Original Summary

Meet TubeExtract . It's a service for extracting anything you want from a Youtube video. ( for dataset see below ) https://tubeextract.dev/ After thinking about how can i make projects that is related to contents of Youtube videos i saw same limit: Extraction. Using big LLM models were the only way to extract but it had extreme costs. So i built TubeExtract which uses Specialized NER models to extract data from youtube videos. With this service you will be able to - Get answers to what, who, where etc. questions about videos. - Get insights about events, places, people in specific creator's videos - Analyze trends - Get responses in JSON All by extracting entities you define with your schema But How it works? You define schema Either use web UI or API post videos in chunks with every chunk having up to 200 videos this will be a single "job" If using Web UI you will see results in each job's tab if using API just send a GET request to URL containing job ID You can optionally set-up a webhook to get alerted when a job finishes (A typical 20 minute video gets processed in about 30 seconds) Also a FREE Dataset about visited restaurants in food videos to let you see what's possible with this product: https://tubeextract.dev/blog/youtube-restaurant-visits-2026-09   submitted by   /u/timurcagri [link]   [comments]

  • 情报分类：工作与职业机会
  • 分类依据：内容涉及招聘、求职或职业发展
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/29 02:28:14