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    examples/youtube-video-tweets-extractor
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    Extract tweets from YouTube video transcript

    video-wisdom

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    VideoWisdom by ⌘ Langbase

    License: MIT

    🧠 VideoWisdom — Summarize and Analyze YouTube Videos with AI

    VideoWisdom is an AI-powered tool designed to help you manage content overload by summarizing YouTube videos, answering questions, extracting main ideas, and more. Built using multiple AI Pipes on Langbase, VideoWisdom works with 30+ LLMs (like OpenAI, Gemini, Mistral, Llama, etc.), and any data (10M+ context with Memory sets).

    Check out the live demo here.

    Features

    • 🧠 VideoWisdom — Transform YouTube videos into insights in just a few minutes with AI!
    • 💬 YouTube Videos Q/A – Get instant answers from any YouTube video.
    • 📝 Summarize YouTube Video – Get concise summaries of YouTube videos.
    • 🧩 Main Ideas Extractor – Extract core concepts from YouTube videos.
    • 💡 List Interesting Facts – Highlight intriguing facts from videos.
    • 🎯 Wow Moments Extractor – Find and review impactful moments in videos.
    • 🐦 Video Tweets Extractor – Create tweet ideas from video content.
    • 🎥 Video Recommendations Extractor – Extract and view video recommendations.
    • 🗣️ List Quotes from Video – Extract notable quotes from YouTube videos.
    • 🚀 AI-Powered Insights — Leverage the power of AI to generate insights from videos
    • ⚡ Real-time Processing — Experience near-instant responses with streaming

    Learn more

    1. Explore the VideoWisdom Pipes on ⌘ Langbase.
    2. Check out the source code on GitHub for this project.
    3. Go through the Documentation: Pipe Quick Start.
    4. Learn more about Pipes & Memory features on ⌘ Langbase.

    Get started

    Let's get started with the project:

    Create a free personal account on Langbase.com and verify your email address.

    1. Fork the the following Pipes on ⌘ Langbase.

    2. Go to the API tab of each Pipe to copy the Pipe's API key (to be used on server-side only).

    3. Clone the respository to your local machine using the following command:

    sh
    1git clone https://github.com/LangbaseInc/langbase-examples
    1. cd into the project directory in examples folder:
    sh
    1    cd langbase-examples/examples/video-wisdom
    1. Duplicate the .env.local.example file in this project and rename it to .env.local.
    2. Add the following environment variables:
    sh
    1# Fork https://langbase.com/examples/youtube-video-summarizer
2# Replace `LB_SUMMARIZE_PIPE_KEY` with your API from the forked Pipe
3LB_SUMMARIZE_PIPE_KEY=""
4# Fork https://langbase.com/examples/you-tube-videos-qn-a
5# Replace `LB_GENERATE_PIPE_KEY` with your API from the forked Pipe
6LB_GENERATE_PIPE_KEY=""
7# Fork https://langbase.com/examples/youtube-video-main-ideas-extractor
8# Replace `LB_MAIN_IDEAS_PIPE_KEY` with your API from the forked Pipe
9LB_MAIN_IDEAS_PIPE_KEY=""
10# Fork https://langbase.com/examples/youtube-video-interesting-facts-extractor
11# Replace `LB_FACTS_PIPE_KEY` with your API from the forked Pipe
12LB_FACTS_PIPE_KEY=""
13# Fork https://langbase.com/examples/youtube-video-wow-moments
14# Replace `LB_WOW_PIPE_KEY` with your API from the forked Pipe
15LB_WOW_PIPE_KEY=""
16# Fork https://langbase.com/examples/youtube-video-tweets-extractor
17# Replace `LB_TWEETS_PIPE_KEY` with your API from the forked Pipe
18LB_TWEETS_PIPE_KEY=""
19# Fork https://langbase.com/examples/youtube-video-recommendations-extractor
20# Replace `LB_RECOMMENDATION_PIPE_KEY` with your API from the forked Pipe
21LB_RECOMMENDATION_PIPE_KEY=""
22# Fork https://langbase.com/examples/youtube-video-quotes-extractor
23# Replace `LB_QUOTES_PIPE_KEY` with your API from the forked Pipe
24LB_QUOTES_PIPE_KEY=""
25
    1. Now execute the following commands in your terminal to run the project:
    sh
    1# Install the dependencies using the following command:
2npm install
3
4# OR if you are using npm, run the following command:
5npm install
6
7# Run the project using the following command:
8npm run dev

    Your app template should now be running on localhost:3000.

    NOTE: This is a Next.js project, so you can build and deploy it to any platform of your choice, like Vercel, Netlify, Cloudflare, etc.

    Authors

    This project is created by Langbase team members, with contributions from:

    Built by ⌘ Langbase.com — Ship composable AI pipe agents with hyper-personalized memory (RAG)!