| from sentence_transformers import SentenceTransformer | |
| _embedder = None | |
| def get_embedding_model() -> SentenceTransformer: | |
| global _embedder | |
| if _embedder is None: | |
| try: | |
| # Try to load from local cache first to prevent blocking network requests | |
| print("Loading embedding model from local cache...") | |
| _embedder = SentenceTransformer("all-MiniLM-L6-v2", local_files_only=True) | |
| except Exception: | |
| # Fall back to downloading if not cached | |
| print("Local cache not found. Downloading embedding model...") | |
| _embedder = SentenceTransformer("all-MiniLM-L6-v2") | |
| return _embedder | |