CompactedResponse Class

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.

Constructor

CompactedResponse(**data: Any)

Methods

construct
copy	Returns a copy of the model. !!! warning "Deprecated" This method is now deprecated; use model_copy instead. If you need include or exclude, use: python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data)
dict
from_orm
json
model_construct
model_copy	!!! abstract "Usage Documentation" model_copy Returns a copy of the model. !!! note The underlying instance's [dict][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).
model_dump	!!! abstract "Usage Documentation" model_dump Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
model_dump_json	!!! abstract "Usage Documentation" model_dump_json Generates a JSON representation of the model using Pydantic's to_json method.
model_json_schema	Generates a JSON schema for a model class.
model_parametrized_name	Compute the class name for parametrizations of generic classes. This method can be overridden to achieve a custom naming scheme for generic BaseModels.
model_post_init	Override this method to perform additional initialization after init and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.
model_rebuild	Try to rebuild the pydantic-core schema for the model. This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.
model_validate	Validate a pydantic model instance.
model_validate_json	!!! abstract "Usage Documentation" JSON Parsing Validate the given JSON data against the Pydantic model.
model_validate_strings	Validate the given object with string data against the Pydantic model.
parse_file
parse_obj
parse_raw
schema
schema_json
to_dict	Recursively generate a dictionary representation of the model, optionally specifying which fields to include or exclude. By default, fields that were not set by the API will not be included, and keys will match the API response, not the property names from the model. For example, if the API responds with "fooBar": true but we've defined a foo_bar: bool property, the output will use the "fooBar" key (unless use_api_names=False is passed).
to_json	Generates a JSON string representing this model as it would be received from or sent to the API (but with indentation). By default, fields that were not set by the API will not be included, and keys will match the API response, not the property names from the model. For example, if the API responds with "fooBar": true but we've defined a foo_bar: bool property, the output will use the "fooBar" key (unless use_api_names=False is passed).
update_forward_refs
validate

construct

construct(_fields_set: set[str] | None = None, **values: object) -> ModelT

Parameters

Name	Description
_fields_set	Default value: None

copy

Returns a copy of the model.

!!! warning "Deprecated" This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data)

copy(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) -> Self

Parameters

Name	Description
include Required	Optional set or mapping specifying which fields to include in the copied model.
exclude Required	Optional set or mapping specifying which fields to exclude in the copied model.
update Required	Optional dictionary of field-value pairs to override field values in the copied model.
deep Required	If True, the values of fields that are Pydantic models will be deep-copied.

Keyword-Only Parameters

Name	Description
include	Default value: None
exclude	Default value: None
update	Default value: None
deep	Default value: False

Returns

Type	Description
	A copy of the model with included, excluded and updated fields as specified.

dict

dict(*, include: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) -> Dict[str, Any]

Keyword-Only Parameters

Name	Description
include	Default value: None
exclude	Default value: None
by_alias	Default value: False
exclude_unset	Default value: False
exclude_defaults	Default value: False
exclude_none	Default value: False

from_orm

from_orm(obj: Any) -> Self

Parameters

Name	Description
obj Required

json

json(*, include: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) -> str

Keyword-Only Parameters

Name	Description
include	Default value: None
exclude	Default value: None
by_alias	Default value: False
exclude_unset	Default value: False
exclude_defaults	Default value: False
exclude_none	Default value: False
encoder	Default value: PydanticUndefined
models_as_dict	Default value: PydanticUndefined

model_construct

model_construct(_fields_set: set[str] | None = None, **values: object) -> ModelT

Parameters

Name	Description
_fields_set	Default value: None

model_copy

!!! abstract "Usage Documentation" model_copy

Returns a copy of the model.

!!! note The underlying instance's [dict][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

model_copy(*, update: Mapping[str, Any] | None = None, deep: bool = False) -> Self

Parameters

Name	Description
update Required	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
deep Required	Set to True to make a deep copy of the model.

