[pstorm]

I've been planning on building some of this for an internal tool, but now it looks like I don't have to. I'm impressed by the demo, it looks really polished.

I'm particularly surprised by the speed considering all of the pre and post processing. I am doing some similar things and that is one bottlenecks. I'll dig in, but I'm curious what models you are using for each of these steps.

[yuhongsun]

A lot of teams we talk to switched from an in-house solution to either directly using Danswer or building on top of Danswer. Glad you liked the demo!

We're using E5 base by default but there's an embedding model admin page to choose alternatives. There's also an API for it if you know what you're doing, you can even set one of the billion+ parameter LLM bi-encoders if you want (but you'd need a GPU for sure).

[pdxandi]

I’m actually giving a presentation tomorrow to my team about a tool I was building to leverage our runbooks (came out of a hackathon) and this just blows my app out of the water. I’m really stoked to give this a try and possibly contribute back by creating a connector for our messaging app. Thank you so much for making this available and for explaining so much about the architecture.