gradio-app/gradio

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gradio-app/gradio has 43k+ stars and 3.5k+ forks on GitHub, is written in Python, and was last pushed on Oct 16, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 41 minutes ago
Added to GitGenius on August 31st, 2026
Created on December 19th, 2018
Open Issues & Pull Requests: 113 (+0)
GitHub issues: Enabled
Number of forks: 3,638
Total Stargazers: 43,793 (+0)
Total Subscribers: 205 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 16.2 hours
Mean response time: 42.0 days
90th percentile: 140.6 days
Tracked items: 2,806

Maintainer activity

8 people did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 11, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits. How this is counted.

How this project is maintained

About 3% of issues opened in the past year have never received a reply. 53% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Work labelled "needs repro" is answered fastest, typically in about 7 hours, while "toclose" waits about 5 months. Almost all tracked open issues have seen activity in the last three months. 93% of issues opened in the past year have since been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 96
New in 7 days: 12
Closed in 7 days: 4
Avg open age: 323 days
Stale 30+ days: 44
Stale 90+ days: 24

Recent activity

Opened in 7 days: 11
Closed in 7 days: 4
Comments in 7 days: 2
Events in 7 days: 5

Top labels

  • bug (1,697)
  • enhancement (422)
  • todo (188)
  • pending clarification (181)
  • toclose (161)
  • docs/website (157)
  • toinvestigate (106)
  • 💾 Dataframe (99)

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Detailed Description

Gradio is a Python framework that lets you build and share web applications for machine learning models, APIs, and Python functions without requiring JavaScript, CSS, or web hosting knowledge.

The tool solves the problem of rapidly prototyping and deploying interactive demos for machine learning work. It works by providing a Python API where you define input and output components, connect them to your model or function, and launch a web interface. The framework handles all frontend rendering and deployment infrastructure, allowing you to focus on the logic of your application rather than web development.

Gradio suits data scientists and machine learning engineers who want to showcase their work quickly, whether in notebooks, local development, or shared deployments. It is particularly valuable for those without web development experience who need to create interactive demos for models, APIs, or data analysis functions. The tool integrates naturally into Jupyter notebooks and Google Colab, making it accessible from common development environments.

The project maintains steady development activity with regular updates to its component library and core functionality. The codebase shows consistent refinement of existing features and expansion of the interface component ecosystem. Development appears focused on improving the developer experience and broadening the range of input and output types supported by the framework.