Waldiez is an innovative platform that enables seamless collaboration among AG2 AI agents through an intuitive drag-and-drop interface. It allows users to design, orchestrate, and execute complex workflows by integrating various AI models and tools effortlessly. Learn more

• 🤖 Runs over AG2: Supporting the AG2 communication patterns for building agentic workflows.
• 🔬 JupyterLab Extension: Integrates Waldiez functionalities directly into JupyterLab, enabling users to create, convert, and execute workflows within their notebooks. Read more
• 🖥️ Visual Studio Code Extension: Provides a dedicated extension for Visual Studio Code, allowing users to design and manage Waldiez flows within the editor. Download
• 🎬 Waldiez Studio: A FastAPI-based application that facilitates the conversion and execution of Waldiez flows, offering a user-friendly web interface for managing workflows. Repository
• 🚀 Rapid Prototyping: Accelerates the prototyping process by exporting and importing existing models, tools/skills, agents, workflows.
• 🧠 Multi-LLM Suport: Supports several LLMs offered by OpenAI, Anthropic, Google, NVIDIA NIM, local hosted models (Ollama) and several others.
• 🐳 Docker Support: Offers pre-configured Docker images for easy deployment of Waldiez components, including the core package, JupyterLab extension, and Waldiez Studio. Check it out

Waldiez hosts several projects that collectively enhance the platform's capabilities:

• 🏛️ waldiez - The central repository that includes a React application designed to generate Waldiez flows, offering a graphical interface for workflow creation, tools and scripts to run and convert Waldiez flows into Python scripts or Jupyter notebooks, facilitating integration with Python-based projects and the documentation for the usage of waldiez. Feel free to upload examples of usage in the blogs section.
• 🔬 jupyter - A JupyterLab extension that integrates Waldiez into the Jupyter environment, enabling users to work with workflows directly within notebooks.
• 🖥️ vscode - An extension for Visual Studio Code that allows users to design and manage Waldiez flows within the editor.
• 🎬 studio - A FastAPI-based application providing a web interface for converting and running Waldiez flows, enhancing user experience.
• 🏃 runner: Responsible for queuing and running waldiez flows in isolated environments and stream logs/input/output via Redis.
• 📝 examples - A collection of exported waldiez flows.

These repositories collectively contribute to the robustness and versatility of the Waldiez platform, enabling users to create, manage, and execute AI-driven workflows across different environments and applications.