agentok
AutoGen Visualized - Build Multi-Agent Apps with Drag-and-Drop Simplicity.
Stars: 148
Agentok Studio is a visual tool built for AutoGen, a cutting-edge agent framework from Microsoft and various contributors. It offers intuitive visual tools to simplify the construction and management of complex agent-based workflows. Users can create workflows visually as graphs, chat with agents, and share flow templates. The tool is designed to streamline the development process for creators and developers working on next-generation Multi-Agent Applications.
README:
AutoGen Visualized - Build Multi-Agent Apps with Drag-and-Drop Simplicity.
⚠️ Warning: This project is currently under development. It is not recommended for production use at this time.
Agentok Studio is a tool built upon AutoGen, a powerful agent framework from Microsoft and a vibrant community of contributors.
We consider AutoGen to be at the forefront of next-generation Multi-Agent Applications technology. Agentok Studio takes this concept to the next level by offering intuitive visual tools that streamline the creation and management of complex agent-based workflows. This simplifies the entire process for creators and developers.
The relationship between two agents is essential. To incorporate tool calls in a conversation, the LLM must determine which tools to invoke, while informing the user proxy about which nodes to execute. Configuring tools on the edge between these nodes is crucial for optimal operation.
We strive to create a user-friendly tool that generates native Python code with minimal dependencies. Simply put, Agentok Studio is a diagram-based code generator for autogen. The generated code is self-contained and can be executed anywhere as a normal Python program, relying solely on the official pyautogen
library.
We also integrated a basic RAG content management feature. This feature is still under development.
Contributions (Issues, Pull Requests, Documentation, even Typo-corrections) to this project are welcome! All contributors will be added to the Contribution Wall.
To quickly explore the features of Agentok Studio, visit https://studio.agentok.ai. While we offer an online deployment of this project, please note that it is not intended for production use. The service level agreement is not guaranteed, and stored data may be wiped due to breaking changes.
After login as Guest or with your OAuth2 account, you can click the Create New Project button to create a new project. The new project comes with a sample workflow. You can click the robot icon flashing on the right bottom to start the conversation.
Due to the limitations of GPT-4 and AutoGen, this simple workflow may not work as expected, but it's a good starting point to understand the basic concepts of Agentic App and Agentok Studio.
For a more in-depth look at the project, please refer to Getting Started.
The project contains Frontend (Built with Next.js) and Backend service (Built with FastAPI in Python), and have been fully dockerized.
Before running the project, you need to create a .env
file in the ui
abd api
directory and set environment variables.
cp frontend/.env.sample frontend/.env
cp api/.env.sample api/.env
cp api/OAI_CONFIG_LIST.sample api/OAI_CONFIG_LIST
Please be aware that Supabase provides both anon key and service_role key for each project. Please be sure to set anon key to NEXT_PUBLIC_SUPABASE_ANON_KEY
for frontend, and service role key to SUPABASE_SERVICE_KEY
for backend(api).
The easiest way to run on local is using docker-compose:
docker-compose up -d
You can also build and run the ui and service separately with docker:
docker build -t agentok-api ./api
docker run -d -p 5004:5004 agentok-api
docker build -t agentok-frontend ./frontend
docker run -d -p 2855:2855 agentok-frontend
(The default port number 2855 is the address of our first office.)
If you're interested in contributing to the development of this project or wish to run it from the source code, you have the option to run the ui and service independently. Here's how you can do that:
- Navigate to the ui directory
cd frontend
. - Rename
.env.sample
to.env.local
and set the value of variables correctly. - Install the necessary dependencies using the appropriate package manager command (e.g.,
pnpm install
oryarn
). - Run the ui service using the start-up script provided (e.g.,
pnpm dev
oryarn dev
).
If you see Server Error related to 'useContext' quite often, it's possibly caused by the bugs in turbo mode. In this case, please remove
--turbo
from the dev command in package.json.
- Switch to the api service directory
cd api
. - Rename
.env.sample
to.env
,OAI_CONFIG_LIST.sample
toOAI_CONFIG_LIST
, and set the value of variables correctly. - Install Poetry.
- Launch with command
poetry run uvicorn agentok_api.main:app --reload --port 5004
.
REPLICATE_API_TOKEN
is needed for LLaVa agent. If you need to use this agent, make sure to include this token in environment variables.
IMPORTANT: The latest version of AutoGen requires Docker for code execution by default. To proceed, you must either:
- Install Docker on your local machine, OR
- Disable this requirement by setting
AUTOGEN_USE_DOCKER=False
in theapi/.env
file.
Note: This requirement is disabled by default since the default deployment of this project is already dockerized.
This project relies on Supabase for user authentication and data storage. To get started, create a Supabase project on https://supabase.com/ and set the environment variables (with SUPABSE in the variable name) in the .env
file. If you prefer, you can deploy your own Supabase instance, but that is beyond the scope of this document.
Once you've started both the ui and api services by following the steps previously outlined, you can access the application by opening your web browser and navigating to:
- api: http://localhost:5004 (OpenAPI docs served at http://localhost:5004/docs)
- frontend: http://localhost:2855
If your services are started successfully and running on the expected ports, you should see the user interface or receive responses from the api services via this URL.
Contributions are welcome! It's not limited to code, but also includes documentation and other aspects of the project. You can open a GitHub Issue or leave comments on our Discord Server.
This project welcomes contributions and suggestions. Please read our Contributing Guide first.
If you are new to GitHub, here is a detailed help source on getting involved with development on GitHub.
Please consider contributing to AutoGen, as Agentok Studio relies on a robust foundation to deliver its capabilities. Your contributions can help enhance the platform's core functionalities, ensuring a more seamless and efficient development experience for Multi-Agent Applications.
This project uses 📦🚀semantic-release to manage versioning and releases. To avoid too frequent auto-releases, we make it a manual GitHub Action to trigger the release.
To follow the Semantic Release process, we enforced commit-lint convention on commit messages. Please refer to Commitlint for more details.
The project is licensed under Apache 2.0 with additional terms and conditions.
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