# YouTube Video Summarizer ๐ŸŽฌ (`easyapi/youtube-video-summarizer`) Actor ๐ŸŽฅ Transform YouTube videos into comprehensive summaries! Get instant insights without watching the entire video. Perfect for researchers, students, and busy professionals seeking quick understanding of video content. - **URL**: https://apify.com/easyapi/youtube-video-summarizer.md - **Developed by:** [EasyApi](https://apify.com/easyapi) (community) - **Categories:** AI, Agents, Social media - **Stats:** 135 total users, 0 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: No ratings yet ## Pricing $1,990.00 / 1,000 per 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.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 Video Summarizer ๐ŸŽฌ Effortlessly extract meaningful summaries from YouTube videos! This powerful Actor transforms lengthy video content into concise, well-structured summaries, helping you save time and gain insights quickly. ### Features โœจ - ๐Ÿš€ Fast and efficient video content analysis - ๐Ÿ“ Comprehensive, well-structured summaries - ๐ŸŽฏ Key points and main takeaways extraction - ๐Ÿ”„ Support for various video lengths and topics - ๐ŸŒ Works with any public YouTube video - โšก Real-time processing with live progress updates - ๐Ÿ“Š Organized output in JSON format ### Use Cases ๐ŸŽฏ - ๐Ÿ“š Research and academic study - ๐Ÿ’ผ Business intelligence and market research - ๐Ÿ“ˆ Content analysis and trend monitoring - ๐ŸŽ“ Educational content review - โฑ๏ธ Time-saving video content consumption - ๐Ÿ“ฑ Social media content research - ๐Ÿง  Quick knowledge acquisition ### Output ๐Ÿ“‹ The Actor provides structured JSON output containing: - ๐Ÿ”— Original YouTube video URL - ๐Ÿ“‘ Comprehensive summary - ๐ŸŽฏ Key points and insights - ๐Ÿ“Œ Main topics covered #### Input Example A full explanation of an input example in JSON. ```json { "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw" } ```` #### Output sample The results will be wrapped into a dataset which you can always find in theย **Storage**ย tab. Here's an excerpt from the data you'd get if you apply the input parameters above: And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML. ```json [ { "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw", "result": [ { "format": "auto", "heading": "Output", "response": "Here is a summary of the anticipated AI trends for 2025:\n\n1. **Agenetic AI**: AI agents capable of reasoning, planning, and taking action are expected to improve, addressing current struggles with consistent logical reasoning and handling complex scenarios.\n\n2. **Inference Time Compute**: AI models will enhance their inference processing, allowing them to spend variable amounts of time \"thinking\" based on the complexity of the task, improving reasoning without retraining the model.\n\n3. **Very Large Models**: The size of AI models is expected to grow significantly, with some models reaching upwards of 50 trillion parameters, enhancing their capabilities.\n\n4. **Very Small Models**: Conversely, smaller models with only a few billion parameters will become more prevalent, capable of running efficiently on personal devices like laptops and phones.\n\n5. **Advanced Use Cases**: AI will be used in more sophisticated ways, such as customer service bots solving complex problems, IT systems optimizing networks, and security tools adapting to threats in real-time.\n\n6. **Near Infinite Memory**: AI systems will have expanded context windows, allowing them to retain vast amounts of information and recall past interactions, enhancing user experience.\n\n7. **Human in the Loop Augmentation**: There will be a focus on improving AI-human collaboration, ensuring that AI tools can be effectively integrated into professional workflows without requiring users to be AI experts.\n\n8. **Community Input**: The final trend is open to audience input, inviting individuals to share their thoughts on what they believe will be significant AI trends in 2025.