spec_version: 1
name: rail_ops
type: space
runtime: fastapi
app: rail_openenv.server:app
port: 7860
description: Rail dispatch on Arriva's single-track Groningen - Leeuwarden line (Netherlands) on real January-June 2025 days - hold, short-turn and cancel trains so opposing trains cross safely after real breakdowns, collisions, signal and points failures (and seeded ones drawn from the 2024-2025 disruption record); graded once on submit against the CP-SAT optimum. 45 eval tasks on held-out weeks, chosen for hardness, and a train pack on the other days.
version: "0.1.0"
variables:
  RAIL_TASKS_DIR: ""          # colon-separated pack directories; defaults to tasks/rail-v1-eval:tasks/rail-v1-train
  RAIL_MAX_CHECKS: "10"
  RAIL_MAX_TOOL_CALLS: "24"
  MAX_CONCURRENT_ENVS: "64"
validation:
  reward:
    range: [0.0, 1.0]
    # oracle/solve.py submits the CP-SAT optimum and scores exactly 1.0; no plan scores 0, any rule broken < 0.2
    oracle_tolerance: 0.001
    floor_margin: 0.5
  resources:
    # pure Python: the grader re-simulates a plan in milliseconds, CP-SAT never runs on the server
    cpu: 2.0
    memory_mb: 2048
    disk_mb: 1024
    episode_timeout_s: 3600.0
  network:
    mode: no-network
  capabilities:
    verifier:
      kind: reward_channel
    oracle:
      form: script
      location: oracle/solve.py
    rubric_tree: true
    task_api: true
    declared_tools: [get_situation, check_plan, submit_plan]
  types:
    tags: [simulation, railway, dispatching, scheduling, operations-research, mcp, real-world-data]