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| """ | |
| InboxIQ — Pydantic models for the OpenEnv RL interface. | |
| Typed Observation, Action, and Reward models per OpenEnv spec. | |
| """ | |
| from pydantic import BaseModel, Field | |
| from typing import Literal, List, Dict, Any, Optional | |
| class Action(BaseModel): | |
| """Agent action — choose a triage operation for a specific email.""" | |
| action_type: Literal["open", "delete", "defer", "escalate"] = Field( | |
| description="The triage action: open (process), delete (remove), defer (delay), escalate (priority)" | |
| ) | |
| email_id: str = Field(description="Unique identifier of the target email") | |
| class EmailItem(BaseModel): | |
| """Single email in the inbox observation.""" | |
| id: str | |
| sender: str = "" | |
| subject: str = "" | |
| type: str = "WORK" | |
| urgency: str = "MEDIUM" | |
| sentiment: str = "Professional" | |
| sentiment_confidence: float = 0.5 | |
| spam_score: float = 0.0 | |
| confidence: float = 0.5 | |
| wait: int = 0 | |
| class Observation(BaseModel): | |
| """Environment observation returned after reset/step.""" | |
| inbox: List[Dict[str, Any]] = Field(default_factory=list) | |
| steps: int = 0 | |
| task: str = "train" | |
| max_steps: int = 10 | |
| total_reward: float = 0.0 | |
| classifier_stats: Optional[Dict[str, Any]] = None | |
| reward: float = 0.0 | |
| done: bool = False | |
| info: Optional[Dict[str, Any]] = None | |
| error_trace: Optional[str] = Field( | |
| default=None, | |
| description="Specific error messages generated by malformed tool calls or invalid state transitions", | |
| ) | |
| step_feedback: Optional[str] = Field( | |
| default=None, | |
| description="Micro-rewards, qualitative hints, or penalties generated immediately after the action", | |
| ) | |
| html_observation: Optional[str] = Field( | |
| default=None, | |
| description="Visual representation of the inbox state as an HTML table for multi-modal agents", | |
| ) | |
| class StepResult(BaseModel): | |
| """Result returned by the step endpoint.""" | |
| observation: Dict[str, Any] | |
| reward: float | |
| done: bool | |
| class State(BaseModel): | |
| """Environment state tracking episode progress.""" | |
| episode_id: str | |
| step_count: int | |
| seed: Optional[int] = None | |
| class GraderResult(BaseModel): | |
| """Grader score for the current episode.""" | |
| score: float = Field(gt=0.0, lt=1.0) | |
| total_reward: float | |
| task: str | |