whylogs_container.whylabs.container.requests

Classes

DebugLLMValidateRequest(*[, prompt, ...])
EmbeddingRequest(*[, prompt, response, context])
Endpoints(value)	An enumeration.
LLMValidateRequest(*[, prompt, response, ...])
LogEmbeddingRequest(*, dataset_id, ...)
LogMultiple(*, columns, data)
LogRequest(*, datasetId, multiple[, timestamp])
PubSubMessage(*, attributes, data, ...)
PubSubRequest(*, subscription, message)

class whylogs_container.whylabs.container.requests.DebugLLMValidateRequest(*, prompt: str | None = None, response: str | None = None, context: InputContext | None = None, id: str | None = None, datasetId: str, timestamp: int = None, additional_data: Dict[str, str | int | float] = None, options: RunOptions | None = None, policy: str)

Bases: LLMValidateRequest

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'frozen': True, 'populate_by_name': True}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'additional_data': FieldInfo(annotation=Dict[str, Union[str, int, float]], required=False, default_factory=<lambda>), 'context': FieldInfo(annotation=Union[InputContext, NoneType], required=False, default=None), 'dataset_id': FieldInfo(annotation=str, required=True, alias='datasetId', alias_priority=2), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'options': FieldInfo(annotation=Union[RunOptions, NoneType], required=False, default=None), 'policy': FieldInfo(annotation=str, required=True), 'prompt': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'response': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'timestamp': FieldInfo(annotation=int, required=False, default_factory=<lambda>)}

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

This replaces Model.__fields__ from Pydantic V1.

policy: str

class whylogs_container.whylabs.container.requests.EmbeddingRequest(*, prompt: str | None = None, response: str | None = None, context: InputContext | None = None)

Bases: BaseModel

context: InputContext | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'frozen': True, 'populate_by_name': True}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'context': FieldInfo(annotation=Union[InputContext, NoneType], required=False, default=None), 'prompt': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'response': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

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

This replaces Model.__fields__ from Pydantic V1.

prompt: str | None

response: str | None

class whylogs_container.whylabs.container.requests.Endpoints(value)

Bases: Enum

An enumeration.

DebugEvaluate = '/debug/evaluate'

Evaluate = '/evaluate'

LogLLM = '/log/llm'

class whylogs_container.whylabs.container.requests.LLMValidateRequest(*, prompt: str | None = None, response: str | None = None, context: InputContext | None = None, id: str | None = None, datasetId: str, timestamp: int = None, additional_data: Dict[str, str | int | float] = None, options: RunOptions | None = None)

Bases: BaseModel

additional_data: Dict[str, str | int | float]

context: InputContext | None

dataset_id: str

id: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'frozen': True, 'populate_by_name': True}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'additional_data': FieldInfo(annotation=Dict[str, Union[str, int, float]], required=False, default_factory=<lambda>), 'context': FieldInfo(annotation=Union[InputContext, NoneType], required=False, default=None), 'dataset_id': FieldInfo(annotation=str, required=True, alias='datasetId', alias_priority=2), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'options': FieldInfo(annotation=Union[RunOptions, NoneType], required=False, default=None), 'prompt': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'response': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'timestamp': FieldInfo(annotation=int, required=False, default_factory=<lambda>)}

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

This replaces Model.__fields__ from Pydantic V1.

options: RunOptions | None

prompt: str | None

classmethod replace_old_times(v: int) → int

response: str | None

timestamp: int

to_data_dict() → DataDict

to_dataframe() → DataFrame

to_row() → Dict[str, str | int | float | InputContext]

class whylogs_container.whylabs.container.requests.LogEmbeddingRequest(*, dataset_id: str, timestamp: int, embeddings: Dict[str, List[List[float]] | List[List[int]] | List[List[str]]])

Bases: BaseModel

datasetId: str

embeddings: Dict[str, List[List[float]] | List[List[int]] | List[List[str]]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'datasetId': FieldInfo(annotation=str, required=True, alias='dataset_id', alias_priority=2), 'embeddings': FieldInfo(annotation=Dict[str, Union[List[List[float]], List[List[int]], List[List[str]]]], required=True), 'timestamp': FieldInfo(annotation=int, required=True)}

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

This replaces Model.__fields__ from Pydantic V1.

timestamp: int

to_log_embedding_request_dict(api_key: WhyLabsApiKey) → LogEmbeddingRequestDict

class whylogs_container.whylabs.container.requests.LogMultiple(*, columns: Sequence[str], data: Sequence[Sequence[str | int | float | bool | List[float] | List[int] | List[str] | None | List[List[float]] | List[List[int]] | List[List[str]]]])

Bases: BaseModel

columns: Sequence[str]

data: Sequence[Sequence[str | int | float | bool | List[float] | List[int] | List[str] | None | List[List[float]] | List[List[int]] | List[List[str]]]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'columns': FieldInfo(annotation=Sequence[str], required=True), 'data': FieldInfo(annotation=Sequence[Sequence[Union[str, int, float, bool, List[float], List[int], List[str], NoneType, List[List[float]], List[List[int]], List[List[str]]]]], required=True)}

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

This replaces Model.__fields__ from Pydantic V1.

class whylogs_container.whylabs.container.requests.LogRequest(*, datasetId: str, multiple: LogMultiple, timestamp: int | None = None)

Bases: BaseModel

dataset_id: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'dataset_id': FieldInfo(annotation=str, required=True, alias='datasetId', alias_priority=2), 'multiple': FieldInfo(annotation=LogMultiple, required=True), 'timestamp': FieldInfo(annotation=Union[int, NoneType], required=False, default=None)}

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

This replaces Model.__fields__ from Pydantic V1.

multiple: LogMultiple

timestamp: int | None

to_log_request_dict(api_key: WhyLabsApiKey) → LogRequestDict

class whylogs_container.whylabs.container.requests.PubSubMessage(*, attributes: Dict[str, str], data: str, message_id: str, publish_time: str)

Bases: BaseModel

attributes: Dict[str, str]

data: str

messageId: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'attributes': FieldInfo(annotation=Dict[str, str], required=True), 'data': FieldInfo(annotation=str, required=True), 'messageId': FieldInfo(annotation=str, required=True, alias='message_id', alias_priority=2), 'publishTime': FieldInfo(annotation=str, required=True, alias='publish_time', alias_priority=2)}

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

This replaces Model.__fields__ from Pydantic V1.

publishTime: str

class whylogs_container.whylabs.container.requests.PubSubRequest(*, subscription: str, message: PubSubMessage)

Bases: BaseModel

message: PubSubMessage

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'message': FieldInfo(annotation=PubSubMessage, required=True), 'subscription': FieldInfo(annotation=str, required=True)}

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

This replaces Model.__fields__ from Pydantic V1.

subscription: str