This seems similar to building a RAG router (1) to perform dynamic retrieval/querying over data.
After getting hundreds of questions on my Interactive Resume AI chatbot (2), I've found the user queries can be categorized as: greeting, professional skills question, professional experience question, personal/hobby question and common interview question.
I am currently working on building a RAG router to help improve the quality of Q&A responses. I currently use gpt3.5 turbo without any special RAG techniques and the quality is lacking on performing Q&A over my resume and Q&A csv file. GPT4 works well but is too expensive.
Comments
This seems similar to building a RAG router (1) to perform dynamic retrieval/querying over data.
After getting hundreds of questions on my Interactive Resume AI chatbot (2), I've found the user queries can be categorized as: greeting, professional skills question, professional experience question, personal/hobby question and common interview question.
I am currently working on building a RAG router to help improve the quality of Q&A responses. I currently use gpt3.5 turbo without any special RAG techniques and the quality is lacking on performing Q&A over my resume and Q&A csv file. GPT4 works well but is too expensive.
1. https://docs.llamaindex.ai/en/stable/examples/low_level/rout... 2. https://jon-olson.com/resume_ai