Journey to 1 Million Gradio Users!

5 years ago, we launched Gradio as a simple Python library to let researchers at Stanford easily demo computer vision models with a web interface.

Today, Gradio is used by >1 million developers each month to build and share AI web apps. This includes some of the most popular open-source projects of all time, like Automatic1111, Oobabooga’s Text Generation WebUI, Dall-E Mini, and LLaMA-Factory.

How did we get here? How did Gradio keep growing in the very crowded field of open-source Python libraries? I get this question a lot from folks who are building their own open-source libraries. This post distills some of the lessons that I have learned over the past few years:

1. Invest in good primitives, not high-level abstractions
2. Embed virality directly into your library
3. Focus on a (growing) niche
4. Your only roadmap should be rapid iteration
5. Maximize ways users can consume your library's outputs

1. Invest in good primitives, not high-level abstractions

When we first launched Gradio, we offered only one high-level class (gr.Interface), which created a complete web app from a single Python function. We quickly realized that developers wanted to create other kinds of apps (e.g. multi-step workflows, chatbots, streaming applications), but as we started listing out the apps users wanted to build, we realized what we needed to do: go lower.

Instead of building many high-level classes to support different use cases, we built a low-level API called Gradio Blocks that let users assemble applications from modular components, events, and layouts. Despite generally being more work to use, gr.Blocks today represents 80% of the usage of Gradio—including the highly popular apps mentioned above.

With a small team, a focus on low-level abstractions has necessarily meant that we could not chase many tempting, high-level abstractions. But this focus saved us from two common pitfalls:

2. Focus on a (growing) niche

3. Build for a (growing) niche use case

4. Your only roadmap should be rapid iteration