Build a Company Policy Chatbot Using RAG, Pinecone, and OpenAI

This workflow automates the creation of a chatbot that leverages Retrieval-Augmented Generation (RAG) to provide precise answers to company policy queries. It involves two main processes: loading company policy documents into a Pinecone vector database and retrieving relevant information to answer user queries using OpenAI's language models. The workflow ensures that new policy documents uploaded to Google Drive are automatically processed, embedded, and indexed in Pinecone, making them readily available for semantic search. Employees can then interact with the chatbot to receive accurate, document-backed answers to their policy-related questions.