smythos-studio README

The project's README from github.com/SmythOS/smythos-studio. As one markdown file: README.md.

SmythOS UI - The Visual Agent Builder

Homepage

The complete visual interface for building, deploying, and managing intelligent AI agents. SmythOS UI provides an intuitive drag-and-drop workspace where you can create sophisticated agent workflows without writing code, while still offering the flexibility of custom integrations when needed.

If you prefer to build agents with code instead, or you want to run your visual agents on your local PC without overhead, check out SmythOS Runtime, SDK and CLI! Great community, support, tutorials. Start in minutes!

SmythOS Visual Agent Studio

🚀 Getting Started | 📖 Documentation | 🐳 Docker Setup | 🤝 Contributing

Why SmythOS Studio

  1. Visual Agent Building: Creating AI agents should be as intuitive as drawing a flowchart.
  2. No-Code to Pro-Code: Start with visual building, extend with custom code when needed.
  3. Open Architecture: Build once, deploy anywhere with complete control over your infrastructure.

Design Principles

SmythOS UI provides a complete visual development environment for AI agents. Just as modern IDEs make software development accessible, SmythOS UI makes AI agent development intuitive and powerful.

Visual-First Development

SmythOS UI offers a drag-and-drop interface for building complex agent workflows. Whether you're connecting LLMs, integrating APIs, processing data, or orchestrating multi-step workflows, everything is visual and intuitive.

This approach makes AI agent development accessible to everyone - from business analysts who understand the processes to developers who need to scale them to production.

Key Benefits:

Quick Start

SmythOS Studio Tutorial

Method 1: Docker Quick Start

Get up and running instantly with Docker Compose.

git clone https://github.com/SmythOS/smythos-studio.git
cd smythos-studio
cp .env.compose.example .env
docker compose up -d

Access your application: http://localhost:6060

🐳 Full Docker Setup: See our Docker Compose Guide for container deployment with automatic SSL, database, and caching.

Troubleshooting: If you encounter any issues during setup, check the Troubleshooting section in the Docker Compose guide.


Method 2: Local Development Setup

Perfect for development, customization, and contributing to the project.

# Clone the repository
git clone https://github.com/SmythOS/smythos-studio.git
cd smythos-studio

# Copy environment configuration
cp .env.example .env
# Edit .env with your database credentials

# Install dependencies
pnpm install

# Start development servers
pnpm dev

Next Steps:

  1. Configure your MySQL database in .env
  2. Set up required subdomains for embodiments
  3. Start building your first agent!

📖 Detailed Setup: See our Contributing Guide for complete development setup instructions.


Repository Structure

This monorepo contains the complete SmythOS UI platform:

📱 App Package - packages/app

The main application containing the visual builder, React frontend, and backend services.

Key Features:

🔧 Middleware Package - packages/middleware

Core API services and database management for the SmythOS UI platform.

Features:

⚡ Runtime Package - packages/runtime

The execution server that uses SRE Core Engine to execute the agents.

Features:

Documentation

Contributing

We welcome contributions from the community! Whether you're fixing bugs, adding features, or improving documentation, your help makes SmythOS UI better for everyone.

Ways to Contribute:

Get Started:

  1. Read our Contributing Guide
  2. Check out open issues

Contributors

Community & Support

License

This project is licensed under the MIT License.

Ready to build your first AI agent?

🚀 Get Started Now | 🌟 Star this repo


/smɪθ oʊ ɛs juː aɪ/

Build visually. Deploy globally. Scale infinitely.

smythos-studio (SmythOS/smythos-studio)

a2a
Searching Database…

What is this?SmythOS Studio is an open-source visual builder for creating and deploying AI agents, where you drag and drop components to assemble agent workflows instead of writing code from scratch.
Is this a no-code tool, or can I still write custom code?It is a no-code-to-pro-code tool: you start with the visual drag-and-drop builder and can extend workflows with custom code when you need more control.
How do I get the Studio running?The fastest path is Docker Compose for an instant setup, or you can run a local development install by configuring MySQL and the project's .env file.
Do I need a MySQL database before I can run it?Yes, for local development you must configure a MySQL database in your .env file; the Docker Compose setup bundles the database automatically.
What extra setup is needed beyond just installing it?Local development also requires setting up required subdomains for embodiments (how agents are exposed as chatbots, APIs, etc.) before you can fully run things.
Who is this aimed at — business users or developers?It targets both: the visual flow is meant for business analysts and non-coders, while developers can extend agents with custom code and scale them to production.
Where does this run — in the cloud, locally, or both?Agents built in the Studio can be deployed anywhere: locally, in the cloud, or at the edge, since it's a self-hostable, open architecture.
What is an 'embodiment' in SmythOS?An embodiment is how a deployed agent is exposed to the outside world, such as a chatbot, an API endpoint, or another integration, handled by the runtime package.
Why would I use SmythOS Runtime/SDK/CLI instead of this Studio?If you'd rather build agents purely in code, or want to run visual agents locally without the Studio's full UI overhead, the separate SmythOS Runtime, SDK, and CLI are the lighter-weight code-first path.
How is the SmythOS Studio codebase organized?It's a monorepo split into packages/app (the React visual builder and backend API), packages/middleware (Prisma-based MySQL data layer), and packages/runtime (the execution server built on the SRE Core Engine).
Creator
SmythOS
Size
49.6 MB
Stars
649
Updated
CommitMar 31
Age
1y
Commits · 90 Days