# Adobe Stock Image Scraper | Fast & Reliable (`fatihtahta/adobe-stock-image-scraper`) Actor Extract Adobe Stock assets at scale with rich metadata, creator data, thumbnails, dimensions, licensing flags, category signals, and advanced filters. Built for enterprise-grade visual intelligence, creative research, asset discovery, and automated data pipelines. - **URL**: https://apify.com/fatihtahta/adobe-stock-image-scraper.md - **Developed by:** [Fatih Tahta](https://apify.com/fatihtahta) (community) - **Categories:** AI, Agents, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $0.70 / 1,000 results 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Adobe Stock Image Scraper **Slug:** `fatihtahta/adobe-stock-image-scraper` ### Overview Adobe Stock Image Scraper collects structured Adobe Stock asset records, including titles, asset identifiers, asset URLs, thumbnails, dimensions, creator information, category metadata, licensing flags, and collection context. [Adobe Stock](https://stock.adobe.com) is a large public marketplace for creative assets, making its searchable asset data useful for market research, catalog analysis, creative operations, and monitoring workflows. The actor turns repeatable Adobe Stock searches and filters into normalized JSON records that can be used in analytics tools, data pipelines, dashboards, and enrichment workflows. It is designed for dependable recurring data acquisition with consistent output fields and clear limits, without requiring manual copying or one-off browser work. Results reflect the publicly available data at run time and can be scheduled, exported, or integrated into downstream systems. ### Why Use This Actor - **Market research / analytics:** collect structured extraction data for asset supply analysis, category comparison, creator coverage, visual trend monitoring, and operational reporting. - **Product & content teams:** build repeatable collection workflows for creative asset discovery, campaign planning, content audits, and dataset normalization. - **Developers / data engineering pipelines:** feed Adobe Stock records into downstream systems, warehouses, search indexes, and enrichment pipelines using predictable JSON output. - **Lead generation / enrichment:** identify creators, categories, asset URLs, and public artist pages that can enrich research or prospecting datasets. - **Monitoring / competitive tracking:** schedule recurring runs to observe changes in asset availability, free collection coverage, AI-generated content, media types, and category movement. ### Common Use Cases - **Market intelligence:** monitor asset supply, category distribution, free availability, creator activity, and visual format coverage across selected searches. - **Creative asset discovery:** collect searchable Adobe Stock records for review queues, campaign planning, mood boards, and content selection workflows. - **Competitive monitoring:** track visible changes in public creative asset collections, category movement, or creator coverage over time. - **Catalog and directory building:** populate owned databases with structured public asset records, thumbnails, creator metadata, and category fields. - **Data enrichment:** add current public Adobe Stock attributes to existing BI, CRM, creative operations, or analytics datasets. - **Recurring reporting:** schedule periodic collection runs for dashboards, alerts, trend analysis, and historical comparison. ### Quick Start 1. Choose one or more `queries`, or leave `queries` empty for broad discovery. 2. Add optional filters such as `asset_type`, `orientation`, `usage_rights`, `generative_ai`, `people`, `background`, `icons`, `vivid_color`, or `free_to_use` when you need a narrower dataset. 3. Set a small `limit`, such as `25` or `50`, for the first validation run. 4. Run the actor in Apify Console. 5. Inspect the first dataset records to confirm that the output fields match your workflow. 6. Increase `limit`, add more search terms, or schedule the actor after the output is verified. ### Input Parameters The actor accepts optional Adobe Stock search terms, asset filters, and a per-target result limit. | Parameter | Type | Description | Default | | --- | --- | --- | --- | | `asset_type` | string | Limits keyword searches to one asset type. Allowed values: `images`, `videos`, `templates`, `3d`. | – | | `queries` | array of strings | Optional search terms. Enter one word or phrase per item. Each search term is collected separately when provided. Leave empty for a broader run without a keyword. | – | | `undiscovered_content` | boolean | Focuses keyword searches on Adobe Stock content marked as not previously downloaded. Availability can vary over time. | `false` | | `background` | array of strings | Narrows keyword searches by background or subject format. Allowed values: `transparent`, `isolated_assets`. | – | | `generative_ai` | string | Chooses whether keyword searches focus on generative AI content or exclude it. Allowed values: `ai_only`, `ai_excluded`. | – | | `icons` | array of strings | Narrows keyword searches to icon-specific formats. Allowed