hermes-agent/environments/endless_terminals/default.yaml
2026-03-03 14:42:45 -05:00

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# 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
eval_split_ratio: 0.1
# 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