\n\n**Conclusion**: The AI landscape in 2025 is expected to be marked by advancements in both large and small models, improved reasoning capabilities, and more sophisticated applications across various domains. The integration of AI into human workflows will be a key focus, aiming to enhance productivity and decision-making. Community engagement will continue to play a role in shaping the future of AI trends." } ] } ] ``` ### Related Actors ๐Ÿค - ๐ŸŽฅ [YouTube Video Data Scraper](https://apify.com/easyapi/youtube-video-data-scraper) - A powerful YouTube video data extractor for comprehensive metadata - ๐Ÿ“Š [YouTube Video Statistics Scraper](https://apify.com/easyapi/youtube-video-statistics-scraper) - Extract comprehensive YouTube video statistics and metadata - ๐ŸŽฌ [YouTube Video Metadata Scraper](https://apify.com/easyapi/youtube-video-metadata-scraper) - Extract rich metadata from YouTube videos - ๐Ÿ’ฌ [YouTube Comments Scraper](https://apify.com/easyapi/youtube-comments-scraper) - Scrape YouTube video comments efficiently - ๐Ÿ” [YouTube Search Scraper](https://apify.com/easyapi/youtube-search-scraper) - Effortlessly fetch search results from YouTube - ๐ŸŽฏ [YouTube Tags Extractor](https://apify.com/easyapi/youtube-tags-extractor) - Extract and analyze tags from YouTube videos - ๐Ÿ“ [YouTube Description Extractor](https://apify.com/easyapi/youtube-description-extractor) - Extract complete descriptions from YouTube videos - ๐ŸŒ [YouTube Region Restriction Checker](https://apify.com/easyapi/youtube-region-restriction-checker) - Check YouTube video regional restrictions - ๐Ÿ“บ [YouTube Trending Videos/Shorts Scraper](https://apify.com/easyapi/youtube-trending-videos-shorts-scraper) - Extract trending videos and shorts from YouTube - ๐ŸŽฎ [YouTube Gaming Trends Scraper](https://apify.com/easyapi/youtube-gaming-trends-scraper) - Scrape trending gaming videos from YouTube - ๐ŸŽฌ [YouTube Movies Trending Scraper](https://apify.com/easyapi/youtube-movies-trending-scraper) - Scrape trending movie trailers from YouTube - ๐Ÿ“ฑ [YouTube Channel Shorts Scraper](https://apify.com/easyapi/youtube-channel-shorts-scraper) - Scrape YouTube Shorts from any channel - ๐ŸŽฅ [YouTube Live Stream Scraper](https://apify.com/easyapi/youtube-live-stream-scraper) - Scrape YouTube live streams and upcoming events - ๐ŸŽฏ [YouTube Hashtag Generator](https://apify.com/easyapi/youtube-hashtag-generator) - Generate relevant hashtags for YouTube content - ๐Ÿ” [YouTube Hashtag Video & Shorts Scraper](https://apify.com/easyapi/youtube-hashtag-video-shorts-scraper) - Scrape videos and Shorts by hashtag # Actor input Schema ## `youtubeVideoUrl` (type: `string`): Enter the URL of the YouTube video you want to summarize ## `proxyConfiguration` (type: `object`): Select your proxy configuration ## Actor input object example ```json { "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw", "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw" }; // Run the Actor and wait for it to finish const run = await client.actor("easyapi/youtube-video-summarizer").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw" } # Run the Actor and wait for it to finish run = client.actor("easyapi/youtube-video-summarizer").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "youtubeVideoUrl": "https://www.youtube.com/watch?v=5zuF4Ys1eAw" }' | apify call easyapi/youtube-video-summarizer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=easyapi/youtube-video-summarizer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Video Summarizer ๐ŸŽฌ", "description": "๐ŸŽฅ Transform YouTube videos into comprehensive summaries! Get instant insights without watching the entire video. Perfect for researchers, students, and busy professionals seeking quick understanding of video content.", "version": "0.0", "x-build-id": "cd3cfP7MfgyvB00pY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/easyapi~youtube-video-summarizer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-easyapi-youtube-video-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/easyapi~youtube-video-summarizer/runs": { "post": { "operationId": "runs-sync-easyapi-youtube-video-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/easyapi~youtube-video-summarizer/run-sync": { "post": { "operationId": "run-sync-easyapi-youtube-video-summarizer", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "youtubeVideoUrl" ], "properties": { "youtubeVideoUrl": { "title": "YouTube Video URL", "type": "string", "description": "Enter the URL of the YouTube video you want to summarize", "default": "https://www.youtube.com/watch?v=5zuF4Ys1eAw" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Select your proxy configuration", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```