Get OpenAgent running and send your first AI-powered message in under 5 minutes.

Quick Start

The goal of this guide is to reach the "First Message" milestone as quickly as possible. OpenAgent runs on port 14000 by default.

Prerequisites

Before you begin, make sure you have:

OpenAgent installed — choose a deployment method below: one-line installer, Docker, or development setup.
An API key — get one from a model provider like DeepSeek, OpenAI, Anthropic, or any supported provider.

Deploy the Infrastructure

Zero installation required. OpenAgent ships as a single self-contained binary. Download it, double-click (or run from the terminal), and it's live — no package managers, no runtimes, no Docker.

Choose Your Deployment Method

macOS / Linux / WSL

curl -fsSL https://raw.githubusercontent.com/the-open-agent/openagent/master/scripts/install.sh | bash

Windows (PowerShell)

irm https://raw.githubusercontent.com/the-open-agent/openagent/master/scripts/install.ps1 | iex

Download the latest binary from the GitHub Releases page.

Windows — download openagent_windows_x86.exe and double-click it, or run from PowerShell:

.\openagent_windows_x86.exe

No WSL, no Docker, no additional dependencies. Runs natively on Windows 10/11.

Linux — download the binary for your platform and run:

chmod +x openagent_linux_x86
./openagent_linux_x86

macOS — download the binary for your platform (openagent_darwin_x86 for Intel, openagent_darwin_arm64 for Apple Silicon) and run:

chmod +x openagent_darwin_arm64
./openagent_darwin_arm64

docker run -d -p 14000:14000 --name openagent casbin/openagent

Requires Go 1.25+, Node.js 18+, and MySQL 8.0+.

git clone https://github.com/the-open-agent/openagent.git
cd openagent
go run main.go
# Separate terminal
cd web && yarn install && yarn start

Once the server is running, navigate to http://localhost:14000.

Configure a Provider

Navigate to Providers → Add Provider.

Category: Model
Type: DeepSeek (Recommended for cost) or OpenAI
API Key: Enter your credentials.
Model (Sub Type): Select deepseek-v4-flash or a model ID supported by your provider.

Initialize an Agent (Store)

Navigate to Stores → Add Store.

Name: primary-assistant
Model Provider: Select the provider from the previous step.
System Prompt: "You are a professional research assistant."

Validate with Chat

Open the Chat interface from the sidebar. Select your agent and send:

"Hello OpenAgent, identify yourself."

Milestone Reached: You now have a functional, self-hosted orchestration engine.

Activate Knowledge Retrieval (RAG)

Transition from a standard LLM to a Knowledge Agent by indexing your own documents.

Add an Embedding Provider

Go to Providers → Add Provider.

Category: Embedding
Type: e.g., OpenAI
Sub Type: text-embedding-3-small (Recommended)

This provider handles the "translation" of your text into mathematical vectors.

Link Knowledge to Agent

Edit your Store and assign the Embedding Provider. Set Knowledge Count to 5 (Recommended for 2026 models) to define retrieval density.

Ingest Documents

Go to Files → Upload, drop your PDFs/Markdown files, and assign them to the Store. Once the status reaches Finished, the agent is grounded in your data.