Daggr: Chain apps programmatically, inspect visually

Daggr, a newly launched open-source Python library, is set to revolutionize AI workflow development by enabling users to programmatically chain Gradio apps, machine learning models, and custom functions with remarkable ease. This library automatically creates a visual canvas that allows developers to inspect intermediate outputs, rerun individual steps, and maintain state across complex pipelines using just a few lines of code. This is significant as it addresses common frustrations in AI development, such as debugging long workflows and losing track of results, all while ensuring that code remains version-controllable.

One of Daggr's standout features is its seamless integration with Gradio Spaces, which allows developers to incorporate Gradio apps as nodes in their workflows effortlessly. With the ability to visualize code flow, inspect outputs, and modify inputs at any step, Daggr streamlines the debugging process and encourages rapid experimentation. It also supports state persistence, ensuring that users can easily resume their workflows. As Daggr is still in beta, feedback from the community will be crucial in shaping its future, making it an exciting addition to the toolkit of AI/ML developers seeking more efficient methods for building and sharing their workflows.