values: `individual_icon`, `icon_sheet`. | – | | `orientation` | array of strings | Filters assets by visual orientation. Allowed values: `horizontal`, `vertical`, `square`, `panoramic`. | – | | `people` | string | Chooses whether searches include assets with people or focus on assets without people. Allowed values: `include_people`, `exclude_people`. | – | | `usage_rights` | string | Limits keyword searches by usage-rights category. Allowed values: `commercial_usage`, `editorial_usage`. | – | | `vivid_color` | string | Steers searches by color intensity. Allowed values: `very_low`, `low`, `high`, `very_high`. | – | | `free_to_use` | boolean | Restricts keyword searches to Adobe Stock assets from the free collection. | `false` | | `limit` | integer | Maximum number of records to save for each search term or target. Minimum: `1`. | – | ### Choosing Inputs Use `queries` when you already know the topic, keyword, theme, or asset segment you want to collect. Leave optional filters empty when the goal is broad discovery, then add filters gradually when you need a more targeted dataset. Narrow filters such as `asset_type`, `orientation`, `usage_rights`, `generative_ai`, `people`, `background`, `icons`, `vivid_color`, and `free_to_use` can improve relevance, while broader inputs improve discovery and coverage. Start with a small `limit` to validate the output shape and increase it after confirming that the records match your downstream requirements. ### Example Inputs #### Search-driven image collection ```json { "queries": ["nature", "forest canopy"], "asset_type": "images", "orientation": ["horizontal"], "people": "exclude_people", "usage_rights": "commercial_usage", "limit": 50 } ```` #### Free icon discovery ```json { "queries": ["finance dashboard icons"], "asset_type": "images", "icons": ["individual_icon"], "free_to_use": true, "vivid_color": "high", "limit": 40 } ``` #### Broad filtered discovery ```json { "asset_type": "templates", "generative_ai": "ai_excluded", "background": ["isolated_assets"], "undiscovered_content": true, "limit": 25 } ``` ### Output #### 9.1 Output destination The actor writes results to an Apify dataset as JSON records. The dataset is designed for direct consumption by analytics tools, ETL pipelines, and downstream APIs with minimal post-processing. When multiple entity types or record shapes exist, the README documents each shape separately based on the provided Example Output. The provided output contains one record shape: an Adobe Stock asset record. #### 9.2 Record envelope and stable identifiers Each record represents one Adobe Stock asset and includes identifiers, public asset URLs, media metadata, creator details, category information, availability flags, and source context. Recommended idempotency key: `id`. If a downstream system requires a URL-based key, `url` is also a stable public asset reference, and `fingerprint` can be retained as a secondary run-level record identifier. Use the recommended key for deduplication and upserts when syncing repeated runs into warehouses, CRMs, search indexes, or asset catalogs. Stable identifiers make records easier to merge, deduplicate, and sync across repeated runs. The `sourceUrl` field records the public collection context used for the record, while `fingerprint` provides an additional deterministic identifier for the saved record. #### 9.3 Examples ##### Example: Adobe Stock asset ```json { "id": "305060700", "id32": "HValp62AU5V1ZTWb2kegfnefp7r5kgDs", "url": "https://stock.adobe.com/tr/images/looking-up-at-the-green-tops-of-trees/305060700", "title": "Looking up at the green tops of trees.", "assetType": "Image", "mediaTypeLabel": "Photo", "contentType": "image/jpeg", "format": "jpeg", "thumbnailUrl": "https://t4.ftcdn.net/jpg/03/05/06/07/360_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg", "thumbnailUrlWebp": "https://t4.ftcdn.net/jpg/03/05/06/07/360_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.webp", "largeThumbnailUrl": "https://as2.ftcdn.net/v2/jpg/03/05/06/07/500_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg", "extraLargeThumbnailUrl": "https://as2.ftcdn.net/v2/jpg/03/05/06/07/1000_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg", "width": 5760, "height": 3840, "author": "proslgn", "creatorId": 205763247, "artistPageUrl": "https://stock.adobe.com/tr/contributor/205763247/proslgn?load_type=author", "categoryId": 782, "categoryName": "Plants and Flowers", "isFree": false, "isPremium": false, "isFireflyGenerated": false, "isVector": false, "isVideo": false, "isImage": true, "isPurchasable": true, "defaultLicenseId": 1, "sourceUrl": "https://stock.adobe.com/tr/Ajax/Search?filters%5Bcontent_type%3A3d%5D=1&filters%5Bcontent_type%3Aaudio%5D=0&filters%5Bcontent_type%3Aillustration%5D=1&filters%5Bcontent_type%3Aimage%5D=1&filters%5Bcontent_type%3Aphoto%5D=1&filters%5Bcontent_type%3Atemplate%5D=1&filters%5Bcontent_type%3Avideo%5D=1&filters%5Bcontent_type%3Azip_vector%5D=1&filters%5Bglobally_safe_collection%5D=1&filters%5Binclude_stock_enterprise%5D=0&get_facets=0&k=nature&limit=100&order=relevance&search_page=1&search_type=asset-type-change", "fingerprint": "4a75cf22d1b4473a4134", "seed_id": "8e7f35c5a556", "seed_type": "query", "seed_value": "nature", "page_index": 