AI-Powered Personal Shopping Assistant with RAG and WooCommerce

This workflow creates an intelligent, AI-driven personal shopper integrated with WooCommerce, utilizing Retrieval-Augmented Generation (RAG) for enhanced product recommendations. It begins with receiving chat messages, which are analyzed by an AI agent to determine if the user is asking for product recommendations or general store information. If a product search is detected, the system extracts key details such as keywords, price range, and SKU from the chat input. These details are used to filter WooCommerce products, retrieving available items within the specified criteria. The workflow employs OpenAI’s language models for understanding user intent and generating responses, while embedding and vector store nodes facilitate document retrieval from Google Drive and a Qdrant vector database for context-aware answers. This setup enables a seamless, AI-powered shopping experience both for users seeking product recommendations and those asking store-related questions. Practical applications include personalized shopping assistants, intelligent customer support, and dynamic product filtering to enhance eCommerce engagement.