Run ComfyUI Workflows for Free with Gradio on Hugging Face Spaces
Hugging Face has published a guide enabling users to run ComfyUI workflows via Gradio on Hugging Face Spaces at no cost. This integration bridges the ComfyUI node-based image generation interface with Gradio's web UI framework, hosted on Spaces infrastructure. The post targets practitioners building and sharing diffusion model pipelines without local GPU requirements.
Related guides (3)
Related events (8)
Welcome, Gradio 5
Hugging Face announces Gradio 5, a major version release of its popular ML demo and application framework. The release likely includes significant updates to the tooling used by researchers and developers to build and share AI/ML interfaces. Gradio is widely used in the AI community for rapid prototyping and model demonstrations.
Upskill your LLMs With Gradio MCP Servers
Hugging Face published a blog post explaining how to build Model Context Protocol (MCP) servers using Gradio, enabling LLMs to access custom tools and external capabilities. The post covers how Gradio applications can be exposed as MCP-compatible tool endpoints that AI agents can invoke. This positions Gradio as part of the growing MCP ecosystem for extending LLM functionality with structured tool use.
How to Build an MCP Server with Gradio
Hugging Face published a tutorial on building Model Context Protocol (MCP) servers using Gradio, enabling AI models to expose tools and resources through the MCP standard. The post demonstrates how Gradio applications can serve as MCP-compatible backends, allowing AI agents to discover and invoke Gradio-hosted functions. This lowers the barrier for ML practitioners to participate in the emerging MCP ecosystem without deep protocol knowledge.
A Security Review of Gradio 5
Hugging Face published a security review of Gradio 5, examining vulnerabilities and mitigations in the popular ML demo and deployment framework. The post covers security improvements made in the version 5 release cycle. As Gradio is widely used for deploying AI/ML models and building interactive demos, its security posture directly affects the broader ML tooling ecosystem.
Gradio-Lite: Serverless Gradio Running Entirely in Your Browser
Gradio-Lite enables running Gradio ML demo applications entirely in the browser using Pyodide (Python compiled to WebAssembly), eliminating the need for a server backend. This allows developers to embed interactive ML interfaces directly in static web pages with no infrastructure costs. The approach leverages WebAssembly to execute Python and ML inference client-side, though with limitations on supported libraries and performance.
Hugging Face demonstrates agent chaining two Spaces to build a 3D Paris gallery
A Hugging Face blog post describes an agent that autonomously chains two Hugging Face Spaces to generate a 3D gallery of Paris, illustrating multi-step tool use and Space-to-Space orchestration. The demo showcases how agents can compose existing hosted ML tools without custom infrastructure. This is a practical capability demonstration relevant to the agent-tool ecosystem.
Bringing Serverless GPU Inference to Hugging Face Users via Cloudflare Workers AI
Hugging Face and Cloudflare have partnered to bring serverless GPU inference to Hugging Face users through Cloudflare Workers AI. The integration allows developers to run Hugging Face models on Cloudflare's global edge network without managing GPU infrastructure. This represents an expansion of serverless inference options for the Hugging Face ecosystem, lowering the barrier to deploying ML models at scale.
Five Big Improvements to Gradio MCP Servers
Hugging Face's Gradio team has announced five significant updates to Gradio's Model Context Protocol (MCP) server support. The improvements aim to make it easier to build and deploy MCP-compatible AI tool servers using Gradio. This is relevant to the growing agent-tool ecosystem where MCP is emerging as a standard protocol for connecting AI models to external tools and data sources.