Building a Local Semantic Search Engine with Qdrant, Qwen3-Embedding (4b), and Spring Boot
Today we will help Dipper manage his notes and search through the vector database Qdrant. Embeddings will be evaluated using local Ollama with model qwen3-embedding:4b. A Spring Boot WebFlux application will enable creating new notes and later finding relevant entries for a given request. How semantic search works Some LLMs process prompts, while others help generate embeddings. An embedding is just a vector — a sequence of numbers evaluated based on your input (note content in our example) ...