lockbot

Cluster resource management bot for IM platforms (e.g., Baidu InfoFlow).

Lock and unlock GPU devices, cluster nodes, and queue slots via chat commands. Supports both standalone Flask deployment and a full platform mode with FastAPI + Vue.js frontend.

中文文档 | Live Demo

Features

• Device Lock Bot — Lock/unlock individual GPUs or devices on a cluster
• Node Lock Bot — Lock/unlock entire cluster nodes
• Queue Bot — Manage a queue for resource allocation with booking and preemption
• Platform Mode — Web UI (Vue 3 + Element Plus) for managing multiple bots, user authentication (JWT), role-based access control, and real-time logs
• State Persistence — Bot state survives restarts (JSON file)
• Bilingual — English and Chinese UI and bot responses

Quick Start — Platform Mode (Recommended)

Full management platform with Web UI, multi-bot orchestration, user authentication, and admin panel.

1. Install:

pip install lockbot

2. Set environment variables:

export JWT_SECRET="your-jwt-secret"
export ENCRYPTION_KEY="your-fernet-key"    # python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
export DEV_MODE="true"                      # dev mode, auto-create admin user

3. Start:

# Backend
uvicorn lockbot.backend.app.main:app --host 0.0.0.0 --port 8000 --reload

# Frontend (another terminal)
cd frontend && npm install && npm run dev

4. Open http://localhost:8000 in your browser.

Docker

# 1. Generate ENCRYPTION_KEY and JWT_SECRET
python tools/gen_keys.py

# 2. Pull pre-built image (or build from source)
docker pull ghcr.io/dynamicheart/lockbot:latest
# docker build -f docker/Dockerfile -t lockbot .

# 3. Run (replace the keys with generated values)
docker run -d --name lockbot -p 8000:8000 \
  -e JWT_SECRET=your-secret \
  -e ENCRYPTION_KEY=your-fernet-key \
  -v lockbot-data:/data \
  ghcr.io/dynamicheart/lockbot:latest

# 4. Create super_admin (password auto-generated and printed)
docker exec -it lockbot python tools/create_super_admin.py --username admin --email admin@example.com

Data persistence: All data (SQLite DB, bot state files) stored under /data. Override with DATA_DIR env var.

Bot Configuration

See python/lockbot/core/config.py for the full configuration reference.

Commands

Development

Dev Server

# Install dependencies
pip install -e ".[dev]"
cd frontend && npm install && cd ..

# Start backend (port 8002, hot-reload)
bash scripts/dev/backend.sh

# Start frontend (port 8001, proxies /api/* -> localhost:8002)
bash scripts/dev/frontend.sh

Both servers support hot-reload — code changes take effect automatically.

Testing

# Run tests
pytest

# Lint + format check
ruff check python/ tests/
ruff format --check python/ tests/

Standalone Mode

Single-bot deployment with a lightweight Flask webhook server.

Device Lock Bot (per-GPU locking):

from lockbot.core.bot_instance import BotInstance
from lockbot.core.entry import create_app

instance = BotInstance("DEVICE", {
    "BOT_NAME": "my-gpu-bot",
    "WEBHOOK_URL": "https://your-webhook-url",
    "TOKEN": "your-bot-token",
    "AESKEY": "your-aes-key",
    "CLUSTER_CONFIGS": {
        "node0": ["A800", "A800", "H100"],
        "node1": ["A800", "H100"],
    },
})

app = create_app(bot=instance.bot, bot_name="my-gpu-bot", port=8000)
app.run(host="0.0.0.0", port=8000)

Node Lock Bot / Queue Bot (per-node locking or queue scheduling):

from lockbot.core.bot_instance import BotInstance
from lockbot.core.entry import create_app

instance = BotInstance("NODE", {       # or "QUEUE" for queue scheduling
    "BOT_NAME": "my-node-bot",
    "WEBHOOK_URL": "https://your-webhook-url",
    "TOKEN": "your-bot-token",
    "AESKEY": "your-aes-key",
    "CLUSTER_CONFIGS": ["node0", "node1", "node2", "node3"],
})

app = create_app(bot=instance.bot, bot_name="my-node-bot", port=8000)
app.run(host="0.0.0.0", port=8000)

License

MIT