Do you discover it tough to maintain up with the newest ML analysis? Are you overwhelmed with the large quantity of papers about LLMs, vector databases, or RAGs?

On this submit, I’ll present construct an AI assistant that mines this huge quantity of data simply. You’ll ask it your questions in pure language and it’ll reply in response to related papers it finds on Papers With Code.

On the backend aspect, this assistant shall be powered with a Retrieval Augmented Era (RAG) framework that depends on a scalable serverless vector database, an embedding mannequin from VertexAI, and an LLM from OpenAI.

On the front-end aspect, this assistant shall be built-in into an interactive and simply deployable net software constructed with Streamlit.

Each step of this course of shall be detailed under with an accompanying supply code that you could reuse and adapt👇.

Prepared? Let’s dive in 🔍.

In case you’re all in favour of ML content material, detailed tutorials, and sensible ideas from the trade, comply with my publication. It’s known as The Tech Buffet.

Papers With Code (a.ok.a PWC) is a free web site for researchers and practitioners to seek out and comply with the newest state-of-the-art ML papers, supply code, and datasets.

Fortunately, it’s additionally potential to work together with PWC by an API to programmatically retrieve analysis papers. In case you have a look at this Swagger UI, you’ll find all of the accessible endpoints and check out them out.

Let’s, for instance, search papers on a particular key phrase.