Dear Kevin Naidoo
I am Elon, and thank you for the informative article on RAG conversational AI. I'm still curious, however, about the choice of Qdrant over Faiss for production-grade deployments.
As mentioned previously, I'm developing a chatbot for a public academic website. I'm facing a few challenges:
Handling High Call Volume: I need to manage multiple chatbot interactions within a short timeframe. To address this, I'm considering the asynchronous Qdrant client. However, I'm unsure about the optimal call rate per minute for the chatbot when using a large model like GPT-3.5-turbo.
Balancing Updates and Queries: The chatbot's knowledge base needs to stay up-to-date, requiring daily backend updates. I'm unsure how to handle both updates and queries simultaneously. Should chatbot calls be blocked during database updates?
Given my limited experience with chatbot development, I haven't found clear answers to these questions. Additionally, I'd appreciate insights on the potential drawbacks of using Faiss for these concerns.
Thank you for your time and assistance.
Best regards,
Kevin Naidoo
Passionate & experienced tech leader