
1/9/2024 · Demetrios Brinkmann
What this post added
This post details the application of Qdrant's vector search capabilities for a music recommendation system. It describes a novel approach to generating song embeddings using natural language descriptions queried from LLMs, and then encoding these descriptions with sentence transformers. The core of the recommendation system relies on Qdrant for performing cosine similarity search on these embeddings to find songs matching user-defined moods or vibes. The post highlights the use of Qdrant's vector indexing and search for this specific use case.