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"""
Data models for Warehouse Optimization Environment.
This module defines the Action, Observation, and State dataclasses
for the warehouse logistics optimization environment.
"""
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
# Support both in-repo and standalone imports
try:
# In-repo imports (when running from OpenEnv repository)
from core.env_server import Action, Observation, State
except ImportError:
# Standalone imports (when environment is standalone with openenv-core from pip)
from openenv_core.env_server import Action, Observation, State
@dataclass
class WarehouseAction(Action):
"""
Action for the warehouse robot.
Actions:
0: MOVE_UP - Move robot one cell up
1: MOVE_DOWN - Move robot one cell down
2: MOVE_LEFT - Move robot one cell left
3: MOVE_RIGHT - Move robot one cell right
4: PICK_UP - Pick up package at current location
5: DROP_OFF - Drop off package at current location
"""
action_id: int # 0-5
# Action names for reference
ACTION_NAMES = {
0: "MOVE_UP",
1: "MOVE_DOWN",
2: "MOVE_LEFT",
3: "MOVE_RIGHT",
4: "PICK_UP",
5: "DROP_OFF",
}
def __post_init__(self):
"""Validate action ID."""
if self.action_id not in range(6):
raise ValueError(f"action_id must be 0-5, got {self.action_id}")
@property
def action_name(self) -> str:
"""Get human-readable action name."""
return self.ACTION_NAMES.get(self.action_id, "UNKNOWN")
@dataclass
class Package:
"""Represents a package in the warehouse."""
id: int
status: str # "waiting", "picked", "delivered"
pickup_location: tuple[int, int]
dropoff_location: tuple[int, int]
priority: int # 1 (low), 2 (medium), 3 (high)
time_waiting: int # Steps since created
@dataclass(kw_only=True)
class WarehouseObservation(Observation):
"""
Observation returned after each step in the warehouse environment.
Attributes:
grid: 2D list representing the warehouse layout
0=empty, 1=wall, 2=shelf, 3=pickup_zone, 4=dropoff_zone
robot_position: Current (x, y) position of the robot
robot_carrying: Package ID if carrying, None otherwise
packages: List of all packages and their states
step_count: Current step number in episode
packages_delivered: Number of packages successfully delivered
total_packages: Total number of packages in episode
time_remaining: Steps remaining before timeout
action_success: Whether the last action was successful
message: Human-readable message about last action
"""
grid: List[List[int]]
robot_position: tuple[int, int]
robot_carrying: Optional[int]
packages: List[Dict[str, Any]]
step_count: int
packages_delivered: int
total_packages: int
time_remaining: int
action_success: bool
message: str
metadata: Dict[str, Any] = field(default_factory=dict)
@dataclass(kw_only=True)
class WarehouseState(State):
"""
Episode state tracking for the warehouse environment.
Attributes:
episode_id: Unique identifier for this episode
step_count: Number of steps taken
packages_delivered: Packages successfully delivered
total_packages: Total packages in episode
difficulty_level: Difficulty setting (1-5)
grid_size: (width, height) of warehouse
cum_reward: Cumulative reward for episode
is_done: Whether episode has ended
"""
episode_id: str
step_count: int
packages_delivered: int
total_packages: int
difficulty_level: int
grid_size: tuple[int, int]
cum_reward: float
is_done: bool
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