This gets Qdrant vector database working with Java and LangChain4j for semantic search and RAG pipelines. You'll find patterns for Spring Boot integration, Docker deployment, and the usual vector operations like similarity search with filters. The skill covers both the raw Qdrant client and LangChain4j's abstractions, which matters because you often need one or the other depending on your setup. Includes multi-tenant patterns and proper async handling. Watch the vector dimension matching, it's strict and will break silently if your embedding model outputs different sizes than your collection expects. Good starting point if you're building retrieval systems in Java rather than Python.
npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill qdrant