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