# AI Infographic Generator (`c4m3r0n808/ai-infographic-generator`) Actor Go from a topic to a production-ready infographic brief in one step. Assembles a detailed prompt across 441 layout-and-style combinations and can render the image with your FLUX key. Built for marketers and creators. - **URL**: https://apify.com/c4m3r0n808/ai-infographic-generator.md - **Developed by:** [Cameron Stanley](https://apify.com/c4m3r0n808) (community) - **Categories:** Other, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $100.00 / 1,000 prompt builts 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 Infographic Generator Turn any topic into a structured, production-ready infographic prompt — **441 combinations** (21 layouts × 21 styles) — and optionally render it. ### Features - **441 design combinations** from a curated layout + style library. - Assembles a detailed, B2B-grade prompt (hook, structure, visual direction) — not a one-liner. - **Three modes**: - `prompt` — just the prompt (no rendering, no key). - `image` — render only. - `both` — prompt + rendered image. - Image rendering uses **your own FAL key** (FLUX). We never see or bill your key. - Output in `landscape` / `portrait` / `square` aspect ratios. ### Input | Field | Type | Notes | |-------|------|-------| | `topic` | string | **Required.** The subject. | | `content` | string | Bullet points / data to include. | | `layout` | string | One of 21 layouts (default `bento-grid`). | | `style` | string | One of 21 styles (default `craft-handmade`). | | `aspect` | string | `landscape` / `portrait` / `square`. | | `falKey` | string | *Optional.* Needed only for image mode. | | `mode` | string | `prompt` / `image` / `both`. | ### Pricing Pay per prompt built — **$0.10**. Prompt-only mode needs no key. # Actor input Schema ## `topic` (type: `string`): Short title/subject for the infographic. ## `content` (type: `string`): Detailed text/points to visualize. Defaults to topic if omitted. ## `layout` (type: `string`): One of 21 layouts (bento-grid, linear-progression, funnel, dashboard, ...). ## `style` (type: `string`): One of 21 styles (craft-handmade, cyberpunk-neon, corporate-memphis, ...). ## `aspect` (type: `string`): Aspect input. ## `language` (type: `string`): Language input. ## `falKey` (type: `string`): Optional. If provided, renders the image via FLUX. If omitted, returns the assembled prompt only. ## Actor input object example ```json { "topic": "Climate Change", "layout": "bento-grid", "style": "craft-handmade", "aspect": "landscape", "language": "en" } ```` # Actor output Schema ## `topic` (type: `string`): No description ## `layout` (type: `string`): No description ## `style` (type: `string`): No description ## `prompt` (type: `string`): No description ## `image_url` (type: `string`): No description ## `image_error` (type: `string`): No description ## `error` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "topic": "Climate Change" }; // Run the Actor and wait for it to finish const run = await client.actor("c4m3r0n808/ai-infographic-generator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "topic": "Climate Change" } # Run the Actor and wait for it to finish run = client.actor("c4m3r0n808/ai-infographic-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 '{ "topic": "Climate Change" }' | apify call c4m3r0n808/ai-infographic-generator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=c4m3r0n808/ai-infographic-generator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Infographic Generator", "description": "Go from a topic to a production-ready infographic brief in one step. Assembles a detailed prompt across 441 layout-and-style combinations and can render the image with your FLUX key. Built for marketers and creators.", "version": "1.0", "x-build-id": "XzyrHEwXc6f5aaj93" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/c4m3r0n808~ai-infographic-generator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-c4m3r0n808-ai-infographic-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/c4m3r0n808~ai-infographic-generator/runs": { "post": { "operationId": "runs-sync-c4m3r0n808-ai-infographic-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/c4m3r0n808~ai-infographic-generator/run-sync": { "post": { "operationId": "run-sync-c4m3r0n808-ai-infographic-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "topic" ], "properties": { "topic": { "title": "Topic", "type": "string", "description": "Short title/subject for the infographic.", "default": "Benefits of daily hydration" }, "content": { "title": "Content", "type": "string", "description": "Detailed text/points to visualize. Defaults to topic if omitted." }, "layout": { "title": "Layout", "type": "string", "description": "One of 21 layouts (bento-grid, linear-progression, funnel, dashboard, ...).", "default": "bento-grid" }, "style": { "title": "Style", "type": "string", "description": "One of 21 styles (craft-handmade, cyberpunk-neon, corporate-memphis, ...).", "default": "craft-handmade" }, "aspect": { "title": "Aspect", "enum": [ "landscape", "portrait", "square" ], "type": "string", "description": "Aspect input.", "default": "landscape" }, "language": { "title": "Language", "type": "string", "description": "Language input.", "default": "en" }, "falKey": { "title": "FAL API Key", "type": "string", "description": "Optional. If provided, renders the image via FLUX. If omitted, returns the assembled prompt only." } } }, "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 } } } } } } } } } } ```