Make AG2 Agents Collaborate: Drag, Drop, and Orchestrate with Waldiez.

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  • License: Apache Software License
  • Author: Panagiotis Kasnesis
  • Requires: Python <3.14, >=3.10
  • Provides-Extra: ag2-extras , dev , docs , jupyter , mqtt , redis , runner , studio , test , websockets
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Project description

Waldiez

Coverage Status PyPI Downloads PyPI version npm version

Make AG2 Agents Collaborate: Drag, Drop, and Orchestrate with Waldiez

Design AI Agents and translate a Waldiez flow to AG2:

Features

  • Convert .waldiez flows to .py or .ipynb
  • Run a .waldiez flow
  • Store the runtime logs of a flow to csv for further analysis

Installation

Python

On PyPI:

python -m pip install waldiez

From the repository:

python -m pip install git+https://github.com/waldiez/waldiez.git

React Component

If you’re looking for the React component, please refer to README.npm.

Note: The React component is only for creating and editing flows — it is not needed to convert or run flows (that functionality is handled by the Python package).

To include waldiez on your website using CDN, here is a simple example:

<!doctype html>
<html lang="en">
    <head>
        <meta charset="UTF-8" />
        <script type="importmap">
          {
            "imports": {
              "react": "https://esm.sh/react@19.1.0",
              "react-dom/client": "https://esm.sh/react-dom@19.1.0/client",
              "@waldiez/react": "https://esm.sh/@waldiez/react"
            }
          }
        </script>
        <style>
            body {
                margin: 0;
                padding: 0;
                justify-content: center;
                background-color: white;
                color: black;
            }
            @media (prefers-color-scheme: dark) {
                body {
                    background-color: black;
                    color: white;
                }
            }
            #loading {
                width: 100vw;
                height: 100vh;
                padding: 0;
                margin: 0;
                display: flex;
                align-items: center;
            }
            #root {
                display: flex;
                flex-direction: column;
                width: 100vw;
                height: 100vh;
            }
            #waldiez-root {
                position: relative;
                width: 80vw;
                height: 80vh;
                margin: auto;
            }
        </style>
        <link rel="stylesheet" href="https://esm.sh/@waldiez/react/dist/@waldiez.css">
    </head>
    <body>
        <div id="root"></div>
        <div id="loading">
            Loading...
        </div>
        <script type="module" src="https://esm.sh/tsx"></script>
        <script type="text/babel">
          import { createRoot } from "react-dom/client"
           import { Waldiez } from "@waldiez/react";
           const root = document.getElementById("root");
           document.getElementById("loading").style.display = "none";
           createRoot(root).render(
                <div id="waldiez-root">
                    <Waldiez />
                </div>
            )
        </script>
    </body>
</html>

To add the waldiez library to your app:

npm install @waldiez/react
# or
yarn add @waldiez/react
# or
pnpm add @waldiez/react
# or
bun add @waldiez/react

Usage

UI Options

  • For creating-only (no exporting or running) waldiez flows, you can use the playground at https://waldiez.github.io.
  • There is also a jupyterlab extension here: waldiez/jupyter
  • You also can use the vscode extension:
  • Finally, you can use waldiez-studio, which includes a FastAPI app to handle the conversion and running of waldiez flows.

The jupyterlab extension and waldiez studio are also provided as extras in the main package.

pip install waldiez[studio]  # or pip install waldiez_studio
pip install waldiez[jupyter]  # or pip install waldiez_jupyter
# or both
pip install waldiez[studio,jupyter]

CLI

# Convert a Waldiez flow to a python script or a jupyter notebook
waldiez convert --file /path/to/a/flow.waldiez --output /path/to/an/output/flow[.py|.ipynb]
# Convert and run the script, optionally force generation if the output file already exists
waldiez run --file /path/to/a/flow.waldiez --output /path/to/an/output/flow[.py|.ipynb] [--force]

Using docker/podman

🪟 Windows (PowerShell with Docker or Podman Desktop)

$hostInputFile = "C:\Users\YourName\Documents\flow.waldiez"
$containerInputFile = "/home/waldiez/workspace/flow.waldiez"
$hostOutputDir = "C:\Users\YourName\Documents\waldiez_output"
$containerOutputDir = "/home/waldiez/output"
$containerOutputFile = "/home/waldiez/output/flow.ipynb"

