# AI Faceless Video Generator — Reddit/Story to Short (`dami_studio/ai-faceless-short-generator`) Actor Turn a subreddit, a story, or a topic into a finished faceless short video — script, AI voiceover, cinematic scene images with motion, and word-synced captions, fully automated. For TikTok, Reels, and YouTube Shorts. The complete pipeline in one actor. - **URL**: https://apify.com/dami\_studio/ai-faceless-short-generator.md - **Developed by:** [Dami's Studio](https://apify.com/dami_studio) (community) - **Categories:** Videos, AI, For creators - **Stats:** 2 total users, 0 monthly users, 60.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $390.00 / 1,000 video generateds 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 Faceless Video Generator Give it a subreddit, a story, or a topic and it returns a finished faceless short: an AI-written script, an AI voiceover, cinematic scene images with ken-burns motion, and word-synced captions burned in. It runs the whole pipeline in one go, so the output is a ready-to-post vertical video for TikTok, Reels, or YouTube Shorts. Built for people churning out faceless content who don't want to stitch five tools together by hand. ### How it works It pulls the source text (top Reddit post via RSS, or your own story/topic), rewrites it into a tight retention script, generates the voiceover with OpenAI TTS, transcribes that audio back to get per-word timings, generates one scene image per ~6 seconds with `gpt-image-1`, then animates the stills with ffmpeg ken-burns and burns the captions over the top. ### Input Nothing is strictly required, but you do need to give it a source (one of `subreddit`, `story`, or `topic`) and an OpenAI key. `subreddit` is prefilled with `tifu` so a run with just a key will produce something. | Field | Required | Notes | |---|---|---| | `subreddit` | one of source | Pulls the top post with enough body text, e.g. `tifu`, `AmItheAsshole`, `nosleep`. Prefilled `tifu`. | | `story` | one of source | Your own text to turn into a video. Overrides `subreddit`. | | `topic` | one of source | A topic to write about from scratch. Overrides `subreddit`. | | `openaiApiKey` | yes in practice | Bring your own key. Used for script, TTS, transcription, and images. Kept private. | | `tone` | no | Script tone: `dramatic` (default), `casual`, `funny`, `emotional`, `educational`, `hype`. | | `voice` | no | OpenAI TTS voice: `onyx` (default), `alloy`, `echo`, `fable`, `nova`, `shimmer`. | | `aspectRatio` | no | `9:16` (default), `16:9`, or `1:1`. | | `captionPreset` | no | Burned caption style: `karaoke` (default), `hormozi`, `beast`, `tiktok`, `clean`. | | `targetSeconds` | no | Approximate length. Default 50. The scene count scales with the final voiceover duration. | | `imageQuality` | no | `gpt-image-1` quality: `low`, `medium`, `high` (default). Drives most of your OpenAI cost. | | `style` | no | Art direction for the scene images. Defaults to a cinematic, moody look. | | `characters` | no | Recurring-character description to keep faces and outfits consistent across scenes. | | `sort` / `time` | no | Reddit sort (`top`/`hot`/`new`/`rising`) and time window for `top`. | ### Output One dataset item per run with the finished MP4 and the metadata around it. The video and the raw voiceover MP3 are written to the run's key-value store. Key fields: `videoUrl` and `videoKey` (the MP4), `title`, `hook` and `altHooks` (extra hook options to A/B), `script`, `voice`, `scenes`, `aspectRatio`, `durationSeconds`, and `source` (where the story came from). ### Example ```json { "subreddit": "tifu", "tone": "dramatic", "voice": "onyx", "captionPreset": "hormozi", "aspectRatio": "9:16", "targetSeconds": 50, "openaiApiKey": "sk-..." } ```` ### Pricing $0.39 per video, pay per result, no subscription. OpenAI usage (script, TTS, transcription, images) is billed separately on your own key. ### Notes Reddit serves the public RSS feed, which works for top posts but not comment threads, so this reads the post body only. `imageQuality: high` is the main lever on OpenAI cost and run time. If your `story` or `topic` is short, the script model pads to roughly `targetSeconds`, which can read thin; feed it more source text for better results. # Actor input Schema ## `subreddit` (type: `string`): Pull the top story from this subreddit (e.g. tifu, AmItheAsshole, nosleep). Leave empty to use 'story' or 'topic'. ## `story` (type: `string`): Your own story/script to turn into a video (overrides subreddit). ## `topic` (type: `string`): A topic to write a video about (overrides subreddit). ## `sort` (type: `string`): Sort for the subreddit source. ## `time` (type: `string`): Time window for top. ## `tone` (type: `string`): Script tone. ## `voice` (type: `string`): AI voiceover voice. ## `aspectRatio` (type: `string`): Video shape. ## `style` (type: `string`): Art style for the scene images. ## `characters` (type: `string`): Recurring-character description for visual consistency. ## `captionPreset` (type: `string`): Burned