KnowledgeBaseListResponseKnowledgebasesInner

class openapi_client.models.knowledge_base_list_response_knowledgebases_inner.KnowledgeBaseListResponseKnowledgebasesInner(**data)

Bases: BaseModel

knowledgebase_id: Optional[StrictStr]

knowledgebase_name: Optional[StrictStr]

description: Optional[StrictStr]

knowledgebase_status: Optional[StrictStr]

embedding_model: Optional[StrictStr]

last_modified_time: Optional[StrictStr]

access_type: Optional[StrictStr]

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True}

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

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of KnowledgeBaseListResponseKnowledgebasesInner from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of KnowledgeBaseListResponseKnowledgebasesInner from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'access_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='AccessType', alias_priority=2, description='Access type of the knowledge base.'), 'description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Description', alias_priority=2, description='Description of the knowledge base.'), 'embedding_model': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='EmbeddingModel', alias_priority=2, description='Embedding model used for the knowledge base.'), 'knowledgebase_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='KnowledgebaseId', alias_priority=2, description='Unique identifier of the knowledge base.'), 'knowledgebase_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='KnowledgebaseName', alias_priority=2, description='Name of the knowledge base.'), 'knowledgebase_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='KnowledgebaseStatus', alias_priority=2, description='Current status of the knowledge base.'), 'last_modified_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LastModifiedTime', alias_priority=2, description='Last Modified time of the knowledge base.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

model_post_init(__context)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• __context (Any) – The context.

Return type:

None