[kacperlukawski]

Have you considered using a proper vector database like Qdrant (https://qdrant.tech)? In the demo, it might be just fine to calculate the distance to all the articles in the knowledge base, but in a real case scenario, you'll sooner or later face scaling issues.

Also, libraries such as Langchain are integrated with both LLMs and vector databases, so you can prototype even faster.

[tiagopavan]

Thank you for your comment!

I hadn't come across Qdrant before, but I will definitely check it out. Although I've been experimenting with milvus.io lately, these vector databases weren't on my radar when I first started exploring embeddings.

Langchain looks incredibly fascinating too! At first glance, it seems like it could be my go-to library for prototyping. I appreciate your suggestion.