automation

openai-agents-python: Automate Workflows

Name: openai-agents-python: Automate Workflows
Author: openai

Founders get multi-agent workflow automation with openai-agents-python, a lightweight framework.

28,375 stars4,438 forksPythonGuide quality 8/10Updated 8/4/2026100% free · open source

What it does

Openai-agents-python allows founders to automate complex workflows by defining and orchestrating multiple AI agents that can interact with each other and their environment.

When to use it

•When you need to automate a business process that involves multiple decision-making steps
•When you want to integrate AI-driven decision making into your existing workflows
•When you need to simulate complex scenarios or environments to test and optimize your business strategies

Ready-to-paste prompt

Create an agent that responds to user input: `agent = Agent('user_input'); agent.act = lambda state: input('Please enter your response: ')`

Heads up: Make sure you have the `openai` library installed and configured with a valid API key to use the `openai-agents` library, as it relies on OpenAI's API for its functionality

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🔑 Needs an API key

Works after you add credentials — the setup agent will ask you for them.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/openai-agents-python && curl -fsSL https://workflowstacks.com/api/skills/openai-agents-python/claude-skill -o ~/.claude/skills/openai-agents-python/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How openai-agents-python: Automate Workflows works

Codeflow

Free to inspect

Openai-agents-python: Automate Workflows is a very large Python project (~176k lines across 585 code files, plus 346 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, MIT license, has a test suite.

Size

Very large codebase

~176k lines · 585 code files · days to read — use, don't read

Setup

One-command install

Installs like a normal app. Reading the code is optional.

Runs on

Python

No API keys detected

Python 100%

Where to start reading

1
README.md
Start here — what it does and how to install it
2
AGENTS.md
The instructions the AI actually follows
3
pyproject.toml
Dependencies and the commands it exposes
4
src/agents/__init__.py
Inside src/ — the main logic begins here
5
examples/README.md
A worked example — copy this to get going

What's in each folder

src/Core code — the actual logic315 files

docs/Documentation407 files

examples/Examples you can copy308 files

integration_tests/Folder37 files

tests/Tests — proof it works387 files

.agents/Tool / agent settings68 files

.github/CI / automation (GitHub Actions)20 files

.vscode/Editor / agent settings2 files

READMEHas testsDocumentedCI checksExamples includedMIT licenseUpdated this month