TIDAL MCP is a personalized music recommendation system that filters the TIDAL music library through LLM combined with user - defined conditions, supporting intelligent recommendation and playlist management based on playback history/playlists.

Ummon is a code analysis tool that enhances the understanding of codebases by building a code knowledge graph. It supports multi-language code analysis, an advanced query system, and intelligent recommendation functions.

This is a fashion recommendation system based on CLIP. It detects the clothing pictures uploaded by users through YOLO and recommends similar products after encoding with CLIP. The project has completed the construction of the FastAPI server, database connection, and basic front - end UI. The next step is to optimize the label accuracy of CLIP and system integration.

TIDAL MCP is a personalized recommendation system based on the TIDAL music platform. Through LLM technology, users can obtain accurate music recommendations based on custom conditions (such as year, style, etc.) and directly manage playlists in their TIDAL accounts.

A fashion recommendation system based on CLIP that realizes similar product recommendations through image recognition and encoding.