> ## 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.

# Projects

> Cloud compute environments with JupyterLab, terminals, and web app hosting

## 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](/guides/automate-notebooks) and [agent automations](/guides/automate-agents).

## 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](/concepts/ai) for details.

**Access:** `https://runalph.ai/{org}/{project}/ide`

## Creating a Project

1. Go to **Projects** in your organization
2. Click **New Project**
3. Enter a name and slug
4. Select a compute type
5. 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      |

GPU instances are also available. Change compute type anytime in **Settings > Compute** (restarts the server).

## 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 run `claude` 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.

1. Start your app on port 5000, bound to `0.0.0.0`
2. Your app is live at `https://{org}-{project}.runalph.dev`

Works with Streamlit, Gradio, Flask, FastAPI, and anything else that serves HTTP. Add a custom domain in **Settings > Domains**.

## Local Projects

Use your own hardware instead of cloud compute:

```bash theme={null}
alphai jupyter lab --org my-org --project my-project
```

This connects a local JupyterLab to Alph. No compute charges — use your laptop, workstation, or cloud VM. Add `--app-port 5000` to expose a web app through the tunnel. See the [Bring Your Own GPU](/guides/bring-your-own-gpu) guide.