Integrating with GPUStack for Local Model Deployment

GPUStack is an open-source GPU cluster manager for running large language models(LLMs).

Dify allows integration with GPUStack for local deployment of large language model inference, embedding and reranking capabilities.

Deploying GPUStack

You can refer to the official Documentation for deployment, or quickly integrate following the steps below:

Linux or MacOS

GPUStack provides a script to install it as a service on systemd or launchd based systems. To install GPUStack using this method, just run:

curl -sfL https://get.gpustack.ai | sh -s -

Windows

Run PowerShell as administrator (avoid using PowerShell ISE), then run the following command to install GPUStack:

Invoke-Expression (Invoke-WebRequest -Uri "https://get.gpustack.ai" -UseBasicParsing).Content

Then you can follow the printed instructions to access the GPUStack UI.

Deploying LLM

Using a LLM hosted on GPUStack as an example:

1. In GPUStack UI, navigate to the "Models" page and click on "Deploy Model", choose Hugging Face from the dropdown.

2. Use the search bar in the top left to search for the model name Qwen/Qwen2.5-0.5B-Instruct-GGUF.

3. Click Save to deploy the model.

gpustack-deploy-llm

Create an API Key

1. Navigate to the "API Keys" page and click on "New API Key".

2. Fill in the name, then click Save.

3. Copy the API key and save it for later use.

Integrating GPUStack into Dify

1. Go to Settings > Model Providers > GPUStack and fill in:

   • Model Type: LLM

   • Model Name: qwen2.5-0.5b-instruct

   • Server URL: http://your-gpustack-server-ip

   • API Key: Input the API key you copied from previous steps

   Click "Save" to use the model in the application.

add-gpustack-llm

For more information about GPUStack, please refer to Github Repo.