On this article, I’ll present you how one can develop the MailDiscoverer utility to go looking Gmail emails utilizing RAG. First, I’ll present you tips on how to arrange the authentication pipeline to entry consumer’s emails (if consent is given). The emails are then embedded utilizing an OpenAI textual content embedder and saved in a Pinecone vector database. This enables a consumer to ask questions relating to the emails, and the RAG system will retrieve probably the most related emails and supply a solution to the query.
The applying developed on this article might be discovered on Streamlit. My GitHub repository for this code is also available.
The video under showcases how the appliance works. After logging in and importing your emails, you may ask a query about them, and the appliance will present a solution and showcase probably the most related emails used to offer the reply.