In the realm of information retrieval, vector embeddings have emerged as a powerful tool for representing text in a multi-dimensional space. These transformations capture the semantic relationships between items, enabling accurate querying based on relevance. By leveraging techniques such as cosine similarity or nearest neighbor search, systems can