FlowGram is a composable, visual, easy-to-integrate, and extensible workflow development framework and toolkit, open-sourced by ByteDance. Its goal is to help developers build AI workflow platforms faster and more simply.
Purpose: FlowGram is aimed at developers who need to build their own AI workflow platforms, providing an underlying framework and toolset rather than a directly usable finished platform. Developers can build workflow products with visual orchestration capabilities based on it.
Main capabilities: The framework includes a process canvas, node configuration forms, variable scope chains, and out-of-the-box materials, including LLM, Condition, Code Editor, etc. The official demo shows a complete process: iterating over a list of cities, obtaining real-time weather via HTTP, parsing the temperature with a code node, having the LLM generate outfit recommendations, filtering through a condition node, aggregating the loop results, and finally having an advisor LLM select the most comfortable city and send it to the end node.
Usage: You can open and experience it online via CodeSandbox or StackBlitz. When creating a new project, the official recommendation is to choose the Free Layout Demo template. After starting the project, visit it in the browser at http://localhost:3000 to view it.
Applicable scenarios: Suitable for development teams that need to build AI workflow platforms, such as agent development tools, multi-platform AI deployment tools, visual SSL certificate management, and other scenarios. The official list includes Coze Studio, NNDeploy, Certimate, etc. as reference cases.
Limitations: FlowGram is not a ready-made workflow platform, but a framework and toolkit for building such platforms. Specific information such as charging, pricing, and platform support scope is not currently provided in the materials.
