# TikTok Viral Product Detector (`inquisitive_magnolia/tiktok-viral-product-detector`) Actor Analyze public TikTok product pages for measurable viral signals. - **URL**: https://apify.com/inquisitive\_magnolia/tiktok-viral-product-detector.md - **Developed by:** [Neiver Alvarez](https://apify.com/inquisitive_magnolia) (community) - **Categories:** E-commerce, Social media, Videos - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.02 / actor start This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## TikTok Viral Product Detector Analyze public TikTok product pages for measurable viral signals. Built for public pages only. It does not log in, bypass CAPTCHAs, or access private data. Enable contact extraction only when you have a lawful purpose. # Actor input Schema ## `startUrls` (type: `array`): Public pages to analyze. Login and CAPTCHA bypass are not supported. ## `includeContacts` (type: `boolean`): Disabled by default; only contacts publicly displayed on the page are considered. ## `minScore` (type: `integer`): Only return results meeting this score threshold. ## `maxRequestsPerCrawl` (type: `integer`): Maximum number of public pages to process. ## `maxConcurrency` (type: `integer`): Maximum parallel requests. ## `maxTextLength` (type: `integer`): Maximum text characters retained from each page. ## `chunkSize` (type: `integer`): Target size of generated knowledge chunks. ## `chunkOverlap` (type: `integer`): Overlap between adjacent knowledge chunks. ## `proxyConfiguration` (type: `object`): Use Apify Proxy where appropriate and permitted. ## Actor input object example ```json { "startUrls": [ { "url": "https://example.com" } ], "includeContacts": false, "minScore": 0, "maxRequestsPerCrawl": 100, "maxConcurrency": 5, "maxTextLength": 50000, "chunkSize": 1200, "chunkOverlap": 150, "proxyConfiguration": { "useApifyProxy": true } } ```` # Actor output Schema ## `results` (type: `string`): Structured intelligence results for each analyzed public page. # 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 = { "startUrls": [ { "url": "https://example.com" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("inquisitive_magnolia/tiktok-viral-product-detector").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 = { "startUrls": [{ "url": "https://example.com" }] } # Run the Actor and wait for it to finish run = client.actor("inquisitive_magnolia/tiktok-viral-product-detector").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 '{ "startUrls": [ { "url": "https://example.com" } ] }' | apify call inquisitive_magnolia/tiktok-viral-product-detector --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=inquisitive_magnolia/tiktok-viral-product-detector", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TikTok Viral Product Detector", "description": "Analyze public TikTok product pages for measurable viral signals.", "version": "0.1", "x-build-id": "KeOebshma6xwbSTb6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/inquisitive_magnolia~tiktok-viral-product-detector/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-inquisitive_magnolia-tiktok-viral-product-detector", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/inquisitive_magnolia~tiktok-viral-product-detector/runs": { "post": { "operationId": "runs-sync-inquisitive_magnolia-tiktok-viral-product-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/inquisitive_magnolia~tiktok-viral-product-detector/run-sync": { "post": { "operationId": "run-sync-inquisitive_magnolia-tiktok-viral-product-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Public URLs", "type": "array", "description": "Public pages to analyze. Login and CAPTCHA bypass are not supported.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "includeContacts": { "title": "Extract publicly displayed contacts", "type": "boolean", "description": "Disabled by default; only contacts publicly displayed on the page are considered.", "default": false }, "minScore": { "title": "Minimum intelligence score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only return results meeting this score threshold.", "default": 0 }, "maxRequestsPerCrawl": { "title": "Maximum pages", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of public pages to process.", "default": 100 }, "maxConcurrency": { "title": "Concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum parallel requests.", "default": 5 }, "maxTextLength": { "title": "Maximum text per page", "minimum": 1000, "maximum": 200000, "type": "integer", "description": "Maximum text characters retained from each page.", "default": 50000 }, "chunkSize": { "title": "RAG chunk size", "minimum": 300, "maximum": 5000, "type": "integer", "description": "Target size of generated knowledge chunks.", "default": 1200 }, "chunkOverlap": { "title": "RAG chunk overlap", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Overlap between adjacent knowledge chunks.", "default": 150 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Use Apify Proxy where appropriate and permitted.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```