Module adcp.types.domains.creative.video_brief

Classes

class Segment (**data: Any)

Expand source code

class Segment(AdCPBaseModel):
    model_config = ConfigDict(
        extra='allow',
    )
    order: Annotated[
        SchemaInt,
        Field(description='1-indexed sequence position of this segment in the final video.', ge=1),
    ]
    duration_ms: Annotated[
        SchemaInt, Field(description='Duration of this segment in milliseconds.', ge=1)
    ]
    prompt: Annotated[
        str,
        Field(
            description='Text prompt fed to the synthesis pipeline for this segment (subject, action, setting, mood). Renamed from earlier `description` to make explicit that this is a generation prompt — not a description-of-finished-content.'
        ),
    ]
    vo: Annotated[str | None, Field(description='Voiceover line for this segment (optional).')] = (
        None
    )
    caption: Annotated[
        str | None, Field(description='On-screen caption text for this segment (optional).')
    ] = None

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 caption : str | None

var duration_ms : int

var model_config

var order : int

var prompt : str

var vo : str | None

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary

class VideoBrief (**data: Any)

Expand source code

class VideoBrief(AdCPBaseModel):
    model_config = ConfigDict(
        extra='allow',
    )
    segments: Annotated[
        list[Segment],
        Field(
            description="Ordered list of per-segment prompts that compose the generated video. The sum of `duration_ms` across segments should match the target video duration declared by the format declaration's `duration_ms_exact` or `duration_ms_range`.",
            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 model_config

var segments : list[Segment]

Inherited members

• AdCPBaseModel:
  • model_dump
  • model_dump_json
  • model_summary