in demo-python/code/custom-vectorizer/scripts/download_embedding_model.py [0:0]
def main():
if model_env_var not in os.environ:
print(f"Using default embedding model{default_embedding_model}")
subprocess.run(f"azd env set {model_env_var} {default_embedding_model}", shell=True)
model_parent_dir = os.path.join(os.getcwd(), model_parent_dir_name)
# Check if the directory exists
if not os.path.exists(model_parent_dir):
# If it doesn't exist, create it
os.makedirs(model_parent_dir)
# Check if model is already downloaded
model_name = os.getenv(model_env_var, default_embedding_model)
model_dir = os.path.join(model_parent_dir, model_name)
if os.path.exists(model_dir):
print(f"Model {model_name} already downloaded")
return
# Initialize and download the model
print(f"Downloading {model_name}...")
from sentence_transformers import SentenceTransformer
model = SentenceTransformer(model_name)
model.save(model_dir)