Build an LLM and RAG-based Chat Application using AlloyDB and LangChain Reviews

Michael C. · Reviewed 5 ay ago

Bola A. · Reviewed 5 ay ago

CJ L. · Reviewed 5 ay ago

Divam S. · Reviewed 5 ay ago

Raman W. · Reviewed 5 ay ago

Carl F. · Reviewed 5 ay ago

Miguel R. · Reviewed 5 ay ago

Great lab, thanks!

Dmitriy S. · Reviewed 5 ay ago

Graham L. · Reviewed 5 ay ago

Awesome!

John E. · Reviewed 5 ay ago

This is a pretty terrible lab. Way too much setup. We haven't even run a query yet, and there's 10 minutes left to go in the webinar. In production you'd probably just terraform all this stuff. Qwiklabs projects can be configured where lots of services like this are already running, so the users don't have to waste so much time with setup. That said, the application is interesting and helpful. However, the lab provides zero insight into how it works. Overall I learned very little from this lab.

Jason B. · Reviewed 5 ay ago

jingren s. · Reviewed 5 ay ago

You get to an end result but nothing is truly taught from an education standpoint. It feels like a series of copy/paste without explanation on what/why.

Timothy F. · Reviewed 5 ay ago

Samuel N. · Reviewed 5 ay ago

too high level, would be nice to dig into how the the code is structured

Zhijia Y. · Reviewed 5 ay ago

Raphael C. · Reviewed 5 ay ago

Patricia B. · Reviewed 5 ay ago

Yes it was great to work in a hands on learning environment. Please do more of these!

Sheena J. · Reviewed 5 ay ago

Cut and paste provides no context, so it's not really a learning experience. Additionally, most of that cut and paste seemed unnecessary for the purpose of the lab. Script it and keep to the learning goals.

Paul B. · Reviewed 5 ay ago

c

Amol C. · Reviewed 5 ay ago

Manish P. · Reviewed 5 ay ago

Paul R. · Reviewed 5 ay ago