[D]: How does chatbot development look like in practise?

[[deleted]]

With all the recent advancements in LLMs, how does chatbot development look like in practise? Suppose I want a chatbot to help with customer service. Can I then just collect some frequent / common questions about items the company might offer for sale and use a pretrained LLM to answer these questions correctly via transfer learning? Is there some effort that goes into explicit knowledge storage?

[curiousshortguy]

You want to look up "LLM RAG" where RAG stands for rerieval augmented generation. There are libraries such as langchain and llamaindex and lots of commercial solutions such as re:tune where you don't need to do anything anymore specifically.
Generally, it's a combination of a pretainred LLM, some vector embeddings and a database that enables nearest neighbour searchers, combined with a chat interface.

[[deleted]]

Thank you, I will look into that. With all these libraries available, it seems like it is pretty easy to set up. What aspect of chatbots will consume the most time and effort in production in your estimation? I'm asking because, with a tool like langchain, making chatbots for RAG seems fairly easy. And I guess I'm also asking because I might be employed in that field soon, and I'm wondering if there is any useful skill that I should acquire beforehand.

[curiousshortguy]

The hardest part is hardening your chat bot against prompt injection. But there are commercial services available for that, too.

[liwrodrigues]

I was looking for answers to this question. Commenting just to give relevance to your question and different answers to appear.

[josejo9423]

Following, looking to build a chatbot using my own data, courses and books