# AI Text Verifier -- GPTZero & ZeroGPT Checker (`oneary/ai-text-verifier`) Actor Check any text for AI-generated content using GPTZero, ZeroGPT, and Originality.ai. Get AI probability scores, perplexity, burstiness, and sentence-level analysis across multiple engines in one call. - **URL**: https://apify.com/oneary/ai-text-verifier.md - **Developed by:** [Luan M.](https://apify.com/oneary) (community) - **Categories:** AI, Education, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $75.00 / 1,000 ai check results 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.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 ## 🤖 AI Content Detector — GPTZero, ZeroGPT & Originality.ai Scraper **Check any text for AI-generated content** across multiple detection engines. Get AI probability scores, human probability estimates, perplexity metrics, and sentence-level analysis — all in one API call. > ✅ Works with GPTZero (free + API), ZeroGPT (free), and Originality.ai (API) > ✅ Supports raw text input AND URL scraping > ✅ Structured JSON output for easy integration > ✅ No browser overhead — fast HTTP-based detection --- ### 🎯 Use Cases #### 🎓 Academic Integrity - Verify student submissions for AI-generated content - Check research papers and essays before submission - Monitor AI usage in academic environments #### 📰 Content Verification - Verify blog posts and articles for AI authorship - Ensure content originality for publishing platforms - Fact-check AI-generated vs human-written content #### 🔍 SEO & Content Marketing - Verify content teams are producing original work - Check competitor content for AI generation - Ensure AI-assisted content meets quality thresholds #### ⚖️ Legal & Compliance - Verify legal documents for AI involvement - Monitor regulatory submissions - Audit AI usage in professional content --- ### 📋 Input Parameters | Field | Type | Required | Description | |-------|------|----------|-------------| | `textContent` | string | No* | Raw text to analyze for AI generation | | `targetUrl` | string | No* | URL to scrape and analyze | | `sources` | string[] | No | Detection engines: `gptzero`, `zerogpt`, `originality` | | `gptzeroApiKey` | string | No | GPTZero API key for higher rate limits | | `originalityApiKey` | string | No | Required for Originality.ai | | `maxItems` | integer | No | Max items to process (1-100, default 5) | *At least one of `textContent` or `targetUrl` must be provided.* --- ### 📦 Output Schema Each dataset item contains: ```json { "type": "ai_detection", "inputType": "text", "textPreview": "The quick brown fox...", "textLength": 1500, "results": [ { "engine": "GPTZero", "status": "success", "aiProbability": 95, "humanProbability": 5, "confidence": "highly_confident", "perplexity": 12.4, "burstiness": 8.2 }, { "engine": "ZeroGPT", "status": "success", "aiProbability": 85, "humanProbability": 15 } ], "verdict": { "averageAIProbability": 90, "verdict": "LIKELY_AI", "enginesUsed": ["GPTZero", "ZeroGPT"], "enginesFailed": [] } } ```` #### Field Reference | Field | Type | Description | |-------|------|-------------| | `results[].engine` | string | Detection engine name | | `results[].status` | string | `success`, `error`, or `skipped` | | `results[].aiProbability` | number | AI generation probability (0-100) | | `results[].humanProbability` | number | Human writing probability (0-100) | | `results[].confidence` | string | Confidence level of the detection | | `results[].perplexity` | number | Text perplexity score (lower = more likely AI) | | `results[].burstiness` | number | Burstiness score (variation in sentence length) | | `verdict.verdict` | string | Combined: `LIKELY_AI`, `UNCERTAIN`, `LIKELY_HUMAN` | *** ### 🔧 Technical Details - **Runtime:** Node.js 22 (no browser needed — faster, cheaper) - **Dependencies:** apify, crawlee, axios - **API endpoints:** GPTZero v2, ZeroGPT, Originality.ai v1 - **Timeout:** 30s per API call - **Input limits:** Text truncated to 5,000 chars for API calls *** ### 💰 Pricing | Plan | Price | Description | |------|-------|-------------| | **Per result** | $0.03 | Each successful detection (across all engines) | | **Actor start** | $0.01 | One-time charge per run | *** ### ❓ FAQ **Which engines work without an API key?