def text_to_embedding(text: str) -> List[float]:
    """Convert text to a unique embedding using ASCII values."""
    ascii_values = [float(ord(char)) for char in text]
    # Pad or trim the list to make it of length ADA_TOKEN_COUNT
    return ascii_values[:EMBEDDING_DIMENSION] + [0.0] * (
        EMBEDDING_DIMENSION - len(ascii_values)
    )
Convert text to a unique embedding using ASCII values.
llama-index-integrations/vector_stores/llama-index-vector-stores-couchbase/tests/test_vector_stores_couchbase.py