Classify Images with a Qdrant KNN Vector Classifier

## KNN classification workflow-tool ### This n8n template takes an image URL (as anomaly detection tool does), and as output, it returns a class of the object on the image (out of land types list) * An image URL is received via the Execute Workflow Trigger, which is then sent to the Voyage.ai Multimodal Embeddings API to fetch its embedding. * The image's embedding vector is then used to query Qdrant, returning a set of X similar images with pre-labeled classes. * Majority voting is done for classes of neighbouring images. * A loop is used to resolve scenarios where there is a tie in Majority Voting (for example, we have 5 "forest" and 5 "beach"), and we increase the number of neighbours to retrieve. * When the loop finally resolves, the identified class is returned to the calling workflow.