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‎LICENSE

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8. Limitation of Liability. In no event and under no legal theory,
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9. Accepting Warranty or Additional Liability. While redistributing
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software
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limitations under the License.

‎README.md

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# GPUStack
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Turn your set of GPUs into a full-fledged LLM stack with a snap.
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GPUStack aims to get you started with running LLMs and performing inference in a simple yet scalable manner.
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## Development
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- Supports a wide variety of hardware.
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- Scales with your GPU inventory.
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- A lightweight Python package with minimal dependencies and operational overhead.
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- OpenAI-compatible APIs.
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- User and API key management.
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- GPU metrics monitoring.
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- Token usage and rate metrics.
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### Prerequisites
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## Installation
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Install `[email protected]` and `poetry`.
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### Linux or MacOS
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### Set Up Environment
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GPUStack provides a script to install it as a service on systemd or launchd based systems. To install GPUStack using this method, just run:
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```
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make install
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```bash
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curl -sfL https://get.gpustack.ai | sh -
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```
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### Run
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You can add additional workers to form a GPUStack cluster by running the following command on worker nodes:
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```
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poetry run gpustack
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```bash
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curl -sfL https://get.gpustack.ai | sh - --server-url http://myserver --token mytoken
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```
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### Build
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The token here is a secret used for adding workers. In the default setup, you can run the following to get the token:
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```
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make build
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```bash
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cat ~/.local/share/gpustack/token
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```
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And check artifacts in `dist`.
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### Windows
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### Test
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`// TODO`
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```
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make test
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### Manual Install
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For manual installation or detail configurations, refer to the [installation](.docs/user-guide/installation.md) docs.
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## Gettting Started
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1. Run and chat with the llama3 model:
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```bash
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gpustack chat llama3 "tell me a joke."
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```
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### Update Dependencies
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2. Open `http://myserver` in the browser to access the GPUStack UI. Log in to GPUStack with username `admin` and the default password. You can run the following command to get the password for the default setup:
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```bash
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cat ~/.local/share/gpustack/initial_admin_password
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```
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poetry add <something>
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3. Click `Playground` in the navigation menus. Now you can chat with the LLM in the UI playground.
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// TODO add screenshot
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4. Click `API Keys` in the navigation menus, then click the `New API Key` button.
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5. Fill in the `Name` and click the `Save` button.
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6. Copy the generated API key and save it somewhere safe. Please note that you can only see it once on creation.
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7. Now you can use the API key to access the OpenAI-compatible API. For example, use curl as the following:
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```bash
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export GPUSTACK_API_KEY=myapikey
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curl http://myserver/v1-openai/chat/completions \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer $GPUSTACK_API_KEY" \
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-d '{
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"model": "llama3",
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"messages": [
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{
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"role": "system",
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"content": "You are a helpful assistant."
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},
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{
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"role": "user",
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"content": "Hello!"
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}
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],
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"stream": true
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}'
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```
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Or
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## Supported Platforms
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- [x] MacOS
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- [x] Linux
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- [x] Windows
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## Supported Accelerators
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We haven't tested everything out in the wild, but we plan to support all of the following in the near future.
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- [x] Apple Metal
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- [x] NVIDIA CUDA
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- [ ] AMD ROCm
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- [ ] Intel oneAPI
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## Supported Models
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GPUStack uses [llama.cpp](https://github.com/ggerganov/llama.cpp) as the backend and supports large language models in [GGUF format](https://github.com/ggerganov/ggml/blob/master/docs/gguf.md). Models from the following sources are supported:
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1. [Hugging Face](https://huggingface.co/)
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2. [Ollama Library](https://ollama.com/library)
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Here are some example models:
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- [x] [LLaMA](https://huggingface.co/meta-llama)
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- [x] [Mistral 7B](https://huggingface.co/mistralai/Mistral-7B-v0.1)
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- [x] [Mixtral MoE](https://huggingface.co/models?search=mistral-ai/Mixtral)
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- [x] [DBRX](https://huggingface.co/databricks/dbrx-instruct)
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- [x] [Falcon](https://huggingface.co/models?search=tiiuae/falcon)
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- [x] [Baichuan](https://huggingface.co/models?search=baichuan-inc/Baichuan)
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- [x] [Aquila](https://huggingface.co/models?search=BAAI/Aquila)
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- [x] [Yi](https://huggingface.co/models?search=01-ai/Yi)
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- [x] [StableLM](https://huggingface.co/stabilityai)
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- [x] [Deepseek](https://huggingface.co/models?search=deepseek-ai/deepseek)
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- [x] [Qwen](https://huggingface.co/models?search=Qwen/Qwen)
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- [x] [Phi](https://huggingface.co/models?search=microsoft/phi)
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- [x] [Gemma](https://ai.google.dev/gemma)
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- [x] [Mamba](https://github.com/state-spaces/mamba)
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- [x] [Grok-1](https://huggingface.co/keyfan/grok-1-hf)
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## OpenAI-Compatible APIs
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GPUStack serves the following OpenAI compatible APIs under the `/v1-openai` path:
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1. List models
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2. Chat completions
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For example, you can use the official [OpenAI Python API library](https://github.com/openai/openai-python) to consume the APIs:
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```python
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from openai import OpenAI
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client = OpenAI(base_url="http://myserver/v1-openai",api_key="myapikey")
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completion = client.chat.completions.create(
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model="llama3",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Hello!"}
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]
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)
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print(completion.choices[0].message)
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```
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poetry add --dev <something>
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```
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For dev/testing dependencies.
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GPUStack users can generate their own API keys in the UI.
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## Build
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1. Install `[email protected]`.
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2. Run `make build`.
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You can find the built wheel package in `dist` directory.
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## Contributing
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Please read the [Contributing Guide](./docs/contributing.md) if you're interested in contributing to GPUStack.
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## License
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Copyright (c) 2024 The GPUStack authors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at [LICENSE](./LICENSE) file for details.
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.

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