| from sentence_transformers import SentenceTransformer | |
| from Rag import load_json_to_db, make_embeddings, save_embeddings # Adjust import | |
| def precompute_and_save(embedder_name, db_path): | |
| print("Loading database...") | |
| db = load_json_to_db(db_path) | |
| print(f"Loading embedder: {embedder_name}") | |
| model = SentenceTransformer(embedder_name, trust_remote_code=True) | |
| print("Computing embeddings...") | |
| embeddings = make_embeddings(model, embedder_name, db) | |
| print("Saving embeddings...") | |
| save_embeddings(embedder_name, embeddings) | |
| print("Done.") | |
| if __name__ == "__main__": | |
| embedder_name = "Qwen/Qwen3-Embedding-0.6B" # Example embedder name | |
| db_path = "../data/processed/guideline_db.json" | |
| precompute_and_save(embedder_name, db_path) | |