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LM Studio Configuration

LM Studio is a desktop application that downloads open-source models and serves them from your own machine through an OpenAI-compatible API. Nothing leaves your computer, which makes it a good fit for private or offline work.

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Before you start

  1. Install LM Studio on the machine that will run the model.
  2. Download a model from the Discover tab.
  3. Open the Developer tab (called Local Server in older versions), load the model, and start the server.
  4. Note the port. LM Studio uses 1234 by default, so the server address is usually http://localhost:1234/v1.
The machine running LM Studio needs enough memory to hold the model. As a rough guide, a quantised 8-billion-parameter model needs about 8 GB of free RAM, and larger models need proportionally more.

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Required Fields

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Endpoint URL *

The address of the LM Studio server, including the /v1 path. Default: http://host.docker.internal:1234/v1 Which value to use: PipesHub runs inside a container, so http://localhost:1234/v1 points at the PipesHub container rather than your desktop. Use host.docker.internal instead. If LM Studio runs on a different machine, enable Serve on Local Network in its server settings, otherwise it only accepts connections from its own host.

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Model Name *

The model identifier shown in LM Studio’s server panel, for example lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF. You can list the exact identifiers the server is serving with:

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Optional Fields

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API Key

LM Studio does not check API keys. Leave this blank unless you have put the server behind a proxy that requires one, in which case enter the key that proxy expects.

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Model Friendly Name

A label shown in the PipesHub interface so you can tell several configurations apart. If you leave it blank, the model name is used.

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Context Length

The size of the model’s context window, in tokens. PipesHub uses this number to decide how much retrieved content it can safely include in a prompt. Set it to the value published for your model. If you leave it blank, PipesHub uses a conservative default.

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Is Multimodal

Turn this on if the model accepts images as well as text. It is on by default.

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Is Reasoning

Turn this on if the model performs extended reasoning before answering. It is on by default.

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Troubleshooting

“Connection refused”. The LM Studio server is not running, or you used localhost where host.docker.internal is needed. Requests time out on the first message. LM Studio loads the model into memory on the first request, which can take a minute for a large model. Load the model in the Developer tab before using it from PipesHub. “Model not found”. The identifier does not match. Copy it from the curl output above rather than typing it by hand.