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.

Provider 🏢	Model Name 🤖	Open Source 🔓	Model String ⌨️	Backend ⚙️	Required API Key
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
Google	Gemini 1.5 Flash	❌	gemini-1.5-flash	google	GEMINI_API_KEY
Google	Gemini 1.5 Flash-8B	❌	gemini-1.5-flash-8b	google	GEMINI_API_KEY
Google	Gemini 1.5 Pro	❌	gemini-1.5-pro	google	GEMINI_API_KEY
Google	Gemini 1.0 Pro	❌	gemini-1.0-pro	google	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	All Models	✅	model-name	ollama	-
vLLM	All Models	✅	model-name	vllm	-
HuggingFace	All Models	✅	model-name	huggingface	HF_HOME

Configuration

Set up configuration file directly (Recommended)

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.

[!TIP] It is important to mention that, we strongly recommend using the aios/config/config.yaml file to set up your API keys. This method is straightforward and helps avoid potential sychronization issues with environment variables.

A simple example to set up your API keys in aios/config/config.yaml is shown below:

api_keys:
  openai: "your-openai-key"    
  gemini: "your-gemini-key"    
  groq: "your-groq-key"      
  anthropic: "your-anthropic-key" 
  huggingface:
    auth_token: "token to authorize specific models for use"  
    home: "path to store downloaded model weights"

To obtain these API keys:

1. Deepseek API: https://api-docs.deepseek.com/

2. OpenAI API: https://platform.openai.com/api-keys

3. Google Gemini API: https://makersuite.google.com/app/apikey

4. Groq API: https://console.groq.com/keys

5. HuggingFace Token: https://huggingface.co/settings/tokens

6. Anthropic API: https://console.anthropic.com/keys

Configure LLM Models

You can configure which LLM models to use in the same aios/config/config.yaml file. Here's an example configuration:

llms:
  models:
    # Ollama Models
    - name: "qwen2.5:7b"
      backend: "ollama"
      hostname: "http://localhost:11434"  # Make sure to run ollama server

    # vLLM Models
    - name: "meta-llama/Llama-3.1-8B-Instruct"
      backend: "vllm"
      hostname: "http://localhost:8091/v1"  # Make sure to run vllm server

Using Ollama Models:

1. First, download ollama from https://ollama.com/

2. Start the ollama server in a separate terminal:

ollama serve

1. Pull your desired models from https://ollama.com/library:

ollama pull qwen2.5:7b  # example model

Ollama supports both CPU-only and GPU environments. For more details about ollama usage, visit ollama documentation

Using vLLM Models:

1. Install vLLM following their installation guide

2. Start the vLLM server in a separate terminal:

vllm serve meta-llama/Llama-3.1-8B-Instruct --port 8091

vLLM currently only supports Linux and GPU-enabled environments. If you don't have a compatible environment, please choose other backend options. To enable the tool calling feature of vllm, refer to https://docs.vllm.ai/en/latest/features/tool_calling.html

Using HuggingFace Models: You can configure HuggingFace models with specific GPU memory allocation:

- name: "meta-llama/Llama-3.1-8B-Instruct"
  backend: "huggingface"
  max_gpu_memory: {0: "24GB", 1: "24GB"}  # GPU memory allocation
  eval_device: "cuda:0"  # Device for model evaluation

Launch AIOS

After you setup the required keys, you can run the following command to launch the AIOS kernel.

bash runtime/launch_kernel.sh

And then you can start a client to interact with the AIOS kernel using Terminal or WebUI.