aphrodite-engine 0.3.1

The inference engine for PygmalionAI models

Breathing Life into Language

Aphrodite is the official backend engine for PygmalionAI. It is designed to serve as the inference endpoint for the PygmalionAI website, and to allow serving the Pygmalion models to a large number of users with blazing fast speeds (thanks to FasterTransformer and vLLM).

Aphrodite builds upon and integrates the exceptional work from various projects, including:

• vLLM (CacheFlow)
• FasterTransformer
• xFormers
• AWQ
• Megatron-LM
• FastChat
• SkyPilot
• OpenAI Python Library

Features

• Continuous Batching
• Efficient K/V management with PagedAttention
• Optimized CUDA kernels for improved inference
• Quantization support via AWQ
• Distributed inference
• Multiple decoding algorithms (e.g. parallel sampling, beam search)

Quickstart

$ pip install aphrodite-engine
$ python -m aphrodite.endpoints.api_server_ooba --model PygmalionAI/pygmalion-2-13b

Requirements

• Operating System: Linux (or WSL for Windows)
• Python: at least 3.8
• CUDA 11.8 (recommended, supports 11.0-11.8)

Supported GPUs

Any NVIDIA GPU with a compute capability of 6.0 or higher. Refer to this page for a full list of CUDA GPUs:

https://developer.nvidia.com/cuda-gpus.

Or, you can manually find out your GPU's Compute Capability by opening a Python interpreter and running:

>>> import torch    # if you don't have `torch` installed, run `pip install torch` first
>>> print(torch.cuda.get_device_capability())

This should print something like this: (7, 5), which would indicate a CC of 7.5

If you do not meet the minimum CC, you will not be able to run Aphrodite.

Setting up the environment

If you run into any problems, please refer to the common Common Issues section, or open an Issue if you can't find the answer there.

Aphrodite will require a slightly specialized environment to run, as the latest CUDA and GCC versions are not supported. You can use Conda to easily configure your environment.

Install miniconda3

$ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
$ bash ./Miniconda3*

You can follow the on-screen instructions, though you may want to set the installation directory to somewhere with a large empty storage space.

You can either source your shell script (. ~/.bashrc or . ~/.zshrc) or restart your terminal instance to begin using conda.

Configuring the env for Aphrodite-engine

$ conda config --set auto_activate_base false
$ conda create -n aphrodite python=3.10
$ conda activate aphrodite
$ conda install -c "nvidia/label/cuda-11.8.0" cuda

Installation

$ pip install aphrodite-engine

Install from source

Click to Expand

git clone https://github.com/PygmalionAI/aphrodite-engine && cd aphrodite-engine
pip install -e .  # this will take a while

Usage

You can spawn a text-generation-webui-compatible API server to use with SillyTavern:

$ python -m aphrodite.endpoints.api_server_ooba --model PygmalionAI/pygmalion-2-13b --max-model-len 4096 --max-num-batched-tokens 4096

This will create a server which runs on port 8000 of your machine. You can navigate to SillyTavern's API menu, select TextGen WebUI, and set the API Type to Aphrodite. The default API key is EMPTY, but you can change it as necessary. Use http://localhost:8000/api as the API URL.

To run a quantized model, use the --quantization awq flag. Make sure your model is in AWQ format, and not GPTQ/GGUF. Run with only the --help flag for a full list of arguments.

To manually query the API, run:

$ curl -X POST "http://localhost:8000/api/v1/generate" \
-H "Content-Type: application/json" \
-H "x-api-key: EMPTY" \
-d '{
  "prompt": "<|system|>Enter chat mode.<|user|>Hello!",
  "stream": false,
  "temperature": 0.8,
  "top_p": 0.90
}'

For the full list of Sampling parameters, please refer to SamplingParams:

https://github.com/PygmalionAI/aphrodite-engine/blob/99657d444bc2bab5e4293e9ee96e154dd7d3de44/aphrodite/common/sampling_params.py#L22-L62

OpenAI-compatible server

An OpenAI-compatible server is also provided. You can launch the server with:

$ python -m aphrodite.endpoints.openai.api_server --model PygmalionAI/pygmalion-2-13b

You can query the server the same as any other OpenAI Completion/Chat Completion endpoint, though without an API key.

Common Issues

• The detected CUDA version (12.1) mismatches the version that was used to compile PyTorch (11.7). Please make sure to use the same CUDA versions.

This is normally due to your environment referring to the global installation of CUDA and not the one in your current env. Run which nvcc and note down the output. For example, if your output is /home/anon/miniconda3/envs/aphrodite/bin/nvcc, run this command:

$ export CUDA_HOME=/home/anon/miniconda3/envs/aphrodite

Then run the installation command again.

• Aborted due to the lack of CPU swap space. Please increase the swap space to avoid this error.

You've run out of swap space! Please pass the --swap-space followed by the amount of swap (in GBs) to allocate. Make sure you leave enough RAM for the model loading process.

Notes

1. By design, Aphrodite takes up 90% of your GPU's VRAM. If you're not serving an LLM at scale, you may want to limit the amount of memory it takes up. You can do this in the API example by launching the server with the --gpu-memory-utilization 0.6 (0.6 means 60%).

2. You can view the full list of commands by running python -m aphrodite.endpoints.api_server_ooba --help.

Contributing

We accept PRs! There will likely be a few typos or other errors we've failed to catch, so please let us know either via an issue or by making a Pull Request.