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| from __future__ import annotations | |
| from dataclasses import asdict, dataclass, field | |
| from typing import Any | |
| from data_agent_baseline.benchmark.schema import AnswerTable | |
| class StepRecord: | |
| step_index: int | |
| thought: str | |
| action: str | |
| action_input: dict[str, Any] | |
| raw_response: str | |
| observation: dict[str, Any] | |
| ok: bool | |
| def to_dict(self) -> dict[str, Any]: | |
| return asdict(self) | |
| class AgentRuntimeState: | |
| steps: list[StepRecord] = field(default_factory=list) | |
| answer: AnswerTable | None = None | |
| failure_reason: str | None = None | |
| class AgentRunResult: | |
| task_id: str | |
| answer: AnswerTable | None | |
| steps: list[StepRecord] | |
| failure_reason: str | None | |
| def succeeded(self) -> bool: | |
| return self.answer is not None and self.failure_reason is None | |
| def to_dict(self) -> dict[str, Any]: | |
| return { | |
| "task_id": self.task_id, | |
| "answer": self.answer.to_dict() if self.answer is not None else None, | |
| "steps": [step.to_dict() for step in self.steps], | |
| "failure_reason": self.failure_reason, | |
| "succeeded": self.succeeded, | |
| } | |