Granular feature access per resource group
Feature access can be controlled per resource group instead of only by organization role, for example leaving Jobs open, restricting Inference Endpoints to admins, and limiting blog publishing.
Also shipped Aug 12, 2026Hugging Face in August 2026 →
Define business concepts with Pages (Beta)
You can now use Pages to give business terms, acronyms, and KPIs a single governed definition. Part of Unity Catalog semantics , Pages form the human-modeled layer of the Genie Ontology that Genie One draws on to ground its answers. See Pages .
Custom trace views in the MLflow trace explorer are in Beta
You can now build custom trace views in the Databricks MLflow trace explorer. Describe the layout you want in plain language, and Genie generates a reusable view that surfaces the trace fields, metrics, and feedback controls most relevant to your review workflow. See Build a custom trace view .
Google Search Console connector is available in Beta
The managed Google Search Console connector is now available in Beta in Databricks Lakeflow Connect. Use it to ingest search performance data, site metadata, and sitemap information from Google Search Console into Databricks.
Glean connector in Lakeflow Connect (Beta)
You can now ingest data from Glean into Databricks using the managed Glean connector in Lakeflow Connect. The connector ingests company-wide usage insights for search, Assistant, and agents, along with the shortcuts (go links) defined in your Glean deployment, using a Glean Client API token. This feature is in Beta . See Glean connector .
Amplitude connector (Beta)
The Amplitude connector in Lakeflow Connect is now in Beta. Ingest product analytics event data along with event, cohort, and annotation metadata from Amplitude. See Amplitude connector .
Gemini Enterprise: GitHub connector with data federation
The GitHub connector with data federation is generally available (GA) in Gemini Enterprise. The connector lets you search and act on GitHub repositories, issues, and pull requests directly from the Gemini Enterprise agent, with tool actions such as creating branches, adding issue comments, merging pull requests, and pushing files.
More from Hugging Face HubEvery Hugging Face Hub release →
Granular Feature Access
Organizations can now control feature access per resource group rather than across the whole organization. This allows restricting features like Inference Endpoints to admins while leaving Jobs open to everyone.
Filter HF Jobs by label
Jobs can be filtered by label, with most-used labels shown as chips with job counts and a free-form key=value input, on user and organization jobs pages.
Filter Jobs by Label
Users can now filter Jobs by label on both user and organization jobs pages. Most-used labels appear as clickable chips with job counts, and a free-form key=value input allows filtering by any label.
Hugging Face MCP Server adds hf_fs tool
The Hugging Face MCP Server's new hf_fs tool provides a single interface to repositories, storage, documentation, papers and more, with search, in just over 1,000 tokens.
Sandboxes for the Hugging Face MCP Server
Sandboxes give an assistant secure execution environments attached to buckets and repositories for dataset analysis, model training, and Space creation.
Egress metrics for users and organizations
Users see egress usage in the dashboard and organizations get a per-user egress breakdown. It currently covers only traffic routed through the Hugging Face CDN.
Build Spaces with AI agents
The new Space creation page has an option to build with an AI agent: copy the generated command into your agent to build and iterate on a Space for a model, paper, or local folder.
[v1.31.0] Custom labels for Sandboxes, More resilient downloads and more
🏷️ Custom labels for Sandboxes Dedicated sandboxes now accept custom labels, attached to the underlying Job. This is useful for cost attribution, bookkeeping, or finding and reconnecting to the sandboxes created by a given controller run. Labels use the same -l / --label KEY=VALUE syntax as hf jobs run .