nat.data_models.intermediate_step

Classes

IntermediateStepCategory	Enum where members are also (and must be) strings
IntermediateStepType	Enum where members are also (and must be) strings
IntermediateStepState	Enum where members are also (and must be) strings
StreamEventData	StreamEventData is a data model that represents the data field in an streaming event.
TTCEventData	TTCEventData is a data model that represents the data field in a TTC event.
UsageInfo
ToolParameters
ToolDetails
ToolSchema
ServerToolUseSchema
TraceMetadata
IntermediateStepPayload	IntermediateStep is a data model that represents an intermediate step in the NAT. Intermediate steps are
IntermediateStep	IntermediateStep is a data model that represents an intermediate step in the NAT. Intermediate steps are

Module Contents

class IntermediateStepCategory

Bases: enum.StrEnum

Enum where members are also (and must be) strings

Initialize self. See help(type(self)) for accurate signature.

LLM = 'LLM'

TOOL = 'TOOL'

WORKFLOW = 'WORKFLOW'

TASK = 'TASK'

FUNCTION = 'FUNCTION'

CUSTOM = 'CUSTOM'

SPAN = 'SPAN'

TTC = 'TTC'

class IntermediateStepType

Bases: enum.StrEnum

Enum where members are also (and must be) strings

Initialize self. See help(type(self)) for accurate signature.

LLM_START = 'LLM_START'

LLM_END = 'LLM_END'

LLM_NEW_TOKEN = 'LLM_NEW_TOKEN'

TOOL_START = 'TOOL_START'

TOOL_END = 'TOOL_END'

WORKFLOW_START = 'WORKFLOW_START'

WORKFLOW_END = 'WORKFLOW_END'

TASK_START = 'TASK_START'

TASK_END = 'TASK_END'

TTC_START = 'TTC_START'

TTC_END = 'TTC_END'

FUNCTION_START = 'FUNCTION_START'

FUNCTION_END = 'FUNCTION_END'

CUSTOM_START = 'CUSTOM_START'

CUSTOM_END = 'CUSTOM_END'

SPAN_START = 'SPAN_START'

SPAN_CHUNK = 'SPAN_CHUNK'

SPAN_END = 'SPAN_END'

class IntermediateStepState

Bases: enum.StrEnum

Enum where members are also (and must be) strings

Initialize self. See help(type(self)) for accurate signature.

START = 'START'

CHUNK = 'CHUNK'

END = 'END'

class StreamEventData(/, **data: Any)

Bases: pydantic.BaseModel

StreamEventData is a data model that represents the data field in an streaming event.

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.

model_config

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

input: Any | None = None

output: Any | None = None

chunk: Any | None = None

payload: Any | None = None

class TTCEventData(/, **data: Any)

Bases: StreamEventData

TTCEventData is a data model that represents the data field in a TTC event.

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.

model_config

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

turn_id: str | None = None

turn_index: int | None = None

candidate_index: int | None = None

score: float | None = None

class UsageInfo(/, **data: Any)

Bases: pydantic.BaseModel

token_usage: nat.data_models.token_usage.TokenUsageBaseModel

num_llm_calls: int = 0

seconds_between_calls: int = 0

class ToolParameters(/, **data: Any)

Bases: pydantic.BaseModel

properties: dict[str, Any] = None

required: list[str] = None

type_: Literal['object'] = None

additionalProperties: bool = None

strict: bool = None

class ToolDetails(/, **data: Any)

Bases: pydantic.BaseModel

name: str = None

description: str = None

parameters: ToolParameters = None

class ToolSchema(/, **data: Any)

Bases: pydantic.BaseModel

type: Literal['function'] = None

function: ToolDetails = None

class ServerToolUseSchema(/, **data: Any)

Bases: pydantic.BaseModel

name: str

arguments: str | dict[str, Any] | Any

output: Any

model_config

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

class TraceMetadata(/, **data: Any)

Bases: pydantic.BaseModel

chat_responses: Any | None = None

chat_inputs: Any | None = None

tool_inputs: Any | None = None

tool_outputs: list[ServerToolUseSchema] | Any | None = None

tool_info: Any | None = None

span_inputs: Any | None = None

span_outputs: Any | None = None

provided_metadata: Any | None = None

tools_schema: list[ToolSchema] = None

model_config

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

class IntermediateStepPayload(/, **data: Any)

Bases: pydantic.BaseModel

IntermediateStep is a data model that represents an intermediate step in the NAT. Intermediate steps are captured while a request is running and can be used to show progress or to evaluate the path a workflow took to get a response.

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.

model_config

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

event_type: IntermediateStepType

event_timestamp: float = None

span_event_timestamp: float | None = None

framework: nat.builder.framework_enum.LLMFrameworkEnum | None = None

name: str | None = None

tags: list[str] | None = None

metadata: dict[str, Any] | TraceMetadata | None = None

data: pydantic.SerializeAsAny[StreamEventData] | None = None

usage_info: UsageInfo | None = None

UUID: str = None

property event_category: IntermediateStepCategory

property event_state: IntermediateStepState

check_span_event_timestamp() → IntermediateStepPayload

class IntermediateStep(/, **data: Any)

Bases: pydantic.BaseModel

IntermediateStep is a data model that represents an intermediate step in the NAT. Intermediate steps are captured while a request is running and can be used to show progress or to evaluate the path a workflow took to get a response.

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.

model_config

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

parent_id: str

The parent step ID for the current step. The parent ID is the ID of the last START step which has a different UUID than the current step. This value is different from the function_ancestry.parent_id value which tracks the last parent FUNCTION step. For the first START step, the parent_id is ‘root’.

function_ancestry: nat.data_models.invocation_node.InvocationNode

The function ancestry for the current step showing the current NAT function that was being executed when the step was created.

payload: IntermediateStepPayload

The payload for the current step.

property event_type: IntermediateStepType

property event_timestamp: float

property span_event_timestamp: float | None

property framework: nat.builder.framework_enum.LLMFrameworkEnum | None

property name: str | None

property tags: list[str] | None

property metadata: dict[str, Any] | TraceMetadata | None

property data: StreamEventData | None

property usage_info: UsageInfo | None

property UUID: str

property event_category: IntermediateStepCategory

property event_state: IntermediateStepState