Generate dense embeddings using a sentence transformer model (e.g., `all-MiniLM-L6-v2` for prototyping, `bge-large-en-v1.5` or `gte-large` for production). - Implement batched embedding generation with progress tracking. - Store embeddings in a vector database (Qdrant, ChromaDB, or Weaviate). - Buil