# Endless Terminals Environment -- Default Configuration
#
# Trains agents on terminal tasks from the Endless Terminals HuggingFace dataset.
# Uses hermes-agent backends (modal/docker/local) with per-task Docker images.
# Tests run in the same sandbox the agent used (no separate containers needed).
#
# Dataset: https://huggingface.co/datasets/obiwan96/endless-terminals-train
#
# Prerequisites:
#   1. Download dataset: huggingface-cli download obiwan96/endless-terminals-train \
#        --repo-type dataset --local-dir ~/endless-terminals-data \
#        --local-dir-use-symlinks False
#   2. Set TASKS_BASE_DIR environment variable or configure tasks_base_dir below
#   3. For modal backend: Configure Modal CLI (modal token set)
#   4. For docker backend: Install Docker
#
# Usage:
#   python environments/endless_terminals/endless_terminals_env.py process \
#       --config environments/endless_terminals/default.yaml

env:
  # Toolsets
  enabled_toolsets: ["terminal", "file"]

  # Agent configuration
  max_agent_turns: 32
  max_token_length: 4096
  agent_temperature: 1.0

  # Terminal backend
  terminal_backend: "local"  # Change to "modal" or "docker" for cloud isolation

  # Dataset settings
  use_dataset: true
  dataset_name: "obiwan96/endless-terminals"
  dataset_split: "train"
  dataset_cache_dir: "~/.cache/huggingface/datasets"
  tasks_base_dir: ""  # Set to directory containing task_* folders (e.g., ~/endless-terminals-data)

  # Test execution
  test_timeout_s: 60

  # Training configuration
  group_size: 8
  total_steps: 10000
  steps_per_eval: 500
  num_eval_tasks: 10

  # Logging
  use_wandb: true
  wandb_name: "endless-terminals"

  # System prompt
  system_prompt: >
    You are a skilled Linux system administrator and programmer.
    You have access to a terminal and file tools to complete system administration
    and programming tasks. Use the tools effectively to solve the given task,
    and verify your solution works correctly before finishing.

openai:
  base_url: "https://openrouter.ai/api/v1"
  model_name: "anthropic/claude-sonnet-4.5"
  server_type: "openai"
  api_key: ""  # Loaded from OPENROUTER_API_KEY env var
  health_check: false
  timeout: 30  # 30 second timeout per request
  max_retries: 2  # Only retry twice