List of embeddings, one for each text.
        """
        results = []
        _chunk_size = len(texts) if chunk_size > len(texts) else chunk_size
        for i in range(0, len(texts), _chunk_size):
            response = self._embedding_func(texts[i : i + _chunk_size])
            results.extend(response)
        return results
[docs]    def embed_query(self, text: str) -> List[float]:
        """Compute query embeddings using a SageMaker inference endpoint.
        Args:
            text: The text to embed.
        Returns:
            Embeddings for the text.
        """
        return self._embedding_func([text])[0]