gradio
Python library for easily interacting with trained machine learning models
Decision gist · record as of 2026-08-14
Yes. Gradio is worth installing if you need to build and share web interfaces for ML models or Python functions without web development expertise. It has low install friction, active maintenance, a permissive license, no known vulnerabilities, and strong adoption. The only consideration is the substantial dependency footprint (28 runtime packages) and the Python 3.10+ requirement; if your environment is constrained, verify compatibility first.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or higher.
- Low install friction with a pure Python wheel distribution.
- Active maintenance with a release 2 days old and 43364 repository stars.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 43,364 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 18,428,509 downloads/mo, #1,084 on PyPI
Alternatives
Verify before relying
pip install gradio
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
demo.launch()- Whether the 30+ built-in components mentioned in the description are all documented and stable in version 6.24.0.
- Performance characteristics when handling concurrent users or large file uploads through shared links.
- Compatibility of the hot-reload and vibe mode features with different development environments.
What it is and what it does
Gradio is a Python framework that wraps machine learning models, APIs, or arbitrary Python functions into interactive web applications with minimal code. It provides high-level classes like Interface for simple demos, Blocks for custom layouts and complex workflows, and ChatInterface for chatbot UIs. The framework handles the entire web stack—FastAPI backend, Starlette routing, and frontend rendering—so developers write only Python. Once built, demos can be shared instantly via public URLs using Gradio's built-in sharing feature, allowing anyone to interact with the application from a browser while computation runs locally.
The package depends on a substantial ecosystem: FastAPI and Uvicorn for the web server, Pydantic for validation, Pillow and NumPy for media handling, Hugging Face Hub for model integration, and several utility libraries. It supports Python 3.10 through 3.13 and is classified as Production/Stable. The framework is actively maintained with frequent releases and strong community adoption (top 5000 PyPI packages by downloads).
Use it for
- Quickly prototype and demo a trained machine learning model without building a custom web application.
- Share a data analysis or visualization tool with collaborators or stakeholders via a public link.
- Build a chatbot interface for a language model or conversational API in a few lines of Python.
- Create an interactive form-based tool for any Python function (e.g., tax calculator, image processor).
- Deploy a complex multi-step workflow with custom layouts and conditional logic using Blocks.
- Integrate with Hugging Face Hub to showcase models directly from the model card.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Gradio is worth installing if you need to build and share web interfaces for ML models or Python functions without web development expertise. It has low install friction, active maintenance, a permissive license, no known vulnerabilities, and strong adoption. The only consideration is the substantial dependency footprint (28 runtime packages) and the Python 3.10+ requirement; if your environment is constrained, verify compatibility first.
Install
gradio on PyPI
Before you install
Low install friction with a pure Python wheel distribution. Active maintenance with a release 2 days old and 43364 repository stars. Requires Python 3.10 or higher and pulls in 28 runtime dependencies including fastapi, uvicorn, and huggingface-hub.
Requires Python 3.10 or higher.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary projects.
Quickstart
pip install gradio
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="textbox", outputs="textbox")
demo.launch()
Verify before relying
- Whether the 30+ built-in components mentioned in the description are all documented and stable in version 6.24.0.
- Performance characteristics when handling concurrent users or large file uploads through shared links.
- Compatibility of the hot-reload and vibe mode features with different development environments.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 28 packagesanyioaudioop-ltsbrotlifastapigradio-clientgroovyhf-gradiohttpxhuggingface-hubjinja2markupsafenumpyorjsonpackagingpandaspillowpydanticpydubpython-multipartpytzpyyamlsafehttpxsemantic-versionstarlettetomlkittypertyping-extensionsuvicorn |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 18,428,509 / month, #1,084 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Visualization |
Evidence: gradio-6.24.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “machine learning web ui builder”
- gradioGradio builds web interfaces for machine learning models, APIs, and…
- h2o-waveH2O Wave is a Python framework for building interactive web…
- niceguiNiceGUI is a Python framework for building browser-based user…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also gradio-client · gradio-imageslider · gradio-pdf · hf-gradio · groovy · gradio-rangeslider · maibot-dashboard · valohai-utils · kumoai · coremltools