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)