from langchain_huggingface import HuggingFaceEmbeddings

def get_embedding_model():
    return HuggingFaceEmbeddings(
        model_name="Qwen/Qwen3-Embedding-0.6B"
    )

if __name__ == "__main__":
    model = get_embedding_model()
    text = "I am a Machine Learning Engineer with Python experience."
    vector = model.embed_query(text)
    print(f"Text: {text}")
    print(f"Vector length (dimension): {len(vector)}")
    print(f"1st 5 elements: {vector[:5]}")