SemanticDotArt: Rethinking art discovery with LanceDB

SemanticDotArt is an innovative platform designed to enhance art discovery by using a multimodal retrieval system powered by LanceDB, which allows users to search for art based on emotions and poetic language rather than just literal traits. The system captures both literal content and emotional subtext by creating multiple representations of artworks, such as poetic impressions, mood tags, and stylistic fingerprints, all stored within a single database row. This enables dynamic semantic routing that adjusts search paths based on user input, whether it is text, images, or a combination, ensuring a more human-like search experience. The platform's core is supported by LanceDB's hybrid search capabilities, allowing for flexible and exploratory interactions, while Google Gemini aids in poetic rewrites and intent classification. SemanticDotArt was developed by Bryan Bischof, Ayush Chaurasia, and Chang She, with contributions from various experts in design and backend services.

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