caption style. ## `targetSeconds` (type: `integer`): Approximate length of the short. ## `imageQuality` (type: `string`): gpt-image-1 quality (affects cost/speed). ## `openaiApiKey` (type: `string`): Your OpenAI key — used for script, TTS, transcription, and images. Kept private. ## `baseUrl` (type: `string`): OpenAI-compatible base URL. Default https://api.openai.com/v1. ## Actor input object example ```json { "subreddit": "tifu", "sort": "top", "time": "week", "tone": "dramatic", "voice": "onyx", "aspectRatio": "9:16", "style": "cinematic, moody, highly detailed, dramatic lighting", "captionPreset": "karaoke", "targetSeconds": 50, "imageQuality": "high" } ``` # Actor output Schema ## `results` (type: `string`): Result rows / metadata are stored in the default dataset (one row per item). ## `files` (type: `string`): Generated media/files (video, audio, images, captions) are stored in the default key-value store. # 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 = { "subreddit": "tifu" }; // Run the Actor and wait for it to finish const run = await client.actor("dami_studio/ai-faceless-short-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 = { "subreddit": "tifu" } # Run the Actor and wait for it to finish run = client.actor("dami_studio/ai-faceless-short-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 '{ "subreddit": "tifu" }' | apify call dami_studio/ai-faceless-short-generator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dami_studio/ai-faceless-short-generator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Faceless Video Generator — Reddit/Story to Short", "description": "Turn a subreddit, a story, or a topic into a finished faceless short video — script, AI voiceover, cinematic scene images with motion, and word-synced captions, fully automated. For TikTok, Reels, and YouTube Shorts. The complete pipeline in one actor.", "version": "0.1", "x-build-id": "rxDQykkzTJRJLBSCn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dami_studio~ai-faceless-short-generator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dami_studio-ai-faceless-short-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dami_studio~ai-faceless-short-generator/runs": { "post": { "operationId": "runs-sync-dami_studio-ai-faceless-short-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dami_studio~ai-faceless-short-generator/run-sync": { "post": { "operationId": "run-sync-dami_studio-ai-faceless-short-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "subreddit": { "title": "Subreddit (source)", "type": "string", "description": "Pull the top story from this subreddit (e.g. tifu, AmItheAsshole, nosleep). Leave empty to use 'story' or 'topic'." }, "story": { "title": "Story text", "type": "string", "description": "Your own story/script to turn into a video (overrides subreddit)." }, "topic": { "title": "Topic", "type": "string", "description": "A topic to write a video about (overrides subreddit)." }, "sort": { "title": "Reddit sort", "enum": [ "top", "hot", "new", "rising" ], "type": "string", "description": "Sort for the subreddit source.", "default": "top" }, "time": { "title": "Reddit time", "enum": [ "day", "week", "month", "year", "all" ], "type": "string", "description": "Time window for top.", "default": "week" }, "tone": { "title": "Tone", "enum": [ "dramatic", "casual", "funny", "emotional", "educational", "hype" ], "type": "string", "description": "Script tone.", "default": "dramatic" }, "voice": { "title": "Voice", "enum": [ "alloy", "echo", "fable", "onyx", "nova", "shimmer" ], "type": "string", "description": "AI voiceover voice.", "default": "onyx" }, "aspectRatio": { "title": "Aspect ratio", "enum": [ "9:16", "16:9", "1:1" ], "type": "string", "description": "Video shape.", "default": "9:16" }, "style": { "title": "Visual style", "type": "string", "description": "Art style for the scene images.", "default": "cinematic, moody, highly detailed, dramatic lighting" }, "characters": { "title": "Character notes (optional)", "type": "string", "description": "Recurring-character description for visual consistency." }, "captionPreset": { "title": "Caption style", "enum": [ "karaoke", "hormozi", "beast", "tiktok", "clean" ], "type": "string", "description": "Burned caption style.", "default": "karaoke" }, "targetSeconds": { "title": "Target length (seconds)", "type": "integer", "description": "Approximate length of the short.", "default": 50 }, "imageQuality": { "title": "Image quality", "enum": [ "low", "medium", "high" ], "type": "string", "description": "gpt-image-1 quality (affects cost/speed).", "default": "high" }, "openaiApiKey": { "title": "OpenAI API key (BYO)", "type": "string", "description": "Your OpenAI key — used for script, TTS, transcription, and images. Kept private." }, "baseUrl": { "title": "API base URL (advanced)", "type": "string", "description": "OpenAI-compatible base URL. Default https://api.openai.com/v1." } } }, "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 } } } } } } } } } } ```