Latent Scope is a new workflow and tool that allows users to visualize and explore datasets through the lens of latent spaces, created by leveraging the power of machine learning models. The project emphasizes the importance of understanding why certain data is being retrieved and offers a unique perspective on data embedding. Users can engage in similarity search, explore labeled clusters, and zoom in on individual data points while keeping the context of the entire dataset. Latent Scope can be run locally or on a trusted server, providing a comprehensive overview of data processing while maintaining a user-friendly approach. The tool offers a structured process with steps like Embed, UMAP, Cluster, Label, Scope, and Explore, empowering users to make informed choices at each stage. The repository supports multiple embedding models and services, enabling customizability and ease of use.
https://github.com/enjalot/latent-scope