[docs]    def __init__(
        self,
        metrics: List[Any],
        implementation_name: Optional[str] = None,
    ) -> None:
        """Initializes the `deepevalCallbackHandler`.
        Args:
            implementation_name: Name of the implementation you want.
            metrics: What metrics do you want to track?
        Raises:
            ImportError: if the `deepeval` package is not installed.
            ConnectionError: if the connection to deepeval fails.
        """
        super().__init__()
        # Import deepeval (not via `import_deepeval` to keep hints in IDEs)
        try:
            import deepeval  # ignore: F401,I001
        except ImportError:
            raise ImportError(
                """To use the deepeval callback manager you need to have the 
                `deepeval` Python package installed. Please install it with 
                `pip install deepeval`"""
            )
        if os.path.exists(".deepeval"):
            warnings.warn(
                """You are currently not logging anything to the dashboard, we 
                recommend using `deepeval login`."""
            )
        # Set the deepeval variables
        self.implementation_name = implementation_name
        self.metrics = metrics
        warnings.warn(
            (
                "The `DeepEvalCallbackHandler` is currently in beta and is subject to"
                " change based on updates to `langchain`. Please report any issues to"
                f" {self.ISSUES_URL} as an `integration` issue."
            ),
        )
[docs]    def on_llm_start(
        self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
    ) -> None: