.Literal['Bearer']]

Inherited members

AdCPBaseModel:
- model_dump
- model_dump_json
- model_summary

class GovernanceAgent (**data: Any)

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class GovernanceAgent(AdCPBaseModel):
    model_config = ConfigDict(
        extra='forbid',
    )
    url: Annotated[AnyUrl, Field(description='Governance agent endpoint URL. Must use HTTPS.')]
    authentication: Annotated[
        Authentication,
        Field(description='Authentication the seller presents when calling this governance agent.'),
    ]

Base model for AdCP types with spec-compliant serialization.

Important

Consumers who want per-model strict validation can override model_config on their subclass.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors

AdCPBaseModel
pydantic.main.BaseModel

Class variables

var authentication : Authentication
var model_config
var url : pydantic.networks.AnyUrl

Inherited members

AdCPBaseModel:
- model_dump
- model_dump_json
- model_summary

class SyncGovernanceRequest (**data: Any)

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class SyncGovernanceRequest(AdcpRequest, AdcpVersionEnvelope):
    model_config = ConfigDict(
        extra='allow',
    )
    idempotency_key: Annotated[
        str,
        Field(
            description='Client-generated unique key for at-most-once execution. `account` gives resource-level dedup, but governance changes emit audit events and can trigger reapproval flows — this key prevents those side effects from firing twice on retry. MUST be unique per (seller, request) pair. Use a fresh UUID v4 for each request.',
            max_length=255,
            min_length=16,
            pattern='^[A-Za-z0-9_.:-]{16,255}$',
        ),
    ]
    accounts: Annotated[
        list[Account],
        Field(
            description='Per-account governance agent configuration. Each entry pairs an account reference with the governance agents for that account.',
            max_length=100,
            min_length=1,
        ),
    ]
    context: context_1.ContextObject | None = None
    ext: ext_1.ExtensionObject | None = None

The request message of a task in the pinned bundle's task registry.

A consumer holding one can resolve its account, decide at-most-once, echo its context and negotiate version – the whole transport-boundary job – before knowing which tool it is. issubclass(model, AdcpRequest) is the registration-time proof that a model is spec-derived rather than a hand-written parallel: a field test passes for a forged model, descent does not.

Each accessor returns the field's value, or None when this tool's schema declares no such field. Only 49 of the 87 request schemas declare an account and only 43 an idempotency_key, so asking the request is what replaces getattr(req, "account", None) against Any at the boundary.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors

AdcpRequest
adcp.types.base._AdcpMessage
AdcpVersionEnvelope
AdCPBaseModel
pydantic.main.BaseModel

Class variables

var accounts : list[Account]
var context : ContextObject | None
var ext : ExtensionObject | None
var idempotency_key : str
var model_config

Inherited members

AdcpRequest:
- get_account
- get_adcp_major_version
- get_adcp_version
- get_context
- get_idempotency_key
- get_push_notification_config
AdcpVersionEnvelope:
- model_dump
- model_dump_json
- model_summary