# Hugging Face API — Model Metadata Export (`tugelbay/huggingface-governance-intelligence`) Actor Use the Hugging Face API to search public models and export IDs, tasks, licenses, gated status, downloads, likes, SHA, and update dates as JSON or CSV. - **URL**: https://apify.com/tugelbay/huggingface-governance-intelligence.md - **Developed by:** [Tugelbay Konabayev](https://apify.com/tugelbay) (community) - **Categories:** AI, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.40 / 1,000 hugging face model records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README **Hugging Face API for model metadata.** Search public models and export clean records through the Apify API, schedules, webhooks, or one-click dataset downloads. This Actor uses the official Hub API and never mirrors model files, private repositories, or gated files. Actor ID `huggingface-governance-intelligence` is a stable legacy identifier. The product scope is public model metadata search and export only, not governance scoring or compliance certification. ![Hugging Face model metadata flowing through an API into structured records](https://konabayev.com/images/apify-actors/hugging-face-model-metadata-api.webp) ### Why use this Actor - Model ID, title, task, library, and Hugging Face URL - License tags and public or gated status - Downloads, likes, repository SHA, and update dates - One normalized row per matching public model - JSON, CSV, Excel, XML, RSS, and API access through Apify datasets Use it for model catalog research, license reviews, public-model inventories, and scheduled metadata snapshots. It is a search-and-export API, not a model inference service or a persistent change-history database. ### Quick start 1. Add one or more public model-search terms. 2. Choose a per-query result limit from 1 to 100. 3. Run the Actor and download the dataset or read it through the Apify API. ```json { "queries": ["text-generation"], "maxItems": 5 } ```` The query is sent to the official Hugging Face model search endpoint. Add up to 20 queries and request 1–100 records per query. ### Example output ```json { "recordType": "result", "query": "text-generation", "sourceId": "daotthuanSE/cv_anytext_text_generation_editing", "title": "daotthuanSE/cv_anytext_text_generation_editing", "status": "public", "url": "https://huggingface.co/daotthuanSE/cv_anytext_text_generation_editing", "updatedAt": "2026-07-08T10:44:55.000Z", "metrics": { "downloads": 0, "likes": 0 }, "metadata": { "pipelineTag": "text-generation", "licenses": ["apache-2.0"], "gated": false }, "sourceName": "Hugging Face Hub" } ``` Fields can be absent when the source record does not publish them. The Actor preserves that uncertainty instead of inventing values. ### Input | Field | Type | Required | Description | | --- | --- | --- | --- | | `queries` | string\[] | Yes | Model names, tasks, authors, or other Hugging Face model-search terms. Up to 20. | | `maxItems` | integer | No | Results stored per query, from 1 to 100. Default: 25. | | `canaryMode` | boolean | No | Returns one no-network release-status row for deterministic platform QA. | ### Output data contract Each row uses the stable fields `recordType`, `query`, `sourceId`, `title`, `description`, `status`, `url`, `publishedAt`, `updatedAt`, `metrics`, `metadata`, `sourceName`, `sourceUrl`, `retrievedAt`, and `releaseState`. The `OUTPUT` record in the default key-value store reports the item count, empty-query count, network use, release state, and any mandatory notice. ### Automate it - Run scheduled model metadata snapshots with Apify Schedules - Trigger downstream work with webhooks - Read the dataset from the Apify API - Export to JSON, CSV, Excel, or another supported dataset format For a buyer-focused guide and integration examples, see the [Hugging Face Model Metadata API page](https://konabayev.com/tools/hugging-face-model-metadata-api/?utm_source=apify\&utm_medium=store-readme\&utm_campaign=hugging-face-model-metadata-api). ### Limitations and responsible use - Source: [official Hugging Face Hub model API](https://huggingface.co/api/models) - API documentation: [Hugging Face Hub API](https://huggingface.co/docs/hub/api) - Rate limits: [Hugging Face Hub rate limits](https://huggingface.co/docs/hub/rate-limits) - Terms: [Hugging Face Terms of Service](https://huggingface.co/terms-of-service) - Independent product; not affiliated with, endorsed by, or sponsored by Hugging Face - Public metadata only - No model weights, binaries, model-card mirroring, or private repositories - Gated model metadata can be returned, but the Actor cannot access or download gated files - This is not a Hugging Face scraper for repository files or model artifacts - HTTPS source hosts are allowlisted; redirects are refused - Responses, retries, and