Keyword-Only Parameters

Name	Description
update	Default value: None
deep	Default value: False

Returns

Type	Description
	New model instance.

model_dump

!!! abstract "Usage Documentation" model_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

model_dump(*, mode: Literal['json', 'python'] | str = 'python', include: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False) -> dict[str, Any]

Parameters

Name	Description
mode Required	The mode in which to_python should run. If mode is 'json', the output will only contain JSON serializable types. If mode is 'python', the output may contain non-JSON-serializable Python objects.
include Required	A set of fields to include in the output.
exclude Required	A set of fields to exclude from the output.
context Required	Additional context to pass to the serializer.
by_alias Required	Whether to use the field's alias in the dictionary key if defined.
exclude_unset Required	Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	Whether to exclude fields that are set to their default value.
exclude_none Required	Whether to exclude fields that have a value of None.
exclude_computed_fields Required	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
round_trip Required	If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings Required	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback Required	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
serialize_as_any Required	Whether to serialize fields with duck-typing serialization behavior.

Keyword-Only Parameters

Name	Description
mode	Default value: python
include	Default value: None
exclude	Default value: None
context	Default value: None
by_alias	Default value: None
exclude_unset	Default value: False
exclude_defaults	Default value: False
exclude_none	Default value: False
exclude_computed_fields	Default value: False
round_trip	Default value: False
warnings	Default value: True
fallback	Default value: None
serialize_as_any	Default value: False

Returns

Type	Description
	A dictionary representation of the model.

model_dump_json

!!! abstract "Usage Documentation" model_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

model_dump_json(*, indent: int | None = None, ensure_ascii: bool = False, include: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, exclude: set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal['none', 'warn', 'error'] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False) -> str

Parameters

Name	Description
indent Required	Indentation to use in the JSON output. If None is passed, the output will be compact.
ensure_ascii Required	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.
include Required	Field(s) to include in the JSON output.
exclude Required	Field(s) to exclude from the JSON output.
context Required	Additional context to pass to the serializer.
by_alias Required	Whether to serialize using field aliases.
exclude_unset Required	Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	Whether to exclude fields that are set to their default value.
exclude_none Required	Whether to exclude fields that have a value of None.
exclude_computed_fields Required	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
round_trip Required	If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings Required	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback Required	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
serialize_as_any Required	Whether to serialize fields with duck-typing serialization behavior.

Keyword-Only Parameters

Name	Description
indent	Default value: None
ensure_ascii	Default value: False
include	Default value: None
exclude	Default value: None
context	Default value: None
by_alias	Default value: None
exclude_unset	Default value: False
exclude_defaults	Default value: False
exclude_none	Default value: False
exclude_computed_fields	Default value: False
round_trip	Default value: False
warnings	Default value: True
fallback	Default value: None
serialize_as_any	Default value: False

Returns

Type	Description
	A JSON string representation of the model.

model_json_schema

Generates a JSON schema for a model class.

model_json_schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}', schema_generator: type[pydantic.json_schema.GenerateJsonSchema] = <class 'pydantic.json_schema.GenerateJsonSchema'>, mode: ~typing.Literal['validation', 'serialization'] = 'validation', *, union_format: ~typing.Literal['any_of', 'primitive_type_array'] = 'any_of') -> dict[str, Any]

Parameters

Name	Description
by_alias	Whether to use attribute aliases or not. Default value: True
ref_template	The reference template. Default value: #/$defs/{model}
union_format Required	The format to use when combining schemas from unions together. Can be one of: 'any_of': Use the anyOf keyword to combine schemas (the default). 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.
schema_generator	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications Default value: <class 'pydantic.json_schema.GenerateJsonSchema'>
mode	The mode in which to generate the schema. Default value: validation

Keyword-Only Parameters

Name	Description
union_format	Default value: any_of

Returns

Type	Description
	The JSON schema for the given model class.

model_parametrized_name

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

model_parametrized_name(params: tuple[type[Any], ...]) -> str

Parameters

Name	Description
params Required	Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Returns

Type	Description
	String representing the new class where params are passed to cls as type variables.

Exceptions

Type	Description
TypeError	Raised when trying to generate concrete names for non-generic models.

model_post_init

Override this method to perform additional initialization after init and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

model_post_init(context: Any, /) -> None

Positional-Only Parameters

Name	Description
context Required

model_rebuild

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: MappingNamespace | None = None) -> bool | None

Parameters

Name	Description
force Required	Whether to force the rebuilding of the model schema, defaults to False.
raise_errors Required	Whether to raise errors, defaults to True.
_parent_namespace_depth Required	The depth level of the parent namespace, defaults to 2.
_types_namespace Required	The types namespace, defaults to None.

