LM Studio Embedding Configuration
LM Studio can serve embedding models as well as chat models, so you can index your documents entirely on your own hardware.
Before you start
Download an embedding model in LM Studio — nomic-ai/nomic-embed-text-v1.5-GGUF is a good general-purpose choice — then load it and start the server. See LM Studio for text generation for the full setup.
Required Fields
Endpoint URL *
The address of the LM Studio server, including /v1.
Default: http://host.docker.internal:1234/v1
Use host.docker.internal rather than localhost when LM Studio runs on the Docker host.
Model Name *
The embedding model’s identifier, for example nomic-ai/nomic-embed-text-v1.5-GGUF.
Optional Fields
API Key
LM Studio does not check API keys. Leave this blank unless a proxy in front of it requires one.
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.
Dimensions
The number of dimensions in the vectors this model produces. PipesHub uses it to size the vector collection.
Changing the embedding model or its dimensions after documents are indexed means existing vectors no longer match new ones. Re-index your content after switching.
Is Multimodal
Turn this on if the model can embed images as well as text. It is off by default.
