def extract_embedding()

in src/fmeval/model_runners/extractors/jumpstart_extractor.py [0:0]

• 10 lines of code
• 4 McCabe index (conditional complexity)

    def extract_embedding(self, data: Union[List, Dict], num_records: int = 1) -> List[float]:
        """
        Extracts the embedding from the JumpStartModel response. This only supported for text embedding models.

        :param data: The model response from the JumpStart Model
        :param num_records: The number of records in the model response. Must be 1.
        """
        assert num_records == 1, "Jumpstart extractor does not support batch requests"
        try:
            assert self._embedding_compiler, f"Unable to extract embedding from Jumpstart model: {self._model_id}"
            output = self._embedding_compiler.search(data)
            if output is None and not isinstance(output, str):
                raise EvalAlgorithmClientError(f"Unable to extract embedding from Jumpstart model: {self._model_id}")
            return output
        except ValueError as e:
            raise EvalAlgorithmClientError(f"Unable to extract embedding from Jumpstart model: {self._model_id}", e)