HTTP Request node
+6

API that extracts engaging moments from YouTube videos

Published 8 months ago

Created by

maxtkacz
Max T

Categories

Template description

How it works

This template takes a YouTube video ID and identifies potentially engaging moments based on the intensity of specific timestamps πŸ‘‡

Screenshot 20240228 at 15.51.02.png

Ideal for vloggers and YouTube content creators, it serves as a foundation for various automations to streamline content calendars or highlight popular moments in your videos. You can leverage it for:

  • Automatic processes to analyze YouTube videos and create sizzle reels or clips for social media, particularly effective for microcontent strategies like those endorsed by Gary Vee.
  • Instant alerts via Slack, Telegram, Email, or WhatsApp when significant moments occur in your videos.
  • Utilizing transcripts of these moments with AI to refine content ideas or brainstorm chatbots in your editorial workflow.

Example response from the Workflow-as-an-API

A GET request to {your instance URL}/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy returns πŸ‘‡

successresponse.png

The workflow generates multiple moments; the screenshot above shows a truncated version.

Not all videos contain timestamp intensity data, the workflow handles this case as well πŸ‘‡
errorresponse.png

How to use

  1. Import the template into your n8n workspace or self-hosted instance, then activate the workflow.
  2. Open the Webhook trigger node and copy the Production URL.
  3. In a web browser or any tool capable of consuming HTTP Requests (e.g., native code, Bubble app, n8n workflow, another automation tool, Postman, etc.), pass along the URL parameter ?ytID={youtube video ID} when invoking the API endpoint.

Your URL should resemble something like https://acme.app.n8n.cloud/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy.

Keep in mind
This workflow relies on an unofficial YouTube API graciously hosted for free by the folks at lemnoslife.com. It's not recommended for high-volume production usecases.

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