Description:

azarrot 0.2.0

Azarrot
(Early WIP) An OpenAI compatible LLM inference server, focusing on OpenVINO™ and IPEX-LLM usage.
The name azarrot is combined from azalea and parrot.
Motivation
NVIDIA sucks on Linux, and AMD does not like people running ROCm on their consumer cards (sadly my RX 5500 XT is not supported).
Meanwhile, Intel consumer cards are cheap, and have good fundamental software support, Intel is also actively maintaining and upstreaming many AI libraries.
So I bought an A770, but all the existing inference servers are lacking on Intel cards: some lacks quantization, some only support a few models, some does not run at all... and they are all lacking on OpenAI API features.
Finally, I decided to create my own inference server, focusing on Intel cards, and targeting full OpenAI API features.
Let's see how far could I go.
Changelog
See CHANGELOG for more details.
Supported OpenAI features

✅：Fully supported
⭕：Partially supported
❓：Implemented, but not tested, may work or not
🚧：Working in progress
❌：Not supported yet




Feature
Subfeature
IPEX-LLM
OpenVINO
Remarks




Chat
Basic chat completion
⭕
⭕
Text generation works, parameters (like frequency_penalty, temperature) not implemented yet


Chat
Streaming response
✅
✅



Chat
Image input
✅
❌
InternVL2 supported


Chat
Tool calling
✅
❓
Qwen2 supported


Embeddings
Create embeddings
❌
⭕
encoding_format not implemented yet


Models
List models
✅
✅




Tested models



Model
Repository
Device
Backend
Remarks




CodeQwen1.5-7B
https://huggingface.co/Qwen/CodeQwen1.5-7B
Intel GPU
IPEX-LLM, OpenVINO



InternVL2-8B
https://huggingface.co/OpenGVLab/InternVL2-8B
Intel GPU
IPEX-LLM
Image input supported


bge-m3
https://huggingface.co/BAAI/bge-m3
Intel GPU, CPU
OpenVINO
Accuracy may decrease if quantized to int8


Qwen2-7B-Instruct
https://huggingface.co/Qwen/Qwen2-7B-Instruct
Intel GPU
IPEX-LLM
Tool calling supported



Other untested models may work or not.
Prerequisites
Hardware
Azarrot supports CPUs and Intel GPUs. NVIDIA and AMD GPUs may work if you manually install corresponding torch libraries.
Tested GPUs:

Intel A770 16GB
Intel Xe 96EU (i7 12700H)

Software
Due to the xpu branch of intel-extension-for-pytorch still has no python 3.12 build, we have to use Python 3.11 or below.
You also have to install oneAPI Toolkit (at least 2024.0) and drivers.
Azarrot is tested on Ubuntu 22.04 and python 3.10.
Usage

WARNING: This project is still in early stages. Bugs are expected.

First, install azarrot from PyPI:
pip install azarrot

Then, create a server.yml in the directory you want to run it:
mkdir azarrot

# Copy from examples/server.yml
cp <SOURCE_ROOT>/examples/server.yml azarrot/

<SOURCE_ROOT> means the repository path you cloned.
In server.yml you can configure things like listening port, model path, etc.
Next we create the models directory:
cd azarrot
mkdir models

And copy an example model file into the models directory:
cp <SOURCE_ROOT>/examples/CodeQwen1.5-7B-ipex-llm.model.yml models/

Azarrot will load all .model.yml files in this directory.
You need to manually download the model from huggingface, or convert them if you are using the OpenVINO backend:
huggingface-cli download --local-dir models/CodeQwen1.5-7B Qwen/CodeQwen1.5-7B

Azarrot will convert it to int4 when loading the model.
Now we can start the server:
source /opt/intel/oneapi/setvars.sh
python -m azarrot

And access http://localhost:8080/v1/models too see all loaded models.
More details are in the documents: Documents

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

Share

• Share on Facebook
• Share on Twitter