ChatMessageRequest Class

Request payload for sending chat history to MCP platform.

This model represents the complete request body sent to the MCP platform's chat history endpoint for threat protection analysis. It includes the current conversation context and historical messages.

The model uses field aliases to serialize to camelCase JSON format as required by the MCP platform API.

Constructor

pydantic model ChatMessageRequest

Keyword-Only Parameters

Name	Description
conversationId Required
messageId Required
userMessage Required
chatHistory Required

Examples


>>> from microsoft_agents_a365.tooling.models import ChatHistoryMessage
>>> request = ChatMessageRequest(
...     conversation_id="conv-123",
...     message_id="msg-456",
...     user_message="What is the weather today?",
...     chat_history=[
...         ChatHistoryMessage(role="user", content="Hello"),
...         ChatHistoryMessage(role="assistant", content="Hi there!"),
...     ]
... )
>>> # Serialize to camelCase JSON
>>> json_dict = request.model_dump(by_alias=True)
>>> print(json_dict["conversationId"])
'conv-123'

Methods

__init__	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.
__new__
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	Creates a new instance of the Model class with validated data. Creates a new model setting dict and pydantic_fields_set from trusted or pre-validated data. Default values are respected, but no other validation is performed. !!! note model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance's dict and pydantic_extra fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.
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.
not_empty	Validate that string fields are not empty or whitespace-only.
parse_file
parse_obj
parse_raw
schema
schema_json
update_forward_refs
validate

init

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.

__init__(**data: Any) -> None

Parameters

Name	Description
data Required	Any

Returns

Type	Description
None

new

__new__(**kwargs)

construct

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

Parameters

Name	Description
_fields_set	set[str] \| None Default value: None
values Required	Any

Returns

Type	Description
Self

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	<xref:AbstractSetIntStr> \| <xref:MappingIntStrAny> \| None Optional set or mapping specifying which fields to include in the copied model.
exclude Required	<xref:AbstractSetIntStr> \| <xref:MappingIntStrAny> \| None Optional set or mapping specifying which fields to exclude in the copied model.
update Required	Dict[str, Any] \| None Optional dictionary of field-value pairs to override field values in the copied model.
deep Required	bool 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
Self	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]

Parameters

Name	Description
include Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None
exclude Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None
by_alias Required	bool
exclude_unset Required	bool
exclude_defaults Required	bool
exclude_none Required	bool

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

Returns

Type	Description
Dict[str, Any]

from_orm

from_orm(obj: Any) -> Self

Parameters

Name	Description
obj Required	Any

Returns

Type	Description
Self

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

Parameters

Name	Description
include Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None
exclude Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None
by_alias Required	bool
exclude_unset Required	bool
exclude_defaults Required	bool
exclude_none Required	bool
encoder Required	Callable[[Any], Any] \| None
models_as_dict Required	bool
dumps_kwargs Required	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
encoder	Default value: PydanticUndefined
models_as_dict	Default value: PydanticUndefined

Returns

Type	Description
str

model_construct

Creates a new instance of the Model class with validated data.

Creates a new model setting dict and pydantic_fields_set from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance's dict and pydantic_extra fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

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

Parameters

Name	Description
_fields_set	set[str] \| None A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used. Default value: None
values Required	Any Trusted or pre-validated data dictionary.

Returns

Type	Description
Self	A new instance of the Model class with validated data.

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	Mapping[str, Any] \| None 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	bool 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
Self	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, polymorphic_serialization: bool | None = None) -> dict[str, Any]

Parameters

Name	Description
mode Required	Literal['json', 'python'] \| str 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	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None A set of fields to include in the output.
exclude Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None A set of fields to exclude from the output.
context Required	Any \| None Additional context to pass to the serializer.
by_alias Required	bool \| None Whether to use the field's alias in the dictionary key if defined.
exclude_unset Required	bool Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	bool Whether to exclude fields that are set to their default value.
exclude_none Required	bool Whether to exclude fields that have a value of None.
exclude_computed_fields Required	bool 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	bool If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings Required	bool \| Literal['none', 'warn', 'error'] How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback Required	Callable[[Any], Any] \| None 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	bool Whether to serialize fields with duck-typing serialization behavior.
polymorphic_serialization Required	bool \| None Whether to use model and dataclass polymorphic serialization for this call.

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
polymorphic_serialization	Default value: None

Returns

Type	Description
dict[str, Any]	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, polymorphic_serialization: bool | None = None) -> str

Parameters

Name	Description
indent Required	int \| None Indentation to use in the JSON output. If None is passed, the output will be compact.
ensure_ascii Required	bool 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	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None Field(s) to include in the JSON output.
exclude Required	set[int] \| set[str] \| Mapping[int, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| Mapping[str, set[int] \| set[str] \| Mapping[int, <xref:IncEx> \| bool] \| Mapping[str, <xref:IncEx> \| bool] \| bool] \| None Field(s) to exclude from the JSON output.
context Required	Any \| None Additional context to pass to the serializer.
by_alias Required	bool \| None Whether to serialize using field aliases.
exclude_unset Required	bool Whether to exclude fields that have not been explicitly set.
exclude_defaults Required	bool Whether to exclude fields that are set to their default value.
exclude_none Required	bool Whether to exclude fields that have a value of None.
exclude_computed_fields Required	bool 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	bool If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings Required	bool \| Literal['none', 'warn', 'error'] How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback Required	Callable[[Any], Any] \| None 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	bool Whether to serialize fields with duck-typing serialization behavior.
polymorphic_serialization Required	bool \| None Whether to use model and dataclass polymorphic serialization for this call.

