Sticky Note Automate

Sticky Note Automate simplifies video summarization by integrating YouTube video transcripts with LangChain, allowing users to generate concise summaries and relevant questions effortlessly. Triggered manually, this workflow enhances productivity by automating content extraction and summarization, making information more accessible and actionable.

7/8/2025
6 nodes
Medium
manualmediumsticky notelangchain
Categories:
Manual TriggeredMedium Workflow
Integrations:
Sticky NoteLangChain

Target Audience

Who should use this workflow


- Content Creators: Individuals or teams who create video content and need to summarize their videos effectively.
- Educators: Teachers and trainers who want to provide concise summaries of educational videos for their students.
- Marketers: Professionals looking to summarize promotional videos and create engaging content for social media.
- Researchers: Those who need to distill information from video sources into concise, usable formats.
- Developers: Programmers who want to integrate video summarization into their applications using LangChain and n8n.

Problem Solved

What problem does this workflow solve


This workflow automates the process of summarizing YouTube videos, addressing the challenge of extracting key information from lengthy video content. It allows users to quickly obtain a textual summary along with example questions, enhancing content accessibility and understanding. The integration with LangChain facilitates advanced processing, ensuring high-quality outputs that are useful for various applications, such as Q&A bots or educational resources.

Workflow Steps

Detailed explanation of the workflow process


1. Manual Trigger: The workflow begins with a manual trigger, allowing users to execute the workflow when they are ready.
2. Set YouTube Video ID: The workflow sets a specific YouTube video ID (OsMVtuuwOXc) to target the video for summarization.
3. LangChain Code Execution: The core of the workflow is the LangChain code node, which:
- Loads the video transcript using the SearchApiLoader from LangChain.
- Splits the transcript into manageable chunks for summarization.
- Utilizes an AI language model (OpenAI's GPT) to generate a summary and a list of example questions based on the transcript.
4. Output: The final output is a structured summary of the video along with potential questions users might ask, enhancing engagement and comprehension.

Customization Guide

How users can customize and adapt this workflow


- Change Video ID: Users can modify the videoId value in the 'Set YouTube video ID' node to target different YouTube videos.
- API Key: Replace in the LangChain code with a valid API key from searchapi.io to enable the video transcript fetching functionality.
- Adjust Summarization Parameters: Users can tweak the parameters in the TokenTextSplitter to change how the transcript is chunked, or adjust the prompts used in the summarization process to tailor the output to their specific needs.
- Integrate Additional Nodes: Users can add more nodes to the workflow to further process the output, such as sending summaries to email, integrating with project management tools, or posting summaries on social media.