The client operates a bookstore with various titles spanning genres, authors, and eras. This store is not just a commercial entity but a hub for literary enthusiasts, providing curated collections, rare editions, and a space for readers to delve deep into the world of literature.The client envisioned a Conversational Agent that would serve as a knowledgeable companion for customers. This agent would possess in-depth knowledge of the content of books on sale and a vast understanding of classic literature. Beyond just answering queries, the agent should recommend books based on user questions. Furthermore, it would have a \'memory\' of past interactions, allowing it to offer personalized recommendations based on previous conversations with the user.A system was built using entirely API-based LLMs. The main LLMs for generation and embeddings were GPT-3.5 and ada-002. We used Pinecone for knowledge & memory storage. This combination allowed the Conversational Agent to provide insightful book recommendations and maintain interaction continuity.
