Quickstart
Be sure to complete the installation instructions before continuing with this guide.
Before starting AIOS, you need to make sure you have installed the LLM backends that you would like to run. Here are the LLM providers for supported backends for AIOS.
Anthropic
Claude 3.5 Sonnet
❌
claude-3-5-sonnet-20241022
anthropic
ANTHROPIC_API_KEY
Anthropic
Claude 3.5 Haiku
❌
claude-3-5-haiku-20241022
anthropic
ANTHROPIC_API_KEY
Anthropic
Claude 3 Opus
❌
claude-3-opus-20240229
anthropic
ANTHROPIC_API_KEY
Anthropic
Claude 3 Sonnet
❌
claude-3-sonnet-20240229
anthropic
ANTHROPIC_API_KEY
Anthropic
Claude 3 Haiku
❌
claude-3-haiku-20240307
anthropic
ANTHROPIC_API_KEY
Deepseek
Deepseek-reasoner (R1)
❌
deepseek-reasoner
deepseek
DEEPSEEK_API_KEY
Deepseek
Deepseek-chat (V3)
❌
deepseek-chat
deepseek
DEEPSEEK_API_KEY
OpenAI
GPT-4
❌
gpt-4
openai
OPENAI_API_KEY
OpenAI
GPT-4 Turbo
❌
gpt-4-turbo
openai
OPENAI_API_KEY
OpenAI
GPT-4o
❌
gpt-4o
openai
OPENAI_API_KEY
OpenAI
GPT-4o mini
❌
gpt-4o-mini
openai
OPENAI_API_KEY
OpenAI
GPT-3.5 Turbo
❌
gpt-3.5-turbo
openai
OPENAI_API_KEY
Gemini 1.5 Flash
❌
gemini-1.5-flash
GEMINI_API_KEY
Gemini 1.5 Flash-8B
❌
gemini-1.5-flash-8b
GEMINI_API_KEY
Gemini 1.5 Pro
❌
gemini-1.5-pro
GEMINI_API_KEY
Gemini 1.0 Pro
❌
gemini-1.0-pro
GEMINI_API_KEY
Groq
Llama 3.2 90B Vision
✅
llama-3.2-90b-vision-preview
groq
GROQ_API_KEY
Groq
Llama 3.2 11B Vision
✅
llama-3.2-11b-vision-preview
groq
GROQ_API_KEY
Groq
Llama 3.1 70B
✅
llama-3.1-70b-versatile
groq
GROQ_API_KEY
Groq
Llama Guard 3 8B
✅
llama-guard-3-8b
groq
GROQ_API_KEY
Groq
Llama 3 70B
✅
llama3-70b-8192
groq
GROQ_API_KEY
Groq
Llama 3 8B
✅
llama3-8b-8192
groq
GROQ_API_KEY
Groq
Mixtral 8x7B
✅
mixtral-8x7b-32768
groq
GROQ_API_KEY
Groq
Gemma 7B
✅
gemma-7b-it
groq
GROQ_API_KEY
Groq
Gemma 2B
✅
gemma2-9b-it
groq
GROQ_API_KEY
Groq
Llama3 Groq 70B
✅
llama3-groq-70b-8192-tool-use-preview
groq
GROQ_API_KEY
Groq
Llama3 Groq 8B
✅
llama3-groq-8b-8192-tool-use-preview
groq
GROQ_API_KEY
ollama
✅
model-name
ollama
-
vLLM
✅
model-name
vllm
-
HuggingFace
✅
model-name
huggingface
HF_HOME
Configuration
After installling LLM backends, multiple API keys may be required to set up. Here we provide the easier way to set up API keys, you can set up the following keys as below in your environment variables.
Recommended Configuration Method
For simplicity and ease of use, we recommend using the config.yaml
file to set up your API keys. This method is straightforward and helps avoid potential issues with environment variables. Simply add your API keys to the config.yaml
file as shown below:
Set Up API Keys You need API keys for services like OpenAI, Anthropic, Groq and HuggingFace. The simplest way to configure them is to edit the
aios/config/config.yaml
.Basic Configuration Add your API keys to the
config.yaml
. For example:Detailed Setup Instructions For detailed instructions on setting up API keys and configuration files, see Environment Variables Configuration.
How to Obtain API Keys
To obtain these API keys:
OpenAI API: Visit https://platform.openai.com/api-keys
Deepseek API: Visit https://api-docs.deepseek.com/
Google Gemini API: Visit https://aistudio.google.com/app/apikey
Groq API: Visit https://console.groq.com/keys
HuggingFace Token: Visit https://huggingface.co/settings/tokens
Anthropic API: Visit https://console.anthropic.com/keys
Use with ollama
You need to download ollama from from https://ollama.com/.
Then you need to start the ollama server either from ollama app or using the following command in the terminal.
Ollama can support both CPU-only and GPU environments. Details of how to use Ollama can be found at GitHub: Ollama.
Use with Huggingface Models
Some of the huggingface models require authentification, if you want to use all of the models you need to set up your authentification token in https://huggingface.co/settings/tokens and set up it as an environment variable using the following command
By default, huggingface will download the models in the ~/.cache directory. If you want to designate the download directory, you can set up it using the following command
If you want to speed up the inference of huggingface models, you can use vLLM as the backend. The vLLM uses the exactly the same name huggingface native models.
It is important to note that vLLM currently only supports linux and GPU-enabled environment. So if you do not have the environment, you need to choose other model providers.
Considering that vLLM itself does not support passing designated GPU ids, you need to either setup the environment variable.
Launch AIOS
After you setup the required keys, you can run the following command to launch the AIOS kernel.
And then you can start a client to interact with the AIOS kernel using Terminal or WebUI.
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