from enum import Enum
from typing import Callable, Union

from numpy import ndarray
from torch import Tensor
from .util import (
    cos_sim,
    manhattan_sim,
    euclidean_sim,
    dot_score,
    pairwise_cos_sim,
    pairwise_manhattan_sim,
    pairwise_euclidean_sim,
    pairwise_dot_score,
)


class SimilarityFunction(Enum):
    """
    Enum class for supported similarity functions. The following functions are supported:

    - ``SimilarityFunction.COSINE`` (``"cosine"``): Cosine similarity
    - ``SimilarityFunction.DOT_PRODUCT`` (``"dot"``, ``dot_product``): Dot product similarity
    - ``SimilarityFunction.EUCLIDEAN`` (``"euclidean"``): Euclidean distance
    - ``SimilarityFunction.MANHATTAN`` (``"manhattan"``): Manhattan distance
    """

    COSINE = "cosine"
    DOT_PRODUCT = "dot"
    DOT = "dot"  # Alias for DOT_PRODUCT
    EUCLIDEAN = "euclidean"
    MANHATTAN = "manhattan"

    @staticmethod
    def to_similarity_fn(
        similarity_function: Union[str, "SimilarityFunction"],
    ) -> Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]:
        """
        Converts a similarity function name or enum value to the corresponding similarity function.

        Args:
            similarity_function (Union[str, SimilarityFunction]): The name or enum value of the similarity function.

        Returns:
            Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]: The corresponding similarity function.

        Raises:
            ValueError: If the provided function is not supported.

        Example:
            >>> similarity_fn = SimilarityFunction.to_similarity_fn("cosine")
            >>> similarity_scores = similarity_fn(embeddings1, embeddings2)
            >>> similarity_scores
            tensor([[0.3952, 0.0554],
                    [0.0992, 0.1570]])
        """
        similarity_function = SimilarityFunction(similarity_function)

        if similarity_function == SimilarityFunction.COSINE:
            return cos_sim
        if similarity_function == SimilarityFunction.DOT_PRODUCT:
            return dot_score
        if similarity_function == SimilarityFunction.MANHATTAN:
            return manhattan_sim
        if similarity_function == SimilarityFunction.EUCLIDEAN:
            return euclidean_sim

        raise ValueError(
            "The provided function {} is not supported. Use one of the supported values: {}.".format(
                similarity_function, SimilarityFunction.possible_values()
            )
        )

    @staticmethod
    def to_similarity_pairwise_fn(
        similarity_function: Union[str, "SimilarityFunction"],
    ) -> Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]:
        """
        Converts a similarity function into a pairwise similarity function.

        The pairwise similarity function returns the diagonal vector from the similarity matrix, i.e. it only
        computes the similarity(a[i], b[i]) for each i in the range of the input tensors, rather than
        computing the similarity between all pairs of a and b.

        Args:
            similarity_function (Union[str, SimilarityFunction]): The name or enum value of the similarity function.

        Returns:
            Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]: The pairwise similarity function.

        Raises:
            ValueError: If the provided similarity function is not supported.

        Example:
            >>> pairwise_fn = SimilarityFunction.to_similarity_pairwise_fn("cosine")
            >>> similarity_scores = pairwise_fn(embeddings1, embeddings2)
            >>> similarity_scores
            tensor([0.3952, 0.1570])
        """
        similarity_function = SimilarityFunction(similarity_function)

        if similarity_function == SimilarityFunction.COSINE:
            return pairwise_cos_sim
        if similarity_function == SimilarityFunction.DOT_PRODUCT:
            return pairwise_dot_score
        if similarity_function == SimilarityFunction.MANHATTAN:
            return pairwise_manhattan_sim
        if similarity_function == SimilarityFunction.EUCLIDEAN:
            return pairwise_euclidean_sim

        raise ValueError(
            "The provided function {} is not supported. Use one of the supported values: {}.".format(
                similarity_function, SimilarityFunction.possible_values()
            )
        )

    @staticmethod
    def possible_values():
        """
        Returns a list of possible values for the SimilarityFunction enum.

        Returns:
            list: A list of possible values for the SimilarityFunction enum.

        Example:
            >>> possible_values = SimilarityFunction.possible_values()
            >>> possible_values
            ['cosine', 'dot', 'euclidean', 'manhattan']
        """
        return [m.value for m in SimilarityFunction]

from enum import Enum
from typing import Callable, Union

from numpy import ndarray
from torch import Tensor
from .util import (
    cos_sim,
    manhattan_sim,
    euclidean_sim,
    dot_score,
    pairwise_cos_sim,
    pairwise_manhattan_sim,
    pairwise_euclidean_sim,
    pairwise_dot_score,
)


class SimilarityFunction(Enum):
    COSINE = "cosine"
    DOT_PRODUCT = "dot"
    DOT = "dot"  # Alias for DOT_PRODUCT
    EUCLIDEAN = "euclidean"
    MANHATTAN = "manhattan"

    @staticmethod
    def to_similarity_fn(
        similarity_function: Union[str, "SimilarityFunction"],
    ) -> Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]:
        similarity_function = SimilarityFunction(similarity_function)

        if similarity_function == SimilarityFunction.COSINE:
            return cos_sim
        if similarity_function == SimilarityFunction.DOT_PRODUCT:
            return dot_score
        if similarity_function == SimilarityFunction.MANHATTAN:
            return manhattan_sim
        if similarity_function == SimilarityFunction.EUCLIDEAN:
            return euclidean_sim

        raise ValueError(
            "The provided function {} is not supported. Use one of the supported values: {}.".format(
                similarity_function, SimilarityFunction.possible_values()
            )
        )

    @staticmethod
    def to_similarity_pairwise_fn(
        similarity_function: Union[str, "SimilarityFunction"],
    ) -> Callable[[Union[Tensor, ndarray], Union[Tensor, ndarray]], Tensor]:
        similarity_function = SimilarityFunction(similarity_function)

        if similarity_function == SimilarityFunction.COSINE:
            return pairwise_cos_sim
        if similarity_function == SimilarityFunction.DOT_PRODUCT:
            return pairwise_dot_score
        if similarity_function == SimilarityFunction.MANHATTAN:
            return pairwise_manhattan_sim
        if similarity_function == SimilarityFunction.EUCLIDEAN:
            return pairwise_euclidean_sim

        raise ValueError(
            "The provided function {} is not supported. Use one of the supported values: {}.".format(
                similarity_function, SimilarityFunction.possible_values()
            )
        )

    @staticmethod
    def possible_values():
        return [m.value for m in SimilarityFunction]
