Documentation Index
Fetch the complete documentation index at: https://docs.runalph.ai/llms.txt
Use this file to discover all available pages before exploring further.
What are Projects?
Projects are JupyterLab servers running on cloud compute. They provide kernels for notebooks, shell access, file storage, and web app hosting — all in an isolated environment. Access:https://runalph.ai/{org-slug}/{project-slug}
Automations
Schedule recurring tasks that run in your project — notebook cells or AI agents on a cron. See guides for notebook automations and agent automations.AI Editor
Every project includes an AI-powered IDE. The agent can create and execute notebook cells, read outputs, create and edit files, debug errors, and iterate — all from a chat interface. See AI and Agents for details. Access:https://runalph.ai/{org}/{project}/ide
Creating a Project
- Go to Projects in your organization
- Click New Project
- Enter a name and slug
- Select a compute type
- Click Create
Compute Types
| Type | CPU | RAM | Use Case |
|---|---|---|---|
| Micro | 0.5 | 1 GB | Light tasks, testing |
| Small | 2 | 4 GB | Data analysis |
| Medium | 4 | 8 GB | ML training |
| Large | 8 | 16 GB | Large datasets |
| XLarge | 16 | 32 GB | Heavy workloads |
Terminals
Full shell access in your browser. Install packages, run scripts, manage files. Claude Code comes pre-installed in every project — open a terminal and runclaude to start.
Create multiple terminal sessions and switch between them. Sessions persist until the project stops.
Kernels
Monitor running kernels at Kernels in your project:- See kernel status (idle, busy, starting)
- View attached notebook sessions
- Shut down individual kernels or all at once
Web App Hosting
Run any web framework and get a public URL automatically.- Start your app on port 5000, bound to
0.0.0.0 - Your app is live at
https://{org}-{project}.runalph.dev
Local Projects
Use your own hardware instead of cloud compute:--app-port 5000 to expose a web app through the tunnel. See the Bring Your Own GPU guide.