Turn YouTube Videos into Summaries, Transcripts, and Visual Insights

Published 1 day ago

Created by

Colleen Brady

Template description

Who is this for?

This workflow is built for anyone who works with YouTube content, whether you're:

A learner looking to understand a video’s key points
A content creator repurposing video material
A YouTube manager looking to update titles, descriptions
A social media strategist searching for the most shareable clips

Don't just ask questions about what's said. Find out what's going on in a video too.

Video Overview: https://www.youtube.com/watch?v=Ovg_KfKxnC8

What problem does this solve?

YouTube videos hold valuable insights, but watching and processing them manually takes time. This workflow automates:

Quick content extraction: Summarize key ideas without watching full videos
Visual analysis: Understand what’s happening beyond spoken words
Clip discovery: Identify the best moments for social sharing

How the workflow works

This n8n-powered automation:

Uses Google’s Gemini 1.5 Flash AI for intelligent video analysis
Provides multiple content analysis templates tailored to different needs

What makes this workflow powerful?

The easiest place to start is by requesting a summary or transcript. From there, you can refine the prompts to match your specific use case and the type of video content you’re working with.

But what's even more amazing? You can ask questions about what’s happening in the video — and get detailed insights about the people, objects, and scenes. It's jaw-dropping.

This workflow is versatile — the actions adapt based on the values set. That means you can use a single workflow to:

Extract transcripts
Generate an extended YouTube description
Write a summary blog post

You can also modify the trigger based on how you want to run the workflow — use a webhook, connect it to an event in Airtable, or leave it as-is for on-demand use. The output can then be sent anywhere: Notion, Airtable, CMS platforms, or even just stored for reference.

How to set it up

Connect your Google API key
Paste a YouTube video URL
Select an analysis method
Run the workflow and get structured results

Analysis Templates

Basic & Timestamped Transcripts: Extract spoken content
Summaries: Get concise takeaways
Visual Scene Analysis: Detect objects, settings, and people
Clip Finder: Locate shareable moments
Actionable Insights: Extract practical information

Customization Options

Modify templates to fit your needs
Connect with external platforms
Adjust formatting preferences

Advanced Configuration

This workflow is designed for use with gemini-1.5-flash. In the future, you can update the flow to work with different models or even modify the HTTP request node to define which API endpoint should be used.

It's also been designed so you can use this flow on it's own or add to a new / existing worflow.

This workflow helps you get the most out of YouTube content — quickly and efficiently.

Share Template

More AI workflow templates

AI agent chat

This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions. To use this template, you need to be on n8n version 1.50.0 or later.

n8n Team

Scrape and summarize webpages with AI

This workflow integrates both web scraping and NLP functionalities. It uses HTML parsing to extract links, HTTP requests to fetch essay content, and AI-based summarization using GPT-4o. It's an excellent example of an end-to-end automated task that is not only efficient but also provides real value by summarizing valuable content. Note that to use this template, you need to be on n8n version 1.50.0 or later.

n8n Team

Building Your First WhatsApp Chatbot

This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions. This template is intended to help introduce n8n users interested in building with WhatsApp. How it works This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot. A product brochure is imported via HTTP request node and its text contents extracted. The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot. A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out. The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool. The Agent's response is sent back to the user via the WhatsApp node. How to use Once you've setup and configured your WhatsApp account and credentials First, populate the vector store by clicking the "Test Workflow" button. Next, activate the workflow to enable the WhatsApp chatbot. Message your designated WhatsApp number and you should receive a message from the AI sales agent. Tweak datasource and behaviour as required. Requirements WhatsApp Business Account OpenAI for LLM Customising this workflow Upgrade the vector store to Qdrant for persistance and production use-cases. Handle different WhatsApp message types for a more rich and engaging experience for customers.

Jimleuk

AI agent that can scrape webpages

⚙️🛠️🚀🤖🦾 This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results). On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content. The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters: url** – an address of the page to fetch method** = full / simplified maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent Page content fetching is a multistep process: An HTTP Request mode tries to get the page content. If the page content was successfuly retrieved, a series of post-processing begin: Extract HTML BODY; content Remove all unnecessary tags to recude the page size Further eliminate external URLs and IMG scr values (based on the method query parameter) Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node). NB: You can isolate the HTTP Request part into a separate workflow. Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object. Please reach out to Eduard is you need further assistance with you n8n workflows and automations! Note that to use this template, you need to be on n8n version 1.19.4 or later.

Eduard

Telegram AI Chatbot

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.