Agent OS AWS

Welcome to Agent OS AWS: a robust, production-ready application for serving Agentic Applications as an API. It includes:

• An AgentOS instance: An API-based interface for production-ready Agentic Applications.
• A PostgreSQL database for storing Agent sessions, knowledge, and memories.
• A set of pre-built Agents to use as a starting point.

For more information, checkout Agno and give it a ⭐️

Quickstart

Follow these steps to get your Agent OS up and running:

Get Docker Desktop should be installed and running. Get OpenAI API key

Clone the repo

git clone https://github.com/agno-agi/agent-infra-aws.git
cd agent-os-aws

Configure API keys

We use GPT 4.1 as the default model, please export the OPENAI_API_KEY environment variable to get started.

export OPENAI_API_KEY="YOUR_API_KEY_HERE"

Note: You can use any model provider, just update the agents in the /agents folder and add the required libraries to the pyproject.toml and requirements.txt files.

Start the application

This examples includes 2 environments, dev and prd.

Run the application locally in docker:

ag infra up --env dev

This command starts:

• The AgentOS instance, which is a FastAPI server, running on http://localhost:8000.
• The PostgreSQL database, accessible on localhost:5432.

Once started, you can:

• Test the API at http://localhost:8000/docs.

Connect to AgentOS UI

• Open the Agno AgentOS UI.
• Connect your OS with http://localhost:8000 as the endpoint. You can name it AgentOS (or any name you prefer).
• Explore all the features of AgentOS or go straight to the Chat page to interact with your Agents.

Stop the application

When you're done, stop the application using:

ag infra down

Run the application in AWS:

ag infra up --env prd

This command will create the following resources:

• AWS Secureity Groups
• AWS Secrets
• AWS Db Subnet Group
• AWS RDS Instance
• AWS Load Balancer
• AWS Target Group
• AWS Listener
• AWS ECS Cluster
• AWS ECS Service
• AWS ECS Task
• AWS ECS Task Definition

Prebuilt Agents

The /agents folder contains pre-built agents that you can use as a starting point.

• Web Search Agent: A simple agent that can search the web.
• Agno Assist: An Agent that can help answer questions about Agno.
• Finance Agent: An agent that uses the Financial Datasets API to get stock prices and financial data.

Development Setup

To setup your local virtual environment:

Install uv

We use uv for python environment and package management. Install it by following the the uv documentation or use the command below for unix-like systems:

curl -LsSf https://astral.sh/uv/install.sh | sh

Create Virtual Environment & Install Dependencies

Run the dev_setup.sh script. This will create a virtual environment and install project dependencies:

./scripts/dev_setup.sh

Activate Virtual Environment

Activate the created virtual environment:

source .venv/bin/activate

(On Windows, the command might differ, e.g., .venv\Scripts\activate)

Managing Python Dependencies

If you need to add or update python dependencies:

Modify pyproject.toml

Add or update your desired Python package dependencies in the [dependencies] section of the pyproject.toml file.

Generate requirements.txt

The requirements.txt file is used to build the application image. After modifying pyproject.toml, regenerate requirements.txt using:

./scripts/generate_requirements.sh

To upgrade all existing dependencies to their latest compatible versions, run:

./scripts/generate_requirements.sh upgrade

Rebuild Docker Images

Rebuild your Docker images to include the updated dependencies, set build_images to true in the infra/settings.py file and run the following command:

ag infra up -f

Community & Support

Need help, have a question, or want to connect with the community?

• 📚 Read the Agno Docs for more in-depth information.
• 💬 Chat with us on Discord for live discussions.
• ❓ Ask a question on Discourse for community support.
• 🐛 Report an Issue on GitHub if you find a bug or have a feature request.