How to use the mindmeld.components.request.FrozenParams function in mindmeld

def test_immutability_of_request_and_params():
    """Test the immutability of the request and params objects"""
    with pytest.raises(FrozenInstanceError):
        params = FrozenParams()
        params.allowed_intents = []

    with pytest.raises(TypeError):
        params = FrozenParams()
        params.dynamic_resource["a"] = "b"

    with pytest.raises(FrozenInstanceError):
        request = Request()
        request.params = Params()

    with pytest.raises(TypeError):
        request = Request()
        request.frame["a"] = "b"

default_params (Params, optional): The default params to use with each turn. These
                defaults will be overridden by params passed for each turn.
            force_sync (bool, optional): Force synchronous return for `say()` and `process()`
                even when app is in async mode.
        """
        app = app or path.get_app(app_path)
        app.lazy_init(nlp)
        self._app_manager = app.app_manager
        if not self._app_manager.ready:
            self._app_manager.load()
        self.context = context or {}
        self.history = []
        self.frame = {}
        self.default_params = default_params or Params()
        self.force_sync = force_sync
        self.params = FrozenParams()

def freeze_params(params):
    """
    If params is a dictionary or Params we convert it into FrozenParams.
    Otherwise we raise a TypeError.

    Args:
        params (dict, Params): The input params to convert

    Returns:
        FrozenParams: The converted params object
    """
    params = params or FrozenParams()
    if isinstance(params, dict):
        params = FrozenParams(**params)
    elif params.__class__ == Params:
        params = FrozenParams(**DialogueResponder.to_json(params))
    elif not isinstance(params, FrozenParams):
        raise TypeError(
            "Invalid type for params argument. "
            "Should be dict or {}".format(FrozenParams.__name__)
        )
    return params

Returns:
            (dict): The dictionary response.
        """
        if self._app_manager.async_mode:
            res = self._process_async(text, params=params)
            if self.force_sync or force_sync:
                return asyncio.get_event_loop().run_until_complete(res)
            return res

        if not self._app_manager.ready:
            self._app_manager.load()

        internal_params = copy.deepcopy(self.params)

        if isinstance(params, dict):
            params = FrozenParams(**params)

        if isinstance(internal_params, dict):
            internal_params = FrozenParams(**internal_params)

        if params:
            # If the params arg is explicitly set, overight the internal params
            for k, v in vars(params).items():
                vars(internal_params)[k] = v

        response = self._app_manager.parse(
            text,
            params=internal_params,
            context=self.context,
            frame=self.frame,
            history=self.history,
        )

Args:
            text (str): The text of a message.
            params (dict): The params to use with this message, overriding any defaults
                which may have been set.

        Returns:
            (dict): The dictionary Response.
        """
        if not self._app_manager.ready:
            await self._app_manager.load()

        internal_params = copy.deepcopy(self.params)

        if isinstance(params, dict):
            params = FrozenParams(**params)

        if isinstance(internal_params, dict):
            internal_params = FrozenParams(**internal_params)

        if params:
            # If the params arg is explicitly set, overight the internal params
            for k, v in vars(params).items():
                vars(internal_params)[k] = v

        response = await self._app_manager.parse(
            text,
            params=internal_params,
            context=self.context,
            frame=self.frame,
            history=self.history,
        )

if self._app_manager.async_mode:
            res = self._process_async(text, params=params)
            if self.force_sync or force_sync:
                return asyncio.get_event_loop().run_until_complete(res)
            return res

        if not self._app_manager.ready:
            self._app_manager.load()

        internal_params = copy.deepcopy(self.params)

        if isinstance(params, dict):
            params = FrozenParams(**params)

        if isinstance(internal_params, dict):
            internal_params = FrozenParams(**internal_params)

        if params:
            # If the params arg is explicitly set, overight the internal params
            for k, v in vars(params).items():
                vars(internal_params)[k] = v

        response = self._app_manager.parse(
            text,
            params=internal_params,
            context=self.context,
            frame=self.frame,
            history=self.history,
        )
        self.history = response.history
        self.frame = response.frame
        self.params = response.params

def freeze_params(params):
    """
    If params is a dictionary or Params we convert it into FrozenParams.
    Otherwise we raise a TypeError.

    Args:
        params (dict, Params): The input params to convert

    Returns:
        FrozenParams: The converted params object
    """
    params = params or FrozenParams()
    if isinstance(params, dict):
        params = FrozenParams(**params)
    elif params.__class__ == Params:
        params = FrozenParams(**DialogueResponder.to_json(params))
    elif not isinstance(params, FrozenParams):
        raise TypeError(
            "Invalid type for params argument. "
            "Should be dict or {}".format(FrozenParams.__name__)
        )
    return params

confidences (): Immutables Map of keys ``domains``, ``intents``, ``entities`` and ``roles``
            containing confidence probabilities across all labels for each classifier.
        nbest_transcripts_text (tuple): List of alternate n-best transcripts from an ASR system
        nbest_transcripts_entities (tuple): List of lists of extracted entities for each of the
            n-best transcripts.
        nbest_aligned_entities (tuple): List of lists of aligned entities for each of the n-best
            transcripts.
    """

    domain = attr.ib(default=None)
    intent = attr.ib(default=None)
    entities = attr.ib(default=attr.Factory(tuple), converter=tuple)
    history = attr.ib(default=attr.Factory(tuple), converter=tuple)
    text = attr.ib(default=None)
    frame = attr.ib(default=immutables.Map(), converter=immutables.Map)
    params = attr.ib(default=FrozenParams())
    context = attr.ib(default=immutables.Map(), converter=immutables.Map)
    confidences = attr.ib(default=immutables.Map(), converter=immutables.Map)
    nbest_transcripts_text = attr.ib(default=attr.Factory(tuple), converter=tuple)
    nbest_transcripts_entities = attr.ib(default=attr.Factory(tuple), converter=tuple)
    nbest_aligned_entities = attr.ib(default=attr.Factory(tuple), converter=tuple)