nat.atif.trajectory#

Trajectory (root) model for ATIF (Agent Trajectory Interchange Format).

Attributes#

Classes#

ATIF trajectory — the complete interaction history of an agent run.

Module Contents#

ATIF_VERSION = 'ATIF-v1.6'#

class Trajectory(/, **data: Any)#

Bases: pydantic.BaseModel

ATIF trajectory — the complete interaction history of an agent run.

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.

schema_version: Literal['ATIF-v1.0', 'ATIF-v1.1', 'ATIF-v1.2', 'ATIF-v1.3', 'ATIF-v1.4', 'ATIF-v1.5', 'ATIF-v1.6'] = None#

session_id: str = None#

agent: nat.atif.agent.Agent = None#

steps: list[nat.atif.step.Step] = None#

notes: str | None = None#

final_metrics: nat.atif.final_metrics.FinalMetrics | None = None#

continued_trajectory_ref: str | None = None#

extra: dict[str, Any] | None = None#

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

to_json_dict(exclude_none: bool = True) → dict[str, Any]#: Export trajectory to a dictionary suitable for JSON serialization.

validate_step_ids() → Trajectory#: Validate that step_ids are sequential starting from 1.

validate_tool_call_references() → Trajectory#: Validate that observation source_call_ids reference valid tool_call_ids.

has_multimodal_content() → bool#: Check if any step contains multimodal content (images).