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Eight.ly Agent Training Dataset

Training data for Eight.ly OS Nova AI assistant tool calling. Used to fine-tune FunctionGemma 270M, Qwen3 4B/8B, and Gemma 4 E2B for NAS management via natural language.

Dataset Files

File	Examples	Description
`merged-dataset.jsonl`	4,909	Combined dataset (tool calls + no-tool), used for latest FunctionGemma training
`nova-tool-calling-dataset.jsonl`	4,684	Original tool-calling dataset across 41 tools
`no-tool-examples.jsonl`	225	No-tool examples (greetings, general knowledge, opinions) to reduce over-triggering
`eval_dataset.jsonl`	200	Held-out evaluation set
`tools.json`	41	Tool schemas in OpenAI function-calling format

Format

Each line in the JSONL files is a conversation in OpenAI chat format:

{
  "messages": [
    {"role": "system", "content": "You are Nova, the AI assistant for Eight.ly NAS OS..."},
    {"role": "user", "content": "How much disk space is free?"},
    {"role": "assistant", "tool_calls": [{"function": {"name": "get_storage_status", "arguments": {}}}]},
    {"role": "tool", "content": "{\"total_gb\": 100, \"free_gb\": 74}"},
    {"role": "assistant", "content": "You have 74 GB free out of 100 GB total storage."}
  ]
}

41 Tools

Docker (10): list_containers, get_container_logs, get_container_stats, list_docker_stacks, list_docker_images, list_docker_networks, list_docker_volumes, container_action, pull_docker_image, install_app

Storage (9): get_storage_status, get_cache_status, get_snapraid_status, get_disk_health, get_zfs_pools, run_snapraid_sync, run_smart_test, spin_down_disks, create_backup

VMs (5): list_vms, get_vm_stats, list_vm_snapshots, vm_action, create_vm_snapshot

LXC (2): list_lxc_containers, lxc_action

File Sharing (4): get_smb_shares, get_nfs_exports, create_smb_share, create_nfs_export

System (11): get_system_info, get_system_version, get_system_logs, get_node_time, get_network_interfaces, get_firewall_rules, get_health_overview, get_nova_models, search_apps, set_timezone, reboot_system

Training

See the model repo for trained GGUFs and the GitHub repo for training scripts.

Dataset Generation

Generated with augmentation scripts:

generate_dataset.py — base dataset from tool definitions
augment_negatives.py — hard negative examples (143)
augment_errors.py — error recovery examples
augment_grounding.py — grounding examples
augment_multiturn.py — multi-turn conversations
augment_no_tool.py — no-tool examples (225)

License

Apache 2.0

Downloads last month: 11

Total file size:

12.6 MB