Quickstart - Lyceum Documentation

1. Create an account

Sign up at the Lyceum Cloud Dashboard. New accounts receive starter credits you can use immediately. An organization is created automatically as your default, every run, VM, and credit lives there until you create or join more orgs.

2. Pick how you want to access the platform

CLI
VS Code Extension
REST API

Install the CLI

The CLI is published as the lyceum binary. Install with pip:

pip install lyceum-cli

Log in

lyceum auth login

You’ll be prompted for your email and password. The command exchanges those for a JWT token stored locally.

For long-running scripts and CI, generate an API key instead, see API Keys.

Run your first job

Run a one-liner on the platform:

lyceum python run "print('Hello from Lyceum')"

Run a Python file with a specific machine type:

lyceum python run script.py --machine cpu

Install the extension

Open VS Code
Open the Extensions view (Cmd/Ctrl+Shift+X)
Search for Lyceum Cloud
Install the official extension published by lyceumtechnology

Authenticate

Open any .py or .ipynb file
Click the cloud icon in the editor toolbar
The extension opens the dashboard for sign-in and redirects back to VS Code

Run code

With a Python file open, click the cloud icon (or run the Lyceum Cloud: Execute on Cloud command). The current file is submitted as a run and streamed back into VS Code.

Get an API key

Open the Lyceum Cloud Dashboard
Go to API Keys
Click New API Key, pick the organization to scope it to, give it a name, optionally set an expiration
Copy the key (starts with lk_), it’s only shown once

API keys are tied to one organization at creation time. Requests made with the key are billed and authorized against that org.

API keys grant full access to your account. Store them in a secret manager and never commit them to source control.

Make a request

The API base is https://api.lyceum.technology/api/v2/external. Authentication is Authorization: Bearer <key>.

curl https://api.lyceum.technology/api/v2/external/billing/credits \
  -H "Authorization: Bearer lk_your_api_key"

See the API Reference for the full endpoint list.

3. Where to next

Launch a run

Submit Python or Docker workloads to GPU machines.

Launch an instance

Provision a dedicated GPU VM with SSH access.

Deploy a model

Stand up a Hugging Face model behind an OpenAI-compatible endpoint.

Upload files

Use your per-user S3 bucket for inputs and outputs.

Need help? Email support@lyceum.technology.

​1. Create an account

​2. Pick how you want to access the platform

​Install the CLI

​Log in

​Run your first job

​Install the extension

​Authenticate

​Run code

​Get an API key

​Make a request

​3. Where to next

Launch a run

Launch an instance

Deploy a model

Upload files

1. Create an account

2. Pick how you want to access the platform

Install the CLI

Log in

Run your first job

Install the extension

Authenticate

Run code

Get an API key

Make a request

3. Where to next