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| """Action, observation and state of the Scott Wu Math environment.""" | |
| from __future__ import annotations | |
| from typing import Any, Optional | |
| from openenv.core.env_server.types import Action, Observation, State | |
| from pydantic import Field | |
| class CardAction(Action): | |
| """The one move of an episode: the final expression. An empty expression gives up.""" | |
| expression: str = Field( | |
| default="", | |
| description="Arithmetic over the card values using each card once, e.g. '(13 - 12 + 11 - 10 + 7) * 9 * 5 * 5'", | |
| ) | |
| class CardObservation(Observation): | |
| task_id: str = Field(default="", description="Task identifier") | |
| level: str = Field(default="", description="24, three-digit, year, four-digit or custom") | |
| target: int = Field(default=0, description="The number to make") | |
| cards: list[dict[str, Any]] = Field(default_factory=list, description="Dealt cards: rank (1-13), suit (S H D C), label") | |
| prompt: str = Field(default="", description="The user prompt a language model reads") | |
| system_prompt: str = Field(default="", description="The system prompt a language model reads") | |
| result: Optional[dict[str, Any]] = Field(default=None, description="Grader output after the submission") | |
| solution: Optional[str] = Field(default=None, description="A reference solution, shown only once the episode is over") | |
| solution_steps: list[str] = Field(default_factory=list, description="The reference solution one combination at a time") | |
| elapsed_s: Optional[float] = Field(default=None, description="Seconds from reset to submission") | |
| class CardState(State): | |
| task_id: str = "" | |
| level: str = "" | |
| target: int = 0 | |
| cards: list[dict[str, Any]] = Field(default_factory=list) | |
| submitted: bool = False | |
| reward_mode: str = "shaped" | |