# 🎬 YouTube AI Summarizer — Transcripts & Summaries (`nexgendata/youtube-ai-summarizer`) Actor Get AI summaries of any YouTube video. Extract transcripts, generate summaries in brief, detailed, or bullet-point format. - **URL**: https://apify.com/nexgendata/youtube-ai-summarizer.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** AI, Videos - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## YouTube AI Summarizer Automatically generate AI-powered summaries of YouTube videos using OpenAI's GPT models. ### Features - **Transcript Extraction**: Automatically fetches transcripts from YouTube videos - **AI Summarization**: Uses OpenAI API to generate intelligent summaries - **Multiple Summary Styles**: Choose from brief, detailed, bullet points, or key takeaways - **Metadata Extraction**: Gets video title, channel name, and other details - **Custom Prompts**: Add your own instructions for summarization - **Multi-language Support**: Supports transcripts in various languages ### Input The actor accepts the following input: ```json { "youtube_urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "openai_api_key": "sk-...", "summary_style": "brief", "custom_prompt": null, "language": "en" } ```` #### Input Parameters - **youtube\_urls** (array of strings, required): Array of YouTube video URLs to summarize - **openai\_api\_key** (string, required): Your OpenAI API key - **summary\_style** (string, optional): Style of summary - `brief`, `detailed`, `bullet_points`, or `key_takeaways`. Default: `brief` - **custom\_prompt** (string, optional): Custom instructions for summarization - **language** (string, optional): Language code for transcript (e.g., `en`, `es`, `fr`). Default: `en` ### Output The actor produces a dataset with the following fields for each video: ```json { "video_id": "dQw4w9WgXcQ", "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "title": "Video Title", "channel": "Channel Name", "transcript": "Full video transcript...", "transcript_length": 5000, "summary": "AI-generated summary...", "key_points": "Extracted key points...", "summary_style": "brief", "language": "en", "status": "success" } ``` ### Requirements - YouTube video must have a transcript available - Valid OpenAI API key with gpt-3.5-turbo or gpt-4 access - YouTube URL must be in a standard format (youtube.com/watch?v=ID or youtu.be/ID) ### How It Works 1. Parses each YouTube URL to extract the video ID 2. Fetches video metadata (title, channel) from YouTube 3. Retrieves the video transcript using YouTube's transcript API 4. Sends the transcript to OpenAI for summarization based on selected style 5. Extracts key points from the transcript 6. Returns structured data with all information ### Example Use Cases - **Content Research**: Quickly summarize long educational videos - **Meeting Notes**: Get summaries of recorded webinars and presentations - **Content Curation**: Batch process multiple videos for content analysis - **Accessibility**: Generate text summaries for users who prefer reading ### Pricing - **Per actor run**: $0.01 - **Per video processed**: $0.02 OpenAI API costs are separate and depend on your OpenAI account tier. ### Rate Limits - YouTube has no official rate limits for transcript API - OpenAI rate limits apply based on your account tier - Recommended: Process no more than 10 videos per run for reliable performance ### Support For issues or feature requests, please contact the actor developer. # Actor input Schema ## `youtube_urls` (type: `array`): Array of YouTube video URLs to summarize ## `openai_api_key` (type: `string`): Your OpenAI API key (starts with sk-) ## `summary_style` (type: `string`): Style of summary ## `custom_prompt` (type: `string`): Custom instructions ## `language` (type: `string`): Language code ## Actor input object example ```json { "youtube_urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "summary_style": "brief", "language": "en" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "youtube_urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "summary_style": "brief", "language": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/youtube-ai-summarizer").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "youtube_urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"], "summary_style": "brief", "language": "en", } # Run the Actor and wait for it to finish run = client.actor("nexgendata/youtube-ai-summarizer").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 '{ "youtube_urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "summary_style": "brief", "language": "en" }' | apify call nexgendata/youtube-ai-summarizer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/youtube-ai-summarizer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🎬 YouTube AI Summarizer — Transcripts & Summaries", "description": "Get AI summaries of any YouTube video. Extract transcripts, generate summaries in brief, detailed, or bullet-point format.", "version": "0.0", "x-build-id": "OiuS6EvnqDjKmBMCY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~youtube-ai-summarizer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-youtube-ai-summarizer", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~youtube-ai-summarizer/runs": { "post": { "operationId": "runs-sync-nexgendata-youtube-ai-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~youtube-ai-summarizer/run-sync": { "post": { "operationId": "run-sync-nexgendata-youtube-ai-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "youtube_urls", "openai_api_key" ], "properties": { "youtube_urls": { "title": "YouTube URLs", "type": "array", "description": "Array of YouTube video URLs to summarize", "items": { "type": "string" } }, "openai_api_key": { "title": "OpenAI API Key", "type": "string", "description": "Your OpenAI API key (starts with sk-)" }, "summary_style": { "title": "Summary Style", "enum": [ "brief", "detailed", "bullet_points", "key_takeaways" ], "type": "string", "description": "Style of summary" }, "custom_prompt": { "title": "Custom Prompt", "type": "string", "description": "Custom instructions" }, "language": { "title": "Language", "type": "string", "description": "Language code" } } }, "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 } } } } } } } } } } ```