# Convert a flow to Jupyter Notebook
docker run --rm `
  -v "$hostInputFile:$containerInputFile" `
  -v "$hostOutputDir:$containerOutputDir" `
  waldiez/waldiez convert --file $hostInputFile --output $containerOutputFile

# Convert and run it
docker run --rm `
  -v "$flow:/home/waldiez/workspace/flow.waldiez" `
  -v "$output:/output" `
  waldiez/waldiez run --file $hostInputFile --output $containerOutputFile

Note If using Hyper-V mode, make sure your files are in a shared folder Docker Desktop has access to.
More info: https://docs.docker.com/desktop/settings/windows/#file-sharing

🐧 Linux/macOS/WSL (Docker or Podman)

CONTAINER_COMMAND=docker # or podman
# Asuming ./flow.waldiez exists
HOST_INPUT="$(pwd)/flow.waldiez"
CONTAINER_INPUT="/home/waldiez/workspace/flow.waldiez"
HOST_OUTPUT_DIR="$(pwd)/output"
CONTAINER_OUTPUT_DIR="/home/waldiez/output"
mkdir -p ${HOST_OUTPUT_DIR}

# Convert a flow to a Python script
$CONTAINER_COMMAND run --rm \
  -v ${HOST_INPUT}:${CONTAINER_INPUT} \
  -v ${HOST_OUTPUT_DIR}:${CONTAINER_OUTPUT_DIR} \
  waldiez/waldiez convert --file $HOST_INPUT --output ${CONTAINER_OUTPUT_DIR}/flow.py

# Convert to a Jupyter Notebook instead
$CONTAINER_COMMAND run --rm \
  -v ${HOST_INPUT}:${CONTAINER_INPUT} \
  -v ${HOST_OUTPUT_DIR}:${CONTAINER_OUTPUT_DIR} \
  waldiez/waldiez convert --file $HOST_INPUT --output ${CONTAINER_OUTPUT_DIR}/flow.ipynb

# Convert and run it (force override generated file if it exists)
$CONTAINER_COMMAND run --rm -it \
  -v ${HOST_INPUT}:${CONTAINER_INPUT} \
  -v ${HOST_OUTPUT_DIR}:${CONTAINER_OUTPUT_DIR} \
  waldiez/waldiez run --file $HOST_INPUT --force

As a library

Export a flow

# Export a Waldiez flow to a python script or a jupyter notebook
from waldiez import WaldiezExporter
flow_path = "/path/to/a/flow.waldiez"
output_path = "/path/to/an/output.py"  # or .ipynb
exporter = WaldiezExporter.load(flow_path)
exporter.export(output_path)

Run a flow

# Run a flow
from waldiez import WaldiezRunner
flow_path = "/path/to/a/flow.waldiez"
output_path = "/path/to/an/output.py"
runner = WaldiezRunner.load(flow_path)
runner.run(output_path=output_path)

Tools

Known Conflicts

  • autogen-agentchat: This package conflicts with ag2. Ensure that autogen-agentchat is uninstalled before installing waldiez. If you have already installed autogen-agentchat, you can uninstall it with the following command:

    pip uninstall autogen-agentchat -y

    If already installed waldiez you might need to reinstall it after uninstalling autogen-agentchat:

    pip install --force --no-cache waldiez ag2

See also

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Panagiotis Kasnesis
Panagiotis Kasnesis
📆 🔬		 Lazaros Toumanidis
Lazaros Toumanidis
💻		 Stella Ioannidou
Stella Ioannidou
📣 🎨		 Amalia Contiero
Amalia Contiero
💻 🐛		 Christos Chatzigeorgiou
Christos Chatzigeorgiou
💻
Add your contributions

License

This project is licensed under the Apache License, Version 2.0 (Apache-2.0).

Project details

Verified details

These details have been verified by PyPI
Project links
Owner
GitHub Statistics
Maintainers
Avatar for waldiez from gravatar.com waldiez

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License
  • Author: Panagiotis Kasnesis
  • Requires: Python <3.14, >=3.10
  • Provides-Extra: ag2-extras , dev , docs , jupyter , mqtt , redis , runner , studio , test , websockets
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