Module `adcp.types.domains.media_buy.refine_proposals_request`

Classes

class RefineProposalsRequest (**data: Any)

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class RefineProposalsRequest(AdcpRequest, AdcpVersionEnvelope):
    model_config = ConfigDict(
        extra='forbid',
    )
    context_id: Annotated[
        str | None,
        Field(
            description='MCP compatibility field: servers ignore this value; A2A uses transport-native Message/Task contextId.',
            min_length=1,
        ),
    ] = None
    context: context_1.ContextObject | None = None
    governance_context: Annotated[str | None, Field(max_length=4096, min_length=1)] = None
    push_notification_config: push_notification_config_1.PushNotificationConfig | None = None
    idempotency_key: Annotated[
        str,
        Field(
            description='Client-generated key required for retry-safe proposal refinement.',
            max_length=255,
            min_length=16,
            pattern='^[A-Za-z0-9_.:-]{16,255}$',
        ),
    ]
    refinements: Annotated[
        list[proposal_refinement.ProposalRefinement] | Refinements,
        Field(
            description='Proposal operations to apply, with at most 25 entries per request. revise creates a draft successor from a draft, committed, or accepted source. finalize MUST target a draft, reserves inventory, and creates a committed successor whose expires_at is the hold deadline. A batch containing finalize MUST contain only finalize entries and is atomic. proposal_id values MUST be unique; results preserve request order.',
            max_length=25,
            min_length=1,
        ),
    ]

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 context : ContextObject | None
var context_id : str | None
var governance_context : str | None
var idempotency_key : str
var model_config
var push_notification_config : PushNotificationConfig | None
var refinements : list[ProposalRefinement2 | ProposalRefinement3 | ProposalRefinement4 | ProposalRefinement5 | ProposalRefinement6 | ProposalRefinement7 | ProposalRefinement8 | ProposalRefinement9] | Refinements

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

class Refinements (**data: Any)

Expand source code

class Refinements(AdCPBaseModel):
    pass

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.