# AI Based Questions Generator (`akash9078/ai-questions-generator`) Actor Generate questions from any given text using AI. Supports multiple question types including MCQ, true/false, fill-in-the-blank, and open-ended questions. - **URL**: https://apify.com/akash9078/ai-questions-generator.md - **Developed by:** [Akash Kumar Naik](https://apify.com/akash9078) (community) - **Categories:** AI, Developer tools, Other - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / 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.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 Based Questions Generator Generate educational questions from any text using NVIDIA's AI models. Perfect for educators, content creators, and e-learning platforms. ### What It Does - Generates **multiple question types**: MCQ, True/False, Fill-in-the-blank, Open-ended - Supports **3 difficulty levels**: Easy, Medium, Hard - Uses **NVIDIA's API** for high-quality AI-generated questions - **Pay Per Event** pricing - only pay for questions generated ### Input ```json { "text": "The water cycle describes the continuous movement of water on, above, and below the surface of the Earth. Water undergoes evaporation, condensation, and precipitation...", "questionType": "mixed", "numQuestions": 5, "difficulty": "medium" } ```` **Parameters:** - `text` (required): The source text to generate questions from (min 50 characters) - `questionType`: Type of questions - "mcq", "true\_false", "fill\_blank", "open\_ended", or "mixed" (default: "mixed") - `numQuestions`: Number of questions to generate, 1-50 (default: 5) - `difficulty`: Difficulty level - "easy", "medium", or "hard" (default: "medium") ### Output ```json { "source_text_preview": "The water cycle describes the continuous...", "question_type": "mixed", "difficulty": "medium", "num_questions_requested": 5, "num_questions_generated": 5, "questions": [ { "type": "mcq", "question": "What is the process called when water changes from liquid to vapor?", "options": ["A. Condensation", "B. Evaporation", "C. Precipitation", "D. Transpiration"], "correct_answer": "B. Evaporation", "explanation": "Evaporation is the process where water changes from liquid to vapor due to heat energy." } ] } ``` ### Environment Variables Configure via Apify console: - `NVIDIA_API_KEY`: Your NVIDIA API key (required) - `NVIDIA_BASE_URL`: API endpoint (default: "https://integrate.api.nvidia.com/v1") - `NVIDIA_MODEL`: Model to use (default: "openai/gpt-oss-120b") - `NVIDIA_TEMPERATURE`: Sampling temperature 0-2 (default: 1.0) - `NVIDIA_MAX_TOKENS`: Max response tokens (default: 16384) ### Use Cases - 📚 **Teachers**: Create quiz questions from educational content - 📝 **Content Creators**: Generate practice questions for articles - 🎓 **E-Learning**: Auto-generate assessments from course materials - 📖 **Researchers**: Create knowledge checks from papers ### Pricing - **Actor Start**: $0.00005 - **Per Question**: $0.005 ### Tips - Provide longer text (300+ words) for more diverse questions - Use "mixed" question type for varied assessments - Set difficulty based on your target audience - Questions are charged individually - only pay for what you generate # Actor input Schema ## `text` (type: `string`): The text to generate questions from. ## `questionType` (type: `string`): Type of questions to generate. ## `numQuestions` (type: `integer`): Number of questions to generate. ## `difficulty` (type: `string`): Difficulty level of questions. ## Actor input object example ```json { "text": "The water cycle describes the continuous movement of water on, above, and below the surface of the Earth. Water undergoes evaporation, condensation, and precipitation. During evaporation, water turns from liquid to vapor and rises into the atmosphere. Condensation occurs when water vapor cools and forms clouds. Precipitation happens when water falls from clouds as rain, snow, sleet, or hail.", "questionType": "mixed", "numQuestions": 5, "difficulty": "medium" } ``` # 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 = { "text": "The water cycle describes the continuous movement of water on, above, and below the surface of the Earth. Water undergoes evaporation, condensation, and precipitation. During evaporation, water turns from liquid to vapor and rises into the atmosphere. Condensation occurs when water vapor cools and forms clouds. Precipitation happens when water falls from clouds as rain, snow, sleet, or hail.", "questionType": "mixed", "numQuestions": 5, "difficulty": "medium" }; // Run the Actor and wait for it to finish const run = await client.actor("akash9078/ai-questions-generator").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 = { "text": "The water cycle describes the continuous movement of water on, above, and below the surface of the Earth. Water undergoes evaporation, condensation, and precipitation. During evaporation, water turns from liquid to vapor and rises into the atmosphere. Condensation occurs when water vapor cools and forms clouds. Precipitation happens when water falls from clouds as rain, snow, sleet, or hail.", "questionType": "mixed", "numQuestions": 5, "difficulty": "medium", } # Run the Actor and wait for it to finish run = client.actor("akash9078/ai-questions-generator").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 '{ "text": "The water cycle describes the continuous movement of water on, above, and below the surface of the Earth. Water undergoes evaporation, condensation, and precipitation. During evaporation, water turns from liquid to vapor and rises into the atmosphere. Condensation occurs when water vapor cools and forms clouds. Precipitation happens when water falls from clouds as rain, snow, sleet, or hail.", "questionType": "mixed", "numQuestions": 5, "difficulty": "medium" }' | apify call akash9078/ai-questions-generator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=akash9078/ai-questions-generator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Based Questions Generator", "description": "Generate questions from any given text using AI. Supports multiple question types including MCQ, true/false, fill-in-the-blank, and open-ended questions.", "version": "0.1", "x-build-id": "kF8Q2Umt2aSocuVC5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/akash9078~ai-questions-generator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-akash9078-ai-questions-generator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/akash9078~ai-questions-generator/runs": { "post": { "operationId": "runs-sync-akash9078-ai-questions-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/akash9078~ai-questions-generator/run-sync": { "post": { "operationId": "run-sync-akash9078-ai-questions-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "text", "questionType", "numQuestions", "difficulty" ], "properties": { "text": { "title": "Input Text", "type": "string", "description": "The text to generate questions from." }, "questionType": { "title": "Question Type", "enum": [ "mcq", "true_false", "fill_blank", "open_ended", "mixed" ], "type": "string", "description": "Type of questions to generate.", "default": "mixed" }, "numQuestions": { "title": "Number of Questions", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of questions to generate.", "default": 5 }, "difficulty": { "title": "Difficulty Level", "enum": [ "easy", "medium", "hard" ], "type": "string", "description": "Difficulty level of questions.", "default": "medium" } } }, "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 } } } } } } } } } } ```