Providers
A SharpMind Compute host is the combined server image: the Studio web UI on 5117 and the OpenAI-style API on 8080, sharing /data/SharpMind. The provider only supplies the machine, Docker, ports and disk.
Compare hosts
| Host | Setup | GPU | Billing | Best for |
|---|---|---|---|---|
| Local Docker | Studio starts the container | Optional local NVIDIA GPU | Free (your power) | Privacy, small models, CPU pretraining |
| Runpod | Studio deploys the pod via API | Yes | Per minute; balance required | Short GPU jobs without a server to keep |
| Vultr | Create instance; Studio sets up over SSH | Yes, A16 class | Hourly; also while stopped | A host you keep for a day of experiments |
| Custom / bare Linux | Your Docker + optional SSH | Whatever the box has | Your provider | An existing server, workstation or lab machine |
Referral links support the project and do not change the price.
The shared contract
Every host follows the same rules, which is why the workflow does not change:
| Item | Value |
|---|---|
| Studio UI | 5117 (and 5118 for the LAN listener) |
| Compute API | 8080 |
| Data root | /data/SharpMind mounted from the host |
| Models | /data/SharpMind/Models |
| Plugins | /app/plugins (the GPU image carries SharpMind.GPU) |
| Auth | SHARPMIND_TOKEN on every API call; /health is open |
| Default model | One active model per process; activate another from Studio or the API |
Which one?
- Only trying the app: run Studio locally and use a packaged model. No host needed.
- Want a GPU for a fine-tune this week: Vultr. Keep the instance for the session, destroy it when done.
- Want a GPU for a few minutes and already have credit: Runpod, deployed from the card.
- Have a Linux box with Docker: custom host; point the card at it and press Test.
- Need full privacy: Local Docker or the local Studio process.
What SSH setup does
For Vultr and custom Linux hosts, Studio can log in over SSH and prepare the machine. It is optional: a host that already runs the image only needs a Base URL, token and Test.
The helper performs these steps, one at a time, with streamed output:
- Probe the host: OS, architecture, Docker version, NVIDIA GPU and free disk.
- Install Docker from get.docker.com when it is missing.
- Install the NVIDIA container toolkit when the GPU host checkbox is on and it is missing.
- Pull the server image. The image name must include a registry prefix, for example integral2u/sharpmind-server:gpu.
- Replace the container, mount /data/SharpMind, publish 5117 and 8080, and pass the saved token.
- Inspect and test the container, then call /health from Studio.
It deliberately does not install the NVIDIA driver: that needs a reboot and can break the session. If nvidia-smi is missing, setup stops and says so. Use a provider GPU image that includes the driver, or install it once and run setup again.
Tokens and security
- The host token is generated in Studio and stored encrypted with the local key box.
- SSH passwords and key passphrases use the same encryption; private keys stay on this PC.
- The SSH host key is trusted on first use. If that matters for your environment, pin it manually.
- Rotate the token before opening a host to the internet; a literal value such as PASTE_YOUR_TOKEN is not a secret.
- Restrict the provider firewall to your own IP where possible. SSH 22, API 8080, Studio 5117.