Keyword-Only Parameters

Name	Description
force	Default value: False
raise_errors	Default value: True
_parent_namespace_depth	Default value: 2
_types_namespace	Default value: None

Returns

Type	Description
	Returns None if the schema is already "complete" and rebuilding was not required. If rebuilding was required, returns True if rebuilding was successful, otherwise False.

model_validate

Validate a pydantic model instance.

model_validate(obj: Any, *, strict: bool | None = None, extra: Literal['allow', 'ignore', 'forbid'] | None = None, from_attributes: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) -> Self

Parameters

Name	Description
obj Required	The object to validate.
strict Required	Whether to enforce types strictly.
extra Required	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
from_attributes Required	Whether to extract data from object attributes.
context Required	Additional context to pass to the validator.
by_alias Required	Whether to use the field's alias when validating against the provided input data.
by_name Required	Whether to use the field's name when validating against the provided input data.

Keyword-Only Parameters

Name	Description
strict	Default value: None
extra	Default value: None
from_attributes	Default value: None
context	Default value: None
by_alias	Default value: None
by_name	Default value: None

Returns

Type	Description
	The validated model instance.

Exceptions

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

!!! abstract "Usage Documentation" JSON Parsing

Validate the given JSON data against the Pydantic model.

model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, extra: Literal['allow', 'ignore', 'forbid'] | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) -> Self

Parameters

Name	Description
json_data Required	The JSON data to validate.
strict Required	Whether to enforce types strictly.
extra Required	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context Required	Extra variables to pass to the validator.
by_alias Required	Whether to use the field's alias when validating against the provided input data.
by_name Required	Whether to use the field's name when validating against the provided input data.

Keyword-Only Parameters

Name	Description
strict	Default value: None
extra	Default value: None
context	Default value: None
by_alias	Default value: None
by_name	Default value: None

Returns

Type	Description
	The validated Pydantic model.

Exceptions

Type	Description
ValidationError	If json_data is not a JSON string or the object could not be validated.

model_validate_strings

Validate the given object with string data against the Pydantic model.

model_validate_strings(obj: Any, *, strict: bool | None = None, extra: Literal['allow', 'ignore', 'forbid'] | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) -> Self

Parameters

Name	Description
obj Required	The object containing string data to validate.
strict Required	Whether to enforce types strictly.
extra Required	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context Required	Extra variables to pass to the validator.
by_alias Required	Whether to use the field's alias when validating against the provided input data.
by_name Required	Whether to use the field's name when validating against the provided input data.

Keyword-Only Parameters

Name	Description
strict	Default value: None
extra	Default value: None
context	Default value: None
by_alias	Default value: None
by_name	Default value: None

Returns

Type	Description
	The validated Pydantic model.

parse_file

parse_file(path: str | Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) -> Self

Parameters

Name	Description
path Required

Keyword-Only Parameters

Name	Description
content_type	Default value: None
encoding	Default value: utf8
proto	Default value: None
allow_pickle	Default value: False

parse_obj

parse_obj(obj: Any) -> Self

Parameters

Name	Description
obj Required

parse_raw

parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: DeprecatedParseProtocol | None = None, allow_pickle: bool = False) -> Self

Parameters

Name	Description
b Required

Keyword-Only Parameters

Name	Description
content_type	Default value: None
encoding	Default value: utf8
proto	Default value: None
allow_pickle	Default value: False

schema

schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}') -> Dict[str, Any]

Parameters

Name	Description
by_alias	Default value: True
ref_template	Default value: #/$defs/{model}

schema_json

schema_json(*, by_alias: bool = True, ref_template: str = '#/$defs/{model}', **dumps_kwargs: Any) -> str

Keyword-Only Parameters

Name	Description
by_alias	Default value: True
ref_template	Default value: #/$defs/{model}

to_dict

Recursively generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

By default, fields that were not set by the API will not be included, and keys will match the API response, not the property names from the model.

