LLM Providers

LM Studio Setup

Run models through the LM Studio desktop app and connect its local API server to MLJAR Studio for notebook assistance.

Before you start

Activate a lifetime MLJAR Studio license to configure your own AI provider. Open AI Provider Settings in MLJAR Studio to choose a provider.

1. Start the model server

Install LM Studio and download a chat or instruction model that fits your computer.
Load the model, open the Developer tab, and turn on Start server. Keep the server running while using MLJAR Studio.

See the official LM Studio server guide for server setup.

2. Connect MLJAR Studio

In AI Provider Settings, select LM Studio from Provider.
Set Base URL to http://127.0.0.1:1234/v1 for the default local setup. Use the actual host and port if you changed them. Keep the /v1 suffix.
Leave LM Studio API key (optional) empty unless you enabled server authentication. If enabled, enter the token from LM Studio.
Wait for models to load automatically, or click Refresh models. Choose your chat model from Model.
Click Test connection, then Save provider once the test succeeds. Changing settings requires another test.
Confirm the success message and the active provider in the sidebar.

Test a notebook request

After saving, send a short request in your notebook. Test connection checks access to the model list and the selected model; a successful test does not guarantee that every model supports the chat or tool features your workflow needs.

Where requests run

The default loopback address connects to the server on the machine running the MLJAR notebook backend. A remote server URL sends prompts and notebook context to that server. Use HTTPS for remote connections. For local inference, keep both the endpoint and model execution on your machine.

Troubleshooting