Deploying to the cloud with Arcade Deploy
This guide shows you how to deploy a worker with a local toolkit with Arcade Deploy.
Requirements
- Python 3.10 or higher
Verify your Python version by runningpython --versionorpython3 --versionin your terminal. - Arcade Account: Sign up for an Arcade account if you haven’t already.
- Arcade CLI: Install the Arcade CLI
uv pip install arcade-aiCreate your deployment config
Create a worker.toml file in your project directory:
### Worker 1
[[worker]]
[worker.config]
id = "my-worker"
secret = <your secret> # Replace with your own secret
[worker.local_source]
packages = ["./<your-toolkit-directory>"] # Replace with the path to your toolkit directoryFor more information on the worker.toml file, see the Arcade Deploy documentation.
Deploy your worker
Run the deploy command in the directory containing your worker.toml file:
arcade deployYou should see output like the following:
Deploying 'my-worker...' main.py:589
⠏ Deploying 1 workers
┏━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Added ┃ Removed ┃ Updated ┃ No Changes ┃
┡━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━┩
│ custom-toolkit │ │ │ │
└─────────────────┴─────────┴─────────┴────────────┘
✅ Worker 'my-worker' deployed successfully.List your workers
Run the following command to list your workers:
arcade worker listYou should see output like the following:
Workers
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ ID ┃ Cloud Deployed ┃ Engine Registered ┃ Enabled ┃ Host ┃ Toolkits ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ my-worker │ True │ True │ True │ https://4bdfrgfdgftlu0ahyko56gdsr.server.arcade.dev │ CustomToolkit │
└───────────┴────────────────┴───────────────────┴─────────┴─────────────────────────────────────────────────────┴───────────────┘Your worker and toolkits are now deployed and registered with the engine and ready to use!
You can go to the dashboard to see your worker and its details.