1, "extraction_strategy": "api_json" } ``` ### Field Reference #### Adobe Stock asset record - **id** *(string, required)*: Adobe Stock asset identifier. Recommended idempotency key. - **id32** *(string, optional)*: Secondary asset identifier used by Adobe Stock media URLs. - **url** *(string, required)*: Public Adobe Stock asset page URL. - **title** *(string, optional)*: Asset title. - **assetType** *(string, optional)*: High-level asset type, such as image or video. - **mediaTypeLabel** *(string, optional)*: Human-readable media label, such as photo. - **contentType / format** *(string, optional)*: Media content type and file format. - **thumbnailUrl** *(string, optional)*: Standard thumbnail image URL. - **thumbnailUrlWebp** *(string, optional)*: WebP thumbnail image URL. - **largeThumbnailUrl** *(string, optional)*: Larger preview thumbnail URL. - **extraLargeThumbnailUrl** *(string, optional)*: Extra-large preview thumbnail URL. - **width / height** *(integer, optional)*: Asset dimensions in pixels. - **author** *(string, optional)*: Public creator or contributor name. - **creatorId** *(integer, optional)*: Adobe Stock creator identifier. - **artistPageUrl** *(string, optional)*: Public contributor page URL. - **categoryId** *(integer, optional)*: Adobe Stock category identifier. - **categoryName** *(string, optional)*: Adobe Stock category name. - **isFree** *(boolean, optional)*: Whether the asset is marked as part of the free collection. - **isPremium** *(boolean, optional)*: Whether the asset is marked as premium. - **isFireflyGenerated** *(boolean, optional)*: Whether the asset is marked as Firefly-generated. - **isVector** *(boolean, optional)*: Whether the asset is marked as vector content. - **isVideo** *(boolean, optional)*: Whether the asset is marked as video content. - **isImage** *(boolean, optional)*: Whether the asset is marked as image content. - **isPurchasable** *(boolean, optional)*: Whether the asset is marked as purchasable. - **defaultLicenseId** *(integer, optional)*: Default license category identifier when provided. - **sourceUrl** *(string, optional)*: Public collection context associated with the saved record. - **fingerprint** *(string, optional)*: Deterministic record fingerprint for deduplication support. - **seed\_id** *(string, optional)*: Identifier for the input target that produced the record. - **seed\_type** *(string, optional)*: Input target type, such as `query`. - **seed\_value** *(string, optional)*: Input value that produced the record. - **page\_index** *(integer, optional)*: Result page number associated with the record. - **extraction\_strategy** *(string, optional)*: Record source label included for traceability. ### Data Quality, Guarantees, And Handling - **Structured records:** results are normalized into predictable JSON objects for downstream use. - **Best-effort extraction:** fields may vary by region, session, availability, or source-side experiments. - **Optional fields:** null-check optional fields in downstream code, especially creator, category, license, and thumbnail metadata. - **Deduplication:** use `id` as the strongest stable key; `url` and `fingerprint` can be retained as secondary identifiers. - **Freshness:** results reflect the publicly available data at run time. - **Repeated runs:** use the recommended idempotency key when syncing data into warehouses, CRMs, search indexes, or asset catalogs. ### Tips For Best Results - Start with a small `limit` to validate the output shape before scaling up. - Use one theme, asset segment, or search intent per run when you need cleaner segmentation. - Leave optional filters empty when the goal is broad discovery. - Add filters gradually to understand how each field changes coverage. - Use `asset_type` and `orientation` when your workflow depends on a specific media format or layout. - Schedule recurring runs for monitoring workflows instead of relying on manual one-off collection. - Store `id`, `url`, and `fingerprint` when deduplicating records over time. ### How to Run on Apify 1. Open the Actor in Apify Console. 2. Configure the available input fields for the target scope. 3. Set the maximum number of outputs to collect with `limit`. 4. Click **Start** and wait for the run to finish. 5. Open the dataset and review the first records. 