For example, if the API responds with "fooBar": true but we've defined a foo_bar: bool property, the output will use the "fooBar" key (unless use_api_names=False is passed).

to_dict(*, mode: Literal['json', 'python'] = 'python', use_api_names: bool = True, exclude_unset: bool = True, exclude_defaults: bool = False, exclude_none: bool = False, warnings: bool = True) -> dict[str, object]

Parameters

Name	Description
mode Required	If mode is 'json', the dictionary will only contain JSON serializable types. e.g. datetime will be turned into a string, "2024-3-22T18:11:19.117000Z". If mode is 'python', the dictionary may contain any Python objects. e.g. datetime(2024, 3, 22)
use_api_names Required	Whether to use the key that the API responded with or the property name. Defaults to True.
exclude_unset Required	Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	Whether to exclude fields that are set to their default value from the output.
exclude_none Required	Whether to exclude fields that have a value of None from the output.
warnings Required	Whether to log warnings when invalid fields are encountered. This is only supported in Pydantic v2.

Keyword-Only Parameters

Name	Description
mode	Default value: python
use_api_names	Default value: True
exclude_unset	Default value: True
exclude_defaults	Default value: False
exclude_none	Default value: False
warnings	Default value: True

to_json

Generates a JSON string representing this model as it would be received from or sent to the API (but with indentation).

By default, fields that were not set by the API will not be included, and keys will match the API response, not the property names from the model.

For example, if the API responds with "fooBar": true but we've defined a foo_bar: bool property, the output will use the "fooBar" key (unless use_api_names=False is passed).

to_json(*, indent: int | None = 2, use_api_names: bool = True, exclude_unset: bool = True, exclude_defaults: bool = False, exclude_none: bool = False, warnings: bool = True) -> str

Parameters

Name	Description
indent Required	Indentation to use in the JSON output. If None is passed, the output will be compact. Defaults to 2
use_api_names Required	Whether to use the key that the API responded with or the property name. Defaults to True.
exclude_unset Required	Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	Whether to exclude fields that have the default value.
exclude_none Required	Whether to exclude fields that have a value of None.
warnings Required	Whether to show any warnings that occurred during serialization. This is only supported in Pydantic v2.

Keyword-Only Parameters

Name	Description
indent	Default value: 2
use_api_names	Default value: True
exclude_unset	Default value: True
exclude_defaults	Default value: False
exclude_none	Default value: False
warnings	Default value: True

update_forward_refs

update_forward_refs(**localns: Any) -> None

validate

validate(value: Any) -> Self

Parameters

Name	Description
value Required

Attributes

created_at

Unix timestamp (in seconds) when the compacted conversation was created.

created_at: int

id

The unique identifier for the compacted response.

id: str

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_config: ClassVar[ConfigDict] = {'defer_build': True, 'extra': 'allow'}

model_extra

Get extra fields set during validation.

Returns

Type	Description
	A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Returns

Type	Description
	A set of strings representing the fields that have been set, i.e. that were not filled from defaults.

object

The object type. Always response.compaction.

object: Literal['response.compaction']

output

The compacted list of output items.

This is a list of all user messages, followed by a single compaction item.

output: List[ResponseOutputMessage | ResponseFileSearchToolCall | ResponseFunctionToolCall | ResponseFunctionWebSearch | ResponseComputerToolCall | ResponseReasoningItem | ResponseCompactionItem | ImageGenerationCall | ResponseCodeInterpreterToolCall | LocalShellCall | ResponseFunctionShellToolCall | ResponseFunctionShellToolCallOutput | ResponseApplyPatchToolCall | ResponseApplyPatchToolCallOutput | McpCall | McpListTools | McpApprovalRequest | ResponseCustomToolCall]

usage

Token accounting for the compaction pass, including cached, reasoning, and total tokens.

usage: ResponseUsage

model_computed_fields

model_computed_fields = {}

model_fields

model_fields = {'created_at': FieldInfo(annotation=int, required=True), 'id': FieldInfo(annotation=str, required=True), 'object': FieldInfo(annotation=Literal['response.compaction'], required=True), 'output': FieldInfo(annotation=List[Annotated[Union[ResponseOutputMessage, ResponseFileSearchToolCall, ResponseFunctionToolCall, ResponseFunctionWebSearch, ResponseComputerToolCall, ResponseReasoningItem, ResponseCompactionItem, ImageGenerationCall, ResponseCodeInterpreterToolCall, LocalShellCall, ResponseFunctionShellToolCall, ResponseFunctionShellToolCallOutput, ResponseApplyPatchToolCall, ResponseApplyPatchToolCallOutput, McpCall, McpListTools, McpApprovalRequest, ResponseCustomToolCall], PropertyInfo]], required=True), 'usage': FieldInfo(annotation=ResponseUsage, required=True)}