# Smart AI Text Rewriter & Style Transformer (`kissable_tiara/smart-ai-text-rewriter-style-transformer`) Actor Advanced text transformation engine. Rewrite and rephrase articles, news, or comments into 6 distinct stylistic dimensions using stateful AI orchestration. - **URL**: https://apify.com/kissable\_tiara/smart-ai-text-rewriter-style-transformer.md - **Developed by:** [Larysa Yarova](https://apify.com/kissable_tiara) (community) - **Categories:** AI, Other, SEO tools - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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. 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 ## Smart AI Text Rewriter & Style Transformer An advanced text processing tool driven by structured AI orchestration. This Actor allows you to rewrite, analyze, and rephrase articles, comments, or news feeds into specific stylistic dimensions while completely preserving or strategically expanding the core factual meaning. ### Features Transform any input text (up to a full A4 page) into one of the following precise modes: * **Sarcastic Rewriting:** Sharp, witty, and highly ironic commentary on the source text. * **Logical & Analytical Response:** Purely objective, dry, and fact-focused output with all emotional bias removed. * **Stoic Philosopher:** Restrained, wise reflection in the style of Marcus Aurelius or Seneca. * **Mystic Warrior (Castaneda):** Deep esoteric commentary focused on intent, energy, and the warrior's path. * **Arguments FOR/AGAINST:** Structured bullet-point extraction for rapid debate or thesis validation. ### How It Works Behind the scenes, the Actor utilizes a stateful **LangGraph pipeline** to validate context, inject adaptive system directives based on structural selection, and control inference temperature (`0.1` for strict logic, `0.8` for creative styles). ### Cost & Speed * **Ultra Fast:** Processing typically takes between 1.5 to 3 seconds. * **Highly Cost-Efficient:** Runs on lightweight infrastructure with optimal token budgeting. ### Input Configuration | Field | Type | Description | | --- | --- | --- | | `text` | String | The source article, comment, or raw text to rewrite. | | `style` | Select | The target transformation style (e.g., `sarcasm`, `logic`, `roman_philosopher`). | | `maxTokens` | Integer | Hard ceiling limit for the generated output length. | ### Output Example The results are saved directly to the Apify Default Dataset and also mirrored directly into the **OUTPUT** Key-Value store slot as a clean `text/plain` file for immediate API integration or webhook consumption. # Actor input Schema ## `text` (type: `string`): Paste the news text or comment to process. The field automatically scales and supports scrolling. ## `style` (type: `string`): Select the generation style for the AI model ## `maxTokens` (type: `integer`): Maximum number of tokens in the response (e.g., 150 tokens = ~100 words) ## Actor input object example ```json { "text": "Elon Musk stated that artificial intelligence will replace all programmers by next year.", "style": "sarcasm", "maxTokens": 300 } ```` # 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": "Elon Musk stated that artificial intelligence will replace all programmers by next year." }; // Run the Actor and wait for it to finish const run = await client.actor("kissable_tiara/smart-ai-text-rewriter-style-transformer").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": "Elon Musk stated that artificial intelligence will replace all programmers by next year." } # Run the Actor and wait for it to finish run = client.actor("kissable_tiara/smart-ai-text-rewriter-style-transformer").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": "Elon Musk stated that artificial intelligence will replace all programmers by next year." }' | apify call kissable_tiara/smart-ai-text-rewriter-style-transformer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kissable_tiara/smart-ai-text-rewriter-style-transformer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Smart AI Text Rewriter & Style Transformer", "description": "Advanced text transformation engine. Rewrite and rephrase articles, news, or comments into 6 distinct stylistic dimensions using stateful AI orchestration.", "version": "0.0", "x-build-id": "Zb5rZkfJqrGoVJg5K" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kissable_tiara~smart-ai-text-rewriter-style-transformer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kissable_tiara-smart-ai-text-rewriter-style-transformer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kissable_tiara~smart-ai-text-rewriter-style-transformer/runs": { "post": { "operationId": "runs-sync-kissable_tiara-smart-ai-text-rewriter-style-transformer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kissable_tiara~smart-ai-text-rewriter-style-transformer/run-sync": { "post": { "operationId": "run-sync-kissable_tiara-smart-ai-text-rewriter-style-transformer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "style" ], "properties": { "text": { "title": "Source text (up to 1 A4 page)", "maxLength": 4000, "type": "string", "description": "Paste the news text or comment to process. The field automatically scales and supports scrolling." }, "style": { "title": "Processing Style", "enum": [ "sarcasm", "logic", "castaneda", "roman_philosopher", "arguments_pro", "arguments_contra" ], "type": "string", "description": "Select the generation style for the AI model", "default": "sarcasm" }, "maxTokens": { "title": "Response Length Limit", "minimum": 50, "maximum": 4000, "type": "integer", "description": "Maximum number of tokens in the response (e.g., 150 tokens = ~100 words)", "default": 300 } } }, "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 } } } } } } } } } } ```