6. Download results in JSON, CSV, Excel, or another supported format. ### Scheduling & Automation #### Scheduling **Automated Data Collection** Schedule runs to keep Adobe Stock asset datasets fresh for reporting, monitoring, and enrichment workflows. Recurring runs are especially useful when tracking category movement, free collection availability, creator coverage, or AI-generated asset trends. - Navigate to **Schedules** in Apify Console - Create a new schedule, such as daily, weekly, or a custom cron expression - Configure input parameters - Enable notifications for run completion - Add webhooks for automated processing #### Integration Options - **BI dashboards:** monitor asset volume, category movement, media mix, free collection coverage, and creator trends over time. - **Data warehouses:** store historical Adobe Stock asset records for analysis, reporting, and audit-friendly comparisons. - **ETL pipelines:** normalize dataset records into organization-specific schemas for search, analytics, or creative operations platforms. - **Webhooks:** trigger validation, ingestion, notification, or downstream processing after each completed run. - **Google Sheets or Airtable:** review smaller curated asset collections with content, marketing, or research teams. - **Slack, Discord, or email alerts:** notify teams when scheduled monitoring runs complete or when downstream checks detect notable changes. ### Export Formats And Downstream Use Apify datasets can be exported or consumed by downstream systems for operational reporting, review, and automated ingestion. - **JSON:** for APIs, applications, and data pipelines. - **CSV or Excel:** for spreadsheet workflows and manual review. - **API access:** for automated ingestion into owned systems. - **BI and warehouses:** for reporting, dashboards, and historical analysis. ### Performance Estimated run times: - **Small runs (< 1,000 outputs):** ~3-5 minutes - **Medium runs (1,000-5,000 outputs):** ~5-15 minutes - **Large runs (5,000+ outputs):** ~15-30 minutes Execution time varies based on filters, result volume, and how much information is returned per record. Highly filtered runs can finish faster, while broad discovery or detail-rich records may take longer. ### Limitations - Availability depends on what `https://stock.adobe.com` publicly exposes at run time. - Some optional fields may be missing on sparse records or asset types with limited metadata. - Very broad searches may take longer or require higher limits to collect enough useful records. - Target-side changes can affect field availability, naming, or visible result composition. - Regional, account, language, or availability differences may change visible results. - The actor does not guarantee completeness for every possible Adobe Stock result matching a broad topic. ### Troubleshooting - **No results returned:** check search terms and filters, and verify that Adobe Stock has matching public records for the selected scope. - **Fewer results than expected:** broaden filters, raise `limit`, or confirm that the target contains enough matching records. - **Some fields are empty:** optional fields depend on what each record publicly provides. - **Run takes longer than expected:** reduce scope, lower `limit` for validation, or split broad collection into smaller segments. - **Output changed:** compare the current output with the field reference and report a small sample if support is needed. ### FAQ #### What data does this actor collect? It collects public Adobe Stock asset records, including asset identifiers, titles, URLs, thumbnails, dimensions, creator metadata, category fields, availability flags, and source context. #### Can I filter by location, category, date, price, or other criteria? The current input schema supports search terms, asset type, background, generative AI status, icon format, orientation, people, usage rights, vivid color, free collection status, undiscovered content, and result limit. It does not include location, date, price, or category input fields. #### Why did I receive fewer results than my limit? The `limit` is a maximum, not a guarantee. A run can return fewer records when Adobe Stock has fewer matching public results for the selected query and filters. #### Can I schedule recurring runs? Yes. Use Apify schedules to run the actor daily, weekly, or on a custom cron schedule with saved input parameters. #### How do I avoid duplicates across runs? Use `id` as the primary idempotency key. Retain `url` and `fingerprint` as secondary identifiers when your downstream system benefits from additional matching fields. #### Can I export the data to CSV, Excel, or JSON? Yes. Apify datasets support JSON, CSV, Excel, and other export formats from the dataset view. #### Does this actor collect private data? No. The actor is intended to collect publicly available Adobe Stock asset information visible from `https://stock.adobe.com`. #### Does the actor download the licensed asset file? The output may include public preview image URLs when available. It does not download licensed asset files, grant usage rights, or replace Adobe Stock licensing requirements. #### What should I include when reporting an issue? Include the input used, the run ID, expected versus actual behavior, and a small output sample if it helps illustrate the issue. Redact anything sensitive before sharing. ### Compliance & Ethics #### Responsible Data Collection This actor collects publicly available **Adobe Stock creative asset** information from **https://stock.adobe.com** for legitimate business purposes, including: - **Creative industry** research and market analysis - **Content operations** and asset discovery workflows - **Market intelligence** and