timeouts are bounded - Empty searches produce an explicit `emptyResult` row and are not charged ### API comparison | Option | Best for | Important boundary | | --- | --- | --- | | Official Hugging Face API | Direct source integration and custom clients | You own normalization, storage, retries, and downstream exports | | This Actor | Bounded model searches with normalized Apify datasets and automation | Snapshot export only; it does not store a historical diff database | ### Validation evidence On 2026-07-23, the bounded source canary returned 100 complete public model metadata records, including 95 declared license tags and 12 models marked gated by the source. On 2026-07-24, actor-specific live QA returned five non-empty records from the deployed build. ### Pricing The primary pay-per-event charge is `result-item`. - List price: **$0.002 per successfully stored source record** - Apify plan tiers: $0.0018, $0.0016, or $0.0014 per record - Canary, empty-result, and failed rows are not charged - Maximum valid input: 20 queries × 100 records = 2,000 source records, or **$4.00 maximum list-price PPE charge per run** - Duplicate query strings are removed before requests; if the same source record matches two different queries, each stored row is charged Apify platform compute charges and plan credits are shown separately by Apify. ### Support For a reproducible issue, include the public query, expected behavior, run ID, and the relevant source URL. Never send private model tokens or gated repository credentials. ### FAQ #### Does this run Hugging Face models? No. It searches public model metadata. It does not perform inference. #### Does it download model files? No. It returns metadata and source URLs only. #### Can it monitor changes? You can schedule repeated snapshots and compare datasets downstream. The Actor itself does not maintain a historical diff database. # Actor input Schema ## `queries` (type: `array`): Model names, tasks, authors, or other terms accepted by Hugging Face model search. Maximum 20. ## `maxItems` (type: `integer`): Maximum model records to store for each query. ## `canaryMode` (type: `boolean`): Return one release-status record without sending a source request. ## Actor input object example ```json { "queries": [ "text-generation" ], "maxItems": 5, "canaryMode": false } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset containing normalized results and explicit empty or release-gate rows. ## `summary` (type: `string`): Key-value-store record containing source, release, item, empty-query, and network metrics. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "text-generation" ], "maxItems": 5, "canaryMode": false }; // Run the Actor and wait for it to finish const run = await client.actor("tugelbay/huggingface-governance-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": ["text-generation"], "maxItems": 5, "canaryMode": False, } # Run the Actor and wait for it to finish run = client.actor("tugelbay/huggingface-governance-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "text-generation" ], "maxItems": 5, "canaryMode": false }' | apify call tugelbay/huggingface-governance-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=tugelbay/huggingface-governance-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hugging Face API — Model Metadata Export", "description": "Use the Hugging Face API to search public models and export IDs, tasks, licenses, gated status, downloads, likes, SHA, and update dates as JSON or CSV.", "version": "0.1", "x-build-id": "QQVjjY9B0LJMJXP6Z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/tugelbay~huggingface-governance-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-tugelbay-huggingface-governance-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/tugelbay~huggingface-governance-intelligence/runs": { "post": { "operationId": "runs-sync-tugelbay-huggingface-governance-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/tugelbay~huggingface-governance-intelligence/run-sync": { "post": { "operationId": "run-sync-tugelbay-huggingface-governance-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "queries" ], "properties": { "queries": { "title": "Model search queries", "minItems": 1, "maxItems": 20, "type": "array", "description": "Model names, tasks, authors, or other terms accepted by Hugging Face model search. Maximum 20.", "items": { "type": "string" } }, "maxItems": { "title": "Results per query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum model records to store for each query.", "default": 25 }, "canaryMode": { "title": "No-network release canary", "type": "boolean", "description": "Return one release-status record without sending a source request.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```