PostgreSQL as Vector database: Create LLM Apps with pgvector

PostgreSQL, a robust and extensible open-source relational database management system, has evolved into a prominent player in vector data processing with the introduction of the pgvector extension. Tessell has integrated pgvector as a first-class component to develop an internal ChatGPT tool for its Sales and Marketing teams, addressing the challenge of managing vast amounts of information in various formats. This tool leverages the Retrieval Augmented Generation (RAG) technique, which provides additional context to foundational models like GPT-3 and GPT-4 by using vector embeddings stored in PostgreSQL, thus enhancing the models' ability to deliver precise and contextually relevant answers. Embeddings are generated using OpenAI APIs and stored in a PostgreSQL vector database, enabling efficient similarity searches to find the most relevant content. This setup allows Tessell to quickly provide accurate responses to specific queries, making it a valuable asset for internal communication and information retrieval.