Vectors Embeddings | Spring AI

A tutorial covering vector embeddings in the context of AI engineering using Spring AI and Mistral's embedding models. Explains how text is tokenized, converted to token IDs, and then transformed into multi-dimensional float vectors that capture semantic relationships between words. Demonstrates the concept visually with 2D plots showing similar words clustering together, then walks through a practical implementation using Spring AI with Mistral's embedding API, including setting up API keys, adding Maven dependencies, and calling the embedding model to get float array representations of text.