Agentex
Build and deploy intelligent agents with ease
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About The Project
AI agent capabilities can be understood in five levels, from simple chatbots to fully autonomous, self-driving agentic systems:
Today, most AI applications are limited to Level 3 (L3) and below, relying on synchronous request/response patterns. This restricts their ability to handle complex, long-running, or autonomous workflows.
Agentex is designed to be future-proof, enabling you to build, deploy, and scale agents at any level (L1–L5). As your needs grow, you can seamlessly progress from basic to advanced agentic AI—without changing your core architecture.
In this README we will start with scaffolding an L1 example just to learn the ropes. For more complicated levels, refer to the Python SDK and Docs mentioned below. Since we have documentation resources in several places, here is how to use each of them.
| Resource | Description |
|---|---|
| This README | Getting Started: Spin up a simple agent on your local computer from scratch in minutes. This comes with a full development UI and agent server. |
| Python SDK | Examples: Agent-building tutorials that work out of the box. These show how to build up from simple to more complex agents using Agentex. |
| Docs Site | Concepts: More in depth details on the what, why, and how of building L1-L5 agents. Enterprise Support: Description of how our zero-ops deployment works. Learn how to share hundreds of agents with the rest of your company. Each agent is hosted and scaled independently on cloud-agnostic infrastructure. |
Getting Started
Here is what we will build together in this README. We'll start with a Hello World agent, but quickly switch to a more intelligent one!
https://github.com/user-attachments/assets/9badad0d-f939-4243-ba39-68cafdae0078
Windows Users: Please see WINDOWS.md for a complete Windows-specific guide with PowerShell commands and troubleshooting tips.
Prerequisites
- Install Python 3.12+ (Required): https://www.python.org/downloads/
Redis is required. Agentex uses Redis for streaming and messaging. You do not need to install it yourself — the Docker stack (
./dev.sh/make dev) starts it for you. If you already run Redis locally it will conflict on port6379, so stop it first (see Troubleshooting).
macOS/Linux
# Install uv (fast Python package manager) https://docs.astral.sh/uv/getting-started/installation/
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install Docker and Node.js
brew install docker docker-compose node
# Stop redis - On Mac the default redis will conflict with the redis that is