Hugging Face Spaces Search Scraper is a BrowserAct Bot template for collecting structured public Space records from Hugging Face. Configure a base URL, keyword, and result count, then run the Bot to return ranked AI app and demo metadata for product research, ecosystem tracking, lead discovery, catalog enrichment, or automation workflows.
What Does BrowserAct Hugging Face Spaces Search Scraper Do?
This template opens Hugging Face's public Spaces search API, parses Space records, derives public Space URLs, and returns one structured record per Space.
Key Features
- Extract public Hugging Face Spaces search results without requiring a login.
- Capture Space ID, URL, author, Space name, SDK, title, emoji, tags, likes, created date, last modified date, private status, gated status, and keyword.
- Sort results by likes in descending order.
- Configure base URL, keyword, and count.
- Handle empty result sets cleanly.
What Data Can I Extract from Hugging Face?
| Field | Description |
|---|---|
rank |
Search result position assigned by the Bot. |
space_id |
Full Hugging Face Space ID. |
space_url |
Public Space page URL. |
author |
Author or namespace. |
space_name |
Space name derived from the Space ID. |
sdk |
Space SDK, such as Gradio, Streamlit, or static. |
title |
Public display title when provided. |
emoji |
Public Space emoji when provided. |
tags |
Public Space tags as a comma-separated string. |
likes |
Like count. |
last_modified |
Last modified date. |
created_at |
Created date. |
private |
Whether the Space is marked private in the response. |
gated |
Gated status when returned. |
search_keyword |
Keyword used for the run. |
How to Use Hugging Face Spaces Search Scraper
- Click Run task.
- Enter the Hugging Face base URL.
- Enter an AI app, model type, workflow, demo, or product keyword.
- Set how many Space records to collect.
- Run the Bot and review the structured Space results.
- Reuse the Bot with another keyword or connect the output to your workflow.
Input Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
base_url |
Yes | https://huggingface.co |
Hugging Face site base URL without a trailing slash. |
keyword |
Yes | chatbot |
Search keyword used to find public Spaces. |
count |
Yes | 20 |
Maximum number of public Space records to collect. |
Example Output
The table below uses records preserved from the validated Bot run. Up to the first 5 records are shown, and long values are shortened in this documentation preview.
| rank | space_id | space_url | author | space_name | sdk | title | emoji | tags | likes | last_modified | created_at | private | gated | search_keyword |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | cvachet/pdf-chatbot | https://huggingface.co/spaces/cvachet/pdf-chatbot | cvachet | pdf-chatbot | gradio | PDF Chatbot | globe | gradio, region:us | 381 | 2025-06-16T20:34:06.000Z | 2023-12-28T21:35:20.000Z | false | null | chatbot |
How Does it Work?
BrowserAct builds the public Hugging Face API URL in the format {base_url}/api/spaces?search={keyword}&limit={count}&sort=likes&direction=-1&full=true. The response is a JSON array sorted by likes in descending order.
For each Space object, BrowserAct maps published fields into a flat record, derives the Space URL as {base_url}/spaces/{space_id}, splits the Space ID into author and Space name, and normalizes tags into a comma-separated string for table-friendly output.
How to Build a New Scraper Bot with Agent Built
Step 1: Describe the Data You Need
Open BrowserAct and start Agent Built from the Home prompt box or from Create -> Build with Agent. Paste a clear request that includes the website, the records to collect, the filters or search conditions, the fields to return, the result limit, and the inputs you want to reuse later.
Step 2: Let BrowserAct Build and Test the Bot
BrowserAct explores the live website, works out the navigation and extraction path, and validates the result. If BrowserAct asks for clarification, reply in the same build conversation with the missing URL, condition, field, example, or expected output.
Step 3: Run the Bot and Review the Result
When the build is complete, run the Bot with the default inputs first. Review the structured records, source URLs, missing fields, and row count before reusing the Bot with new inputs or connecting it to another workflow.
Why Scrape Hugging Face Space Results?
Hugging Face Space data helps teams discover public AI apps, compare SDK adoption, track demos around a topic, monitor ecosystem activity, enrich product research databases, and route public Space metadata into dashboards, alerts, or agent workflows.
Who Can Use This Template?
- AI product teams researching public app examples.
- Developer relations teams monitoring popular demos.
- Growth teams discovering active builders and projects.
- Data teams enriching AI application catalogs.
- Automation builders routing Space metadata into spreadsheets, databases, alerts, or agents.
How Many Results Can You Scrape?
Use count to control the number of Space records returned. The template supports up to the public API limit verified during build, and Hugging Face returns fewer records when fewer public matches are available.
Automation and Export
BrowserAct returns structured Hugging Face Space records first. You can then use the output through API JSON responses, n8n workflows, Make scenarios, Zapier automations, MCP-based agent workflows configured from the Bot's Integrations tab, or manual CSV review.
Need Help?
Contact us at
Discord: Discord Community
E-mail: service@browseract.com
