env/models.py

"""
Core models and shared type aliases for SYNAPSE-X.
"""

from typing import Any, Literal

from pydantic import BaseModel, Field, PrivateAttr


ActionType = Literal["execute", "delay", "reallocate"]
ActionPayload = dict[str, Any]


class Task(BaseModel):
    id: int
    name: str
    dependencies: list[int] = Field(default_factory=list, description="IDs of tasks that must complete first")
    release_time: int = Field(0, ge=0, description="Step when the task becomes actionable")
    released: bool = True
    priority: float = Field(..., ge=0.0, le=1.0, description="Task priority 0-1")
    risk: float = Field(..., ge=0.0, le=1.0, description="Execution risk 0-1")
    uncertainty: float = Field(..., ge=0.0, le=1.0, description="PRISM uncertainty 0-1")
    deadline: float = Field(..., description="Steps remaining until deadline")
    completed: bool = False
    failed: bool = False
    future_risk: float = Field(0.0, ge=0.0, description="ECHO predicted future risk")
    deadline_pressure: float = Field(0.0, ge=0.0, le=1.0, description="ECHO deadline pressure")
    resources_required: float = Field(0.1, ge=0.0, le=1.0, description="Resource cost to execute")
    delay_count: int = 0
    _history_risk: float = PrivateAttr(default=0.0)

    @property
    def is_terminal(self) -> bool:
        return self.completed or self.failed

    @property
    def is_active(self) -> bool:
        return self.released and not self.is_terminal


class Observation(BaseModel):
    tasks: list[Task]
    time: int
    resources: float = Field(..., ge=0.0, le=1.0, description="Available resources 0-1")
    episode_done: bool = False


class Action(BaseModel):
    action_type: ActionType
    task_id: int


class StepResult(BaseModel):
    observation: Observation
    reward: float
    done: bool
    info: dict[str, Any]


class GradeResult(BaseModel):
    score: float = Field(..., ge=0.0, le=1.0)
    completion_rate: float
    efficiency: float
    reward_score: float
    details: dict[str, Any]