**\ GPTZero and ZeroGPT work without API keys. Originality.ai requires an API key. **Can I scan a full website?**\ Yes — provide a `targetUrl` and the actor will scrape the page content and analyze it. **How accurate is the detection?**\ Each engine uses different models. We recommend using multiple engines (especially GPTZero + Originality.ai for the most reliable results). **Is this faster than browser-based detectors?**\ Yes — this uses direct HTTP API calls, making it 5-10x faster than Playwright/Puppeteer-based solutions. No browser overhead. *** ### 📝 Notes - AI detection is probabilistic, not deterministic — results should be used as indicators, not proof - Detection accuracy varies by text length (500+ characters recommended) - Combining multiple engines improves reliability - Free versions of APIs may have rate limits # Actor input Schema ## `textContent` (type: `string`): Paste the text you want to check for AI-generated content. ## `targetUrl` (type: `string`): URL of a webpage to scrape and analyze for AI content. ## `sources` (type: `array`): Engines: gptzero (free), zerogpt (free), originality (API key required). ## `gptzeroApiKey` (type: `string`): Optional — higher rate limits. ## `originalityApiKey` (type: `string`): Required for Originality.ai engine. ## `maxItems` (type: `integer`): Max items per run. ## Actor input object example ```json { "textContent": "The quick brown fox jumps over the lazy dog.", "targetUrl": "https://example.com/article", "sources": [ "gptzero", "zerogpt" ], "maxItems": 5 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `outputEnvelope` (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 = { "textContent": "The quick brown fox jumps over the lazy dog.", "targetUrl": "https://example.com/article", "sources": [ "gptzero", "zerogpt" ] }; // Run the Actor and wait for it to finish const run = await client.actor("oneary/ai-text-verifier").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 = { "textContent": "The quick brown fox jumps over the lazy dog.", "targetUrl": "https://example.com/article", "sources": [ "gptzero", "zerogpt", ], } # Run the Actor and wait for it to finish run = client.actor("oneary/ai-text-verifier").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 '{ "textContent": "The quick brown fox jumps over the lazy dog.", "targetUrl": "https://example.com/article", "sources": [ "gptzero", "zerogpt" ] }' | apify call oneary/ai-text-verifier --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=oneary/ai-text-verifier", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Text Verifier -- GPTZero & ZeroGPT Checker", "description": "Check any text for AI-generated content using GPTZero, ZeroGPT, and Originality.ai. Get AI probability scores, perplexity, burstiness, and sentence-level analysis across multiple engines in one call.", "version": "1.0", "x-build-id": "bGw7FhwFjReEc1aRd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/oneary~ai-text-verifier/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-oneary-ai-text-verifier", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/oneary~ai-text-verifier/runs": { "post": { "operationId": "runs-sync-oneary-ai-text-verifier", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/oneary~ai-text-verifier/run-sync": { "post": { "operationId": "run-sync-oneary-ai-text-verifier", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "textContent": { "title": "Text to Analyze", "type": "string", "description": "Paste the text you want to check for AI-generated content." }, "targetUrl": { "title": "URL to Analyze", "type": "string", "description": "URL of a webpage to scrape and analyze for AI content." }, "sources": { "title": "Detection Engines", "type": "array", "description": "Engines: gptzero (free), zerogpt (free), originality (API key required).", "items": { "type": "string" } }, "gptzeroApiKey": { "title": "GPTZero API Key", "type": "string", "description": "Optional — higher rate limits." }, "originalityApiKey": { "title": "Originality.ai API Key", "type": "string", "description": "Required for Originality.ai engine." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 100, "type": "integer", "description": "Max items per run.", "default": 5 } } }, "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 } } } } } } } } } } ```