Run your own app in the browser

Any web app you start on your GPU machine on port 7860 opens with Open my app on your running instance: Streamlit, Gradio, FastAPI, a dev server. Only you can open it, the same way as JupyterLab and the other built-in apps, and access ends when the machine stops.

1. Start your app on 127.0.0.1, port 7860

Use a terminal on the machine (SSH, or a JupyterLab terminal). Listen on 127.0.0.1 only: the machine has no public web port, and the browser reaches your app through ComputeNexa's protected connection, never directly.

Streamlit

streamlit run app.py --server.port 7860 --server.address 127.0.0.1 --server.headless true

Gradio

demo.launch(server_name="127.0.0.1", server_port=7860)

FastAPI (uvicorn)

uvicorn main:app --host 127.0.0.1 --port 7860

Next.js dev server

npx next dev -H 127.0.0.1 -p 7860

Next.js blocks dev requests from other addresses: add your app's domain to next.config, e.g. allowedDevOrigins: ["*.computenexa-apps.com"].

To keep it running after you close the terminal, start it inside tmux or with nohup … &.

2. Open it

On Instances, click Open my app. If nothing is listening on port 7860 yet, you'll see a page saying so; it checks again every 10 seconds, so it shows your app as soon as it starts.

Good to know

Websockets and streaming work (Streamlit, Gradio). No need to turn off Streamlit's CORS or XSRF protection: the browser talks to your app at its own address.
Your app is served at the root of its address (/); no base path is needed.
One app per machine on port 7860. Other ports aren't reachable from the browser.
Files your app writes are kept only if they're in ~/work on a machine with a project.

More guides

Getting started: rent your first GPU: Sign up, pick a GPU and an app, launch it, connect, and stop it when you're done.
Set up your organization and invite your team: One shared balance for your company: roles, invitations, GPU limits and who can see what.
Use the ComputeNexa API: Launch, check and stop GPUs from your own scripts, CI jobs or platform with an API key.
Python SDK: pip install computenexa: launch, use and stop GPUs from Python, with waiting and clear errors built in.
Command-line tool (cnx): cnx launch, ls, ssh, stop: your GPUs from the terminal, scripts and CI.
API reference: Every API operation by name (listProjects, launchInstance…), with its request and reply.
What's in each image: Exactly what's installed in each app's images: Ubuntu, CUDA, Python, packages and versions.

Questions? Email support@computenexa.com.