GoalEvaluation (agents/goal_state.py)

Defines typed dictionaries for goal evaluation and state in an agent system.

# Source: https://github.com/bytedance/deer-flow | License: MIT | Copyright 2025 Bytedance Ltd. and/or its affiliates
# Provided via justclaw.it.com; keep this notice with the code.
from __future__ import annotations

from typing import Any, Literal, NotRequired, TypedDict

GoalBlocker = Literal[
    "none",
    "missing_evidence",
    "needs_user_input",
    "run_failed",
    "external_wait",
    "goal_not_met_yet",
]


class GoalEvaluation(TypedDict):
    satisfied: bool
    blocker: GoalBlocker
    reason: str
    evidence_summary: NotRequired[str]
    relied_on_assumption: NotRequired[bool]


class GoalState(TypedDict):
    objective: str
    status: Literal["active"]
    created_at: str
    updated_at: str
    continuation_count: int
    max_continuations: int
    no_progress_count: i

... (truncated -- full source via MCP)