Hugging Face Spaces Monitor - AI Demo Discovery & Likes

Track which public demo listings appear and how their likes and SDK metadata change.

Hugging Face Spaces Monitor with saved field comparisons, source URLs and CSV/JSON exports. Simple inputs, bounded results and readable reports. No source API key.

Start in under a minute

1. Paste ai demo searches into the first input field, or use the included sample.
2. Keep the five-result limit for your first run and choose Start.
3. Open Observations, Scope and diagnostics, or the Readable run report in Output. Export CSV or JSON from the dataset.

{
  "queries": [
    "flux"
  ],
  "maxResults": 5,
  "itemsPerQuery": 3
}

No source account, API key, paid proxy or extra subscription is required for these public endpoints. Source availability and rate limits still apply.

Who this helps

AI product scouts and developers researching public demos.

A real output sample

Captured in a successful bounded Apify run; arrays and long text are shortened for readability. Values are snapshots, not live guarantees.

{
  "recordId": "black-forest-labs/FLUX.1-dev",
  "title": "black-forest-labs/FLUX.1-dev",
  "repositoryId": "black-forest-labs/FLUX.1-dev",
  "likes": 9583,
  "sdk": "gradio",
  "tags": [
    "gradio",
    "region:us"
  ],
  "createdAt": "2024-08-01T14:14:02.000Z",
  "url": "https://huggingface.co/spaces/black-forest-labs/FLUX.1-dev",
  "observedAt": "2026-10-18T03:53:24.307Z",
  "comparisonStatus": "not_requested"
}

What you receive

One row per unique confirmed observation. Every row includes a stable recordId, title, source URL and observation time.

Field	Meaning
repositoryId	Source-reported repository id; missing optional values remain null.
likes	Source-reported likes; missing optional values remain null.
sdk	Source-reported sdk; missing optional values remain null.
tags	Source-reported tags; missing optional values remain null.
createdAt	Source-reported created at; missing optional values remain null.
comparisonStatus	not_requested, new, changed or unchanged
changedFields	Fields different from your last saved observation
previous	Previous saved source values when comparison is enabled

Saved comparisons

Enable Compare with saved observations, choose a snapshot name, and reuse the same input scope. The first run establishes history; it cannot report changes before that point. Enable Save only new or changed observations for later runs if you want a change-only export. An unchanged run can correctly save zero rows.

Only confirmed saved rows advance history. A bounded or failed run never establishes that a missing record was deleted. History is stored in a named key-value store in the running user's account. Use one writer per snapshot: do not overlap runs against the same snapshot. Change the snapshot name when starting a new independent workflow.

Scope and limitations

Public Spaces search ordered by likes, one page. No inference calls, tool execution, availability tests or private Spaces. Likes do not establish product quality.

At most ten input values and five hundred saved rows per run. Results requested per query controls a single source page (1–50, default five); there is no pagination. Each input performs one bounded public source request. Requests are paced. Responses are capped at 8 MiB and share the run deadline. No authentication bypass or code execution is performed. HTTP 429 stops further requests. Source failures appear in SUMMARY and the HTML report, never as paid data rows.

Pricing

The configured base price is $0.001 per saved observation, plus $0.00005 per start at the default memory. Five observations cost $0.00505 at that base rate. Applicable plan discounts and the Store pricing panel govern actual charges. Set a maximum charge in Run options. Diagnostics, reports and unchanged skipped rows are not dataset result events.

A practical workflow

AI product scouts and developers researching public demos. Track which public demo listings appear and how their likes and SDK metadata change. Start with the included five-result sample, review source links, then save your own scope as an Actor task. Use a named snapshot for repeat runs and keep source metadata with downstream exports.

Make it recurring

Save an Actor task with your inputs, then attach an Apify Schedule. For change detection, keep the same snapshot and avoid overlapping runs. Add an integration to deliver results to your own spreadsheet or workflow. No external delivery is enabled automatically.

Frequently asked questions

Why did a repeat run return zero rows? With change-only mode enabled, unchanged records are skipped. Check SUMMARY to distinguish this from empty matches, limits, or an upstream error.

Does a missing record mean it was deleted? No. Searches cover a bounded source window; a record can move outside it. Missing records never become deletion claims.

Can I export or integrate the data? Yes. Use Apify dataset exports for CSV/JSON, or the Actor API and your own integrations. No external message or delivery is enabled by default.

Examples

1. AI demo searches: flux — A bounded flux observation sample. Review source evidence and export rows or compare them in a later run.
2. AI demo searches: whisper — A bounded whisper observation sample. Review source evidence and export rows or compare them in a later run.
3. AI demo searches: video — A bounded video observation sample. Review source evidence and export rows or compare them in a later run.

Source and support

Official source documentation. This independent Mayd IT tool is not affiliated with the source platform. Open an Actor issue with the run ID and expected result, or contact bmay@mayd-it.com. Never include credentials.