recurring public data monitoring This section is informational and not legal advice. Users are responsible for ensuring that their use of collected data complies with applicable laws, regulations, and platform terms. #### Best Practices - Use collected data in accordance with applicable laws, regulations, and the target site's terms - Respect individual privacy and personal information - Use data responsibly and avoid disruptive or excessive collection - Do not use this actor for spamming, harassment, or other harmful purposes - Follow relevant data protection requirements where applicable, such as GDPR and CCPA ### Support For help, use the actor page or Issues section. Include the input used, with sensitive values redacted if needed, the run ID, the expected versus actual behavior, and a small output sample when it helps clarify the problem. # Actor input Schema ## `asset_type` (type: `string`): Limit keyword searches to a specific Adobe Stock asset type, such as images, videos, templates, or 3D content. ## `queries` (type: `array`): Enter one word or phrase per line, or leave empty to run without a keyword. Each search term is collected separately when provided. ## `undiscovered_content` (type: `boolean`): Focus keyword searches on Adobe Stock content marked as not previously downloaded. Use this when you want less commonly used assets; availability may vary over time. ## `background` (type: `array`): Narrow keyword searches to assets with transparent backgrounds or isolated subjects when those formats fit your creative workflow. ## `generative_ai` (type: `string`): Choose whether keyword searches should focus only on generative AI content or exclude generative AI assets. ## `icons` (type: `array`): Narrow keyword searches to individual icons or icon sheets when collecting icon-focused creative assets. ## `orientation` (type: `array`): Select one or more orientations when your output needs to match a layout, placement, or campaign format. ## `people` (type: `string`): Choose whether keyword searches should include assets with people or focus on assets without people. ## `usage_rights` (type: `string`): Limit keyword searches by the usage-rights category that matches your intended editorial or commercial workflow. ## `vivid_color` (type: `string`): Use color intensity to steer keyword searches toward muted or highly vivid assets, depending on the visual style you need. ## `free_to_use` (type: `boolean`): Restrict keyword searches to Adobe Stock assets from the free collection when your workflow requires free-to-use results. ## `limit` (type: `integer`): Set the maximum number of records to save for each search term. Leave empty when you do not want to apply a per-target cap. ## Actor input object example ```json { "undiscovered_content": false, "free_to_use": false, "limit": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "limit": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("fatihtahta/adobe-stock-image-scraper").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 = { "limit": 100 } # Run the Actor and wait for it to finish run = client.actor("fatihtahta/adobe-stock-image-scraper").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 '{ "limit": 100 }' | apify call fatihtahta/adobe-stock-image-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fatihtahta/adobe-stock-image-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Adobe Stock Image Scraper | Fast & Reliable", "description": "Extract Adobe Stock assets at scale with rich metadata, creator data, thumbnails, dimensions, licensing flags, category signals, and advanced filters. Built for enterprise-grade visual intelligence, creative research, asset discovery, and automated data pipelines.", "version": "0.0", "x-build-id": "6ohsGtjdhJ0OAhZRJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fatihtahta~adobe-stock-image-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fatihtahta-adobe-stock-image-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fatihtahta~adobe-stock-image-scraper/runs": { "post": { "operationId": "runs-sync-fatihtahta-adobe-stock-image-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fatihtahta~adobe-stock-image-scraper/run-sync": { "post": { "operationId": "run-sync-fatihtahta-adobe-stock-image-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "asset_type": { "title": "Choose an Asset Type", "enum": [ "images", "videos", "templates", "3d" ], "type": "string", "description": "Limit keyword searches to a specific Adobe Stock asset type, such as images, videos, templates, or 3D content." }, "queries": { "title": "Add Optional Search Terms", "type": "array", "description": "Enter one word or phrase per line, or leave empty to run without a keyword. Each search term is collected separately when provided.", "items": { "type": "string" } }, "undiscovered_content": { "title": "Show Undiscovered Content (marked as not previously downloaded)", "type": "boolean", "description": "Focus keyword searches on Adobe Stock content marked as not previously downloaded. 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