How does it compare to notebooklm in terms of quality and length of output given llama3.2-8B?
You need to give more context, currently it seems like this is yet another reinvention of the wheel.
Good question! You can use any open source or private model you want with this (just by changing one line in `databridge.toml`), whereas notebook lm is limited to gemini. While our UI component allows it to be used as an open source notebook lm alternative, it is developed for developers building AI apps and doing context management. We are working on adding techniques like CAG (cache augmented generation) and graphRAG for better and more flexible querying, and have custom embedding pipelines for different data types.