openenv.yaml

spec_version: 1
name: gov-workflow-openenv
version: "0.3.0"
type: space
runtime: fastapi
app: app.main:app
port: 7860
description: >
  A real-world OpenEnv environment for government-service workflow control.
  The agent optimizes avoidable administrative delay via priority control,
  document resolution, staffing, escalation, and fairness balancing.

entrypoint:
  module: app.main
  object: app
  inference_script: inference.py

environment:
  class: server.gov_environment.GovWorkflowOpenEnv
  observation_model: app.models.ObservationModel
  action_model: app.models.ActionModel
  reward_model: app.models.RewardModel
  state_model: app.models.EpisodeStateModel
  step_info_model: app.models.StepInfoModel

tasks:
  - id: district_backlog_easy
    seed: 11
    description: >
      Small district office with 3 services and generous SLA windows.
      Tests baseline queue control and document handling.
    grader: app.graders.grade_easy

  - id: mixed_urgency_medium
    seed: 22
    description: >
      Mid-sized office with mixed urgency and tighter fairness requirements.
      Tests urgency prioritization and staffing trade-offs.
    grader: app.graders.grade_medium

  - id: cross_department_hard
    seed: 33
    description: >
      Large cross-department office with high arrivals and strict fairness.
      Tests escalation discipline and multi-queue balancing.
    grader: app.graders.grade_hard

api:
  endpoints:
    - method: GET
      path: /health
      description: Server and session health check
    - method: POST
      path: /reset
      description: Create a new episode session and return initial observation
    - method: POST
      path: /step
      description: Apply one action and advance simulation state
    - method: GET
      path: /state
      description: Return current episode state (query param session_id)
    - method: POST
      path: /state
      description: Return current episode state (body with session_id)
    - method: POST
      path: /grade
      description: Run deterministic task grader for the current episode

metadata:
  domain: government-services
  real_world: true
  reward_type: dense
  action_space: discrete
  observation_space: structured
  deterministic_tasks: true
  deterministic_graders: true
  num_tasks: 3
  framework: fastapi
  language: python

deployment:
  host: 0.0.0.0
  port: 7860
  dockerfile: Dockerfile
  platform: huggingface-spaces
  runtime: docker