tasc-hpc-daemon 0.1.1

HPC cluster daemon for bridging AI agents to remote compute resources

HPC Daemon

A lightweight daemon that runs on HPC clusters or remote servers, bridging AI agents to local PTY shells and SLURM job schedulers over WebSocket.

How It Works

AI agents run in isolated cloud sandboxes and cannot directly reach machines behind firewalls. The daemon solves this with a reverse-proxy pattern:

1. The daemon runs on your server and opens an outbound WebSocket to the Tiptree platform
2. The agent client also connects outbound to the same platform
3. The platform routes messages between them, keyed on your user identity

Because the daemon initiates the connection, no inbound firewall rules are needed.

Execution Modes

• PTY mode (synchronous) — interactive shell sessions for quick commands
• Job mode (asynchronous) — batch job submission with automatic wake-on-complete callbacks that are persisted locally and retried until delivery succeeds

The daemon auto-detects SLURM. If sbatch is available, jobs go through SLURM; otherwise they run as local background processes.

Installation

• Python 3.10+
• A Tiptree account

pip install tasc-hpc-daemon

This installs the hpc-daemon command and its only dependency (websockets).

Setup

hpc-daemon setup \
    --email [e-mail] \
    --url https://althea.tiptreesystems.com

For the development environment, use:

hpc-daemon setup \
    --email [e-mail] \
    --url https://althea.dev.tiptreesystems.com

The --url value must be the Tiptree app/platform base URL that exposes /otp, /auth, and /hpc routes. Do not use the marketing domain, such as https://tiptreesystems.com or https://dev.tiptreesystems.com.

The setup wizard:

1. Authenticates via a one-time code sent to your email
2. Presents a disclaimer about remote code execution risks
3. Creates an API key for daemon authentication
4. Prompts for an optional skill (built-in cluster-specific guidance, or a custom server description)
5. Prompts for directory restrictions (where the agent is allowed to write; defaults to $SCRATCH/tiptree-workspace or ~/tiptree-workspace)
6. Prompts for a job working directory and optional server instructions
7. Registers the daemon with the platform

The daemon ID defaults to the machine's hostname. Override with --daemon-id.

Re-running setup for the same daemon ID updates the existing profile (no duplicates).

Non-Interactive Setup

For automated deployments:

hpc-daemon setup \
    --email [e-mail] \
    --url https://althea.tiptreesystems.com \
    --no-interview \
    --allowed-dirs ~/workspace ~/scratch \
    --skill mila-hpc \
    --cluster-name my-cluster

Use --cluster-name to set a human-readable name for the cluster (defaults to the machine's hostname).

Warning: --no-interview skips all interactive prompts (disclaimer, skill selection, directory restrictions, working directory, server instructions). OTP is still required. Without --allowed-dirs, the agent gets unrestricted filesystem write access.

Running

# Start in foreground
hpc-daemon start

# Start in background (persists after logout)
nohup hpc-daemon start 2>&1 &

# Check status
hpc-daemon status

# View logs
tail -f ~/.hpc_daemon/<daemon_id>.log

# Stop
hpc-daemon stop

# List registered daemons
hpc-daemon list

If only one daemon profile exists, --daemon-id is auto-detected. With multiple profiles, specify it explicitly (e.g., hpc-daemon start --daemon-id mila-login-1).

To force local mode on a SLURM cluster (jobs run as background processes instead of sbatch):

LOCAL_MODE=1 hpc-daemon start

State

All configuration, job records, and callback delivery state are stored in ~/.hpc_daemon/state.db (SQLite). PID files and logs live in the same directory.

Safety

The daemon enforces directory restrictions via bash function wrappers injected into PTY sessions. File-modifying commands (rm, rmdir, mv, cp, mkdir, touch, tee), directory navigation (cd, pushd, popd), and output redirections are validated against the allowed directory list configured during setup.

Job ownership is also enforced: code assistants can only cancel jobs they submitted.

These guardrails are shell-level and not a hard security boundary. They prevent accidental damage, not a determined adversary.

Shared machines: Your API key is stored in ~/.hpc_daemon/state.db. The file and directory are restricted to your user account (0600/0700), so other users on the same login node cannot read it. However, if multiple people share the same Unix account, they all have access. Do not use the daemon on a shared account.

Project Structure

hpc_daemon/
├── core/
│   ├── cli.py            # CLI (setup, start, stop, status, list)
│   ├── config.py         # Runtime config, SLURM detection
│   ├── ws.py             # WebSocket connection and message routing
│   └── pty_session.py    # PTY shell session management
├── setup/
│   ├── wizard.py         # Setup wizard and daemon registration
│   └── prompts.py        # Interactive setup prompts
├── jobs/
│   ├── handlers.py       # Job submit/status handlers
│   ├── interfaces.py     # SlurmInterface, LocalJobInterface
│   ├── models.py         # JobRecord, JobState
│   └── monitor.py        # Background job polling and callbacks
├── api_client/
│   ├── auth.py           # OTP signin, API key creation
│   ├── daemon_registry.py # Daemon registration
│   └── http.py           # HTTP client utilities
├── skills/
│   ├── __init__.py       # Skill discovery and loading
│   └── mila-hpc.md       # Built-in Mila cluster skill
├── db.py                 # SQLite database (profiles, jobs)
├── guardrails.py         # Directory restriction enforcement
└── __main__.py           # Entry point