Spaces:
Sleeping
Sleeping
| """ | |
| models.py — Typed Action / Observation models for the Email Triage environment. | |
| Real-world task: An AI agent reads incoming emails and must: | |
| 1. Classify the email category | |
| 2. Assign a priority level | |
| 3. Route to the correct department + draft an appropriate reply | |
| Action Space: | |
| - category : spam | billing | technical | hr | general | |
| - priority : low | medium | high | urgent | |
| - department : support | finance | engineering | hr | management | |
| - reply : free-text reply draft (required for medium/hard tasks) | |
| Observation Space: | |
| - email_id : unique ID for the current email | |
| - subject : email subject line | |
| - body : email body text | |
| - sender : sender address | |
| - task_level : easy | medium | hard | |
| - feedback : natural-language feedback on the last action | |
| - score : 0.0-1.0 cumulative task score | |
| - done : episode finished flag | |
| - reward : step reward | |
| - emails_remaining: how many emails are left in the episode | |
| """ | |
| from typing import Literal, Optional | |
| from openenv.core.env_server.types import Action, Observation | |
| Category = Literal["spam", "billing", "technical", "hr", "general"] | |
| Priority = Literal["low", "medium", "high", "urgent"] | |
| Department = Literal["support", "finance", "engineering", "hr", "management"] | |
| class TriageAction(Action): | |
| """Agent's triage decision for one email.""" | |
| category: Category | |
| priority: Priority | |
| department: Department | |
| reply: str = "" # Required for medium / hard tasks | |
| class TriageObservation(Observation): | |
| """What the agent sees after each step.""" | |
| email_id: str | |
| subject: str | |
| body: str | |
| sender: str | |
| task_level: Literal["easy", "medium", "hard"] | |
| feedback: str = "" | |
| score: float = 0.0 | |
| emails_remaining: int = 0 | |