FlowGram is a composable, visual, and extensible workflow development framework designed to accelerate the creation of AI workflow platforms. It targets developers seeking a faster, simpler way to build custom AI applications by providing a toolkit with built-in components like a flow canvas, form engine, and variable management. The benefit lies in abstracting complex workflow orchestration, allowing developers to focus on AI logic and platform features.

How It Works

The framework employs a visual, node-based approach, offering both free and fixed layout canvases for designing workflows. Core components include a form engine for node configuration, a variable engine for managing data scope and types, and a library of ready-to-use materials such as LLM integrations, conditional logic, and code editors. This modular design facilitates easy integration and extensibility, enabling developers to construct sophisticated AI workflows efficiently.

Quick Start & Requirements

To begin, create a new project using npx @flowgram.ai/create-app@latest, recommending the "Free Layout Demo" template. Navigate to the created directory (cd demo-free-layout), install dependencies with npm install, and start the development server using npm start. The demo application will be accessible at http://localhost:3000. Prerequisites include Node.js and npm. Links to interactive demos are available on CodeSandbox and StackBlitz.

Highlighted Details

• Flexible Canvases: Supports both free-form and fixed-layout canvases, including compound nodes for branches and loops.
• Robust Form & Variable Engines: Manages node data CRUD, rendering, validation, and side effects, alongside scope-aware variable management with type inference.
• Extensible Materials: Includes pre-built components for LLM integration, conditional logic, and code editing, with support for custom materials.
• Visual Development: Offers a visual interface for building and managing complex AI workflows.

Maintenance & Community

Community support is primarily channeled through GitHub Issues and a Feishu (Lark) user group, accessible via a QR code in the repository. Information on contributors and specific community channels like Discord or Slack is not detailed in the provided README excerpt.

Licensing & Compatibility

The project is released under an open-source license, detailed in the LICENSE file within the repository. Specific compatibility notes for commercial use or linking with closed-source projects are not explicitly stated.

Limitations & Caveats

FlowGram is presented as a framework and toolkit, not a complete, out-of-the-box platform, requiring significant development effort to build a functional AI workflow application. No specific technical limitations, alpha status, or known bugs are detailed in the provided README.