We just built an open NotebookLM clone!
Here’s what it can do for you:
Process multi-modal data.
Scrape websites and YouTube videos.
Create a knowledge base on top of it.
Answer the questions you ask.
Remember every conversation.
Generate a podcast.
Tech stack:
AssemblyAI for multilingual speech-to-text that can transcribe over 99 languages → (it also gives you 300 hrs of free transcription).
The reason for us to do this is not to reinvent the wheel but to explain how one of the most powerful tools for learning and research actually works under the hood.
The idea is to replicate this as closely as possible using some popular and open-source tools!
The video at the top gives a video walkthrough.
So by the end of this video, you’ll learn:
How to process multimodal data, including text, audio, video, website URLs, and even YouTube videos, into a format ready for use with LLMs.
How to store that data in a vector database for faster search and retrieval.
On top of it, add a memory layer to remember conversations and preferences, giving a more personalized user experience.
And finally, you can either chat with it or generate a podcast from this knowledge using a fully open-source, locally running text-to-speech model.
The code is available in this Studio: Build your own NotebookLM. You can run it without any installations by reproducing our environment below:
Thanks for reading and watching!