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
polymorphic_serialization	Default value: None

Returns

Type	Description
str	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 = DEFAULT_REF_TEMPLATE, schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema, mode: Literal['validation', 'serialization'] = 'validation', *, union_format: Literal['any_of', 'primitive_type_array'] = 'any_of') -> dict[str, Any]

Parameters

Name	Description
by_alias	bool Whether to use attribute aliases or not. Default value: True
ref_template	str The reference template. Default value: DEFAULT_REF_TEMPLATE
union_format Required	Literal['any_of', 'primitive_type_array'] 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	type[<xref:pydantic.json_schema.GenerateJsonSchema>] To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications Default value: GenerateJsonSchema
mode	Literal['validation', 'serialization'] 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
dict[str, Any]	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[type[Any], ...] 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
str	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

Parameters

Name	Description
context Required	Any

Returns

Type	Description
None

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	bool Whether to force the rebuilding of the model schema, defaults to False.
raise_errors Required	bool Whether to raise errors, defaults to True.
_parent_namespace_depth Required	int The depth level of the parent namespace, defaults to 2.
_types_namespace Required	<xref:MappingNamespace> \| None 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
bool \| None	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	Any The object to validate.
strict Required	bool \| None Whether to enforce types strictly.
extra Required	Literal['allow', 'ignore', 'forbid'] \| None Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
from_attributes Required	bool \| None Whether to extract data from object attributes.
context Required	Any \| None Additional context to pass to the validator.
by_alias Required	bool \| None Whether to use the field's alias when validating against the provided input data.
by_name Required	bool \| None 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
Self	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	str \| bytes \| bytearray The JSON data to validate.
strict Required	bool \| None Whether to enforce types strictly.
extra Required	Literal['allow', 'ignore', 'forbid'] \| None Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context Required	Any \| None Extra variables to pass to the validator.
by_alias Required	bool \| None Whether to use the field's alias when validating against the provided input data.
by_name Required	bool \| None 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
Self	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	Any The object containing string data to validate.
strict Required	bool \| None Whether to enforce types strictly.
extra Required	Literal['allow', 'ignore', 'forbid'] \| None Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context Required	Any \| None Extra variables to pass to the validator.
by_alias Required	bool \| None Whether to use the field's alias when validating against the provided input data.
by_name Required	bool \| None 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
Self	The validated Pydantic model.

not_empty

Validate that string fields are not empty or whitespace-only.

validator not_empty  »  message_id, conversation_id, user_message

Parameters

Name	Description
v Required	str

Returns

Type	Description
str

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	str \| <xref:Path>
content_type Required	str \| None
encoding Required	str
proto Required	<xref:DeprecatedParseProtocol> \| None
allow_pickle Required	bool

Keyword-Only Parameters

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

Returns

Type	Description
Self

parse_obj

parse_obj(obj: Any) -> Self

Parameters

Name	Description
obj Required	Any

Returns

Type	Description
Self

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	str \| bytes
content_type Required	str \| None
encoding Required	str
proto Required	<xref:DeprecatedParseProtocol> \| None
allow_pickle Required	bool

Keyword-Only Parameters

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

Returns

Type	Description
Self

schema

schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE) -> Dict[str, Any]

Parameters

Name	Description
by_alias	bool Default value: True
ref_template	str Default value: DEFAULT_REF_TEMPLATE

Returns

Type	Description
Dict[str, Any]

schema_json

schema_json(*, by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, **dumps_kwargs: Any) -> str

Parameters

Name	Description
by_alias Required	bool
ref_template Required	str
dumps_kwargs Required	Any

Keyword-Only Parameters

Name	Description
by_alias	Default value: True
ref_template	Default value: DEFAULT_REF_TEMPLATE

Returns

Type	Description
str

update_forward_refs

update_forward_refs(**localns: Any) -> None

Parameters

Name	Description
localns Required	Any

Returns

Type	Description
None

validate

validate(value: Any) -> Self

Parameters

Name	Description
value Required	Any

Returns

Type	Description
Self

Attributes

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.

conversation_id

Unique identifier for the conversation.

field conversation_id: str [Required] (alias 'conversationId')

message_id

Unique identifier for the current message.

field message_id: str [Required] (alias 'messageId')

user_message

The current user message being processed.

field user_message: str [Required] (alias 'userMessage')

chat_history

List of previous messages in the conversation.

field chat_history: List[ChatHistoryMessage] [Required] (alias 'chatHistory')