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A simple demonstration of how to use existing AI tools to "chat with youtube videos".

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🌟 Chat With YouTube Videos 🌟

How I made a Chatbot to speak with YouTube Videos

📺 For a visual walk-through and more insights, don't forget to watch the video: Watch Now!

Introduction 🚀

Hey there, awesome coders! 🎉 I'm super thrilled to introduce our latest Python project that's going to blow your minds! 🤯 Imagine chatting with YouTube videos - yes, you heard that right! 📹💬 We're merging the power of Large Language Models (LLMs) with the magic of YouTube, allowing you to interact with video content like never before. 🌈✨

What's Cooking? 🍳

Our project uses a mix of cool tech to make this possible:

  • Ollama / HuggingFace LLMs: We're harnessing these AI giants to understand and respond to the content of YouTube videos. 🧠🤖
  • Pythonic YouTube Transcribe Package: This nifty tool transcribes YouTube videos, turning spoken words into text. 🎙️➡️📝
  • LiteLLM: This is our secret sauce for managing LLM completion queries, ensuring smooth and intelligent responses. 🌟🔧

How It Works? 🧐

  1. Transcribe: First, our Python script transcribes the YouTube video. 📼🔠
  2. Contextualize: The transcribed text is then used to provide context to our LLMs. 📖🌍
  3. Chat Away: You ask questions or make comments, and our LLMs, fueled by the video's context, respond as if you're having a conversation with the video itself! 🗨️💬

Features 📚

  • Interactive Video Experience: Feel like you're having a real conversation with your favorite YouTube videos. 🎥👥
  • Diverse LLM Support: Thanks to Ollama and HuggingFace, our responses are smart, relevant, and incredibly engaging. 🧠✨
  • Easy-to-Use: Simple setup, user-friendly interface. Perfect for both beginners and pros! 🙌💻

Installation 🛠️

pip install -r requirements.txt

A single command and you're all set to go! 🚀

Configuration ⚙️

Head over to config/ai_models.json. You can add / remove existing configuration as you wish, just make sure that the URLs that you're using match the expectations. Example config for a local ollama deployment:

{
  "Ollama Mistral": {
    "model": "ollama/mistral",
    "base_api": "http://localhost:11434",
    "resolver_type": "ollama"
  }
}

Contribute 🤝

Got ideas? Bugs? Want to contribute? Join us on this exciting journey to revolutionize how we interact with digital content! 🌍❤️

Stay Tuned 📢

Follow us for updates, tips, and much more. Let's make YouTube conversations the next big thing! 🚀🎉


Made with ❤️ and a dash of Python magic! 🐍✨

#ChatWithYouTube #PythonProject #AIConversations

p.s: you guessed right, an LLM wrote this README 😂

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