Vector/Semantic Search

Search using **vector mode** - pure semantic similarity search using embeddings. **Best For:** - Natural language queries - Conceptual searches - Queries like "quiet place for business meetings" or "romantic anniversary destination" **How it Works:** 1. Query is converted to a vector embedding 2. k-NN search finds hotels with similar embedding vectors 3. Results ranked by cosine similarity score **Note:** Works best with descriptive, natural language queries rather than keywords. ### Request Body Example ```json { "q": "romantic beachside getaway with spa", "stars": 5, "limit": 15 } ```