Use Pinecone, OpenAI, and Stream To Chat With Any Book

AI technology now enables users to engage in interactive conversations with characters from their favorite books or delve into the contents of any PDF document. This is achieved by uploading a book or document to an AI model that uses embeddings, which are high-dimensional vector representations of words that capture their meanings and relationships. The system is built using tools like Next.js for app creation, Pinecone for vector database management, OpenAI for generating embeddings, and Stream Chat for real-time communication. The process involves extracting text from PDFs, creating embeddings, and storing them in a vector database to facilitate retrieval-augmented generation (RAG). Once the text is embedded, users can chat with the document through a specially created channel, where the AI uses the embeddings to provide relevant, context-based responses. This setup allows for a dynamic, conversational engagement with texts, making it easier to extract and understand the most pertinent information from lengthy documents.