# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========

import json
from typing import List, Optional

from camel.logger import get_logger
from camel.toolkits import FunctionTool
from camel.toolkits.base import BaseToolkit
from camel.utils import MCPServer

logger = get_logger(__name__)


@MCPServer()
class SymPyToolkit(BaseToolkit):
    r"""A toolkit for performing symbolic computations using SymPy.
    This includes methods for Algebraic manipulation calculus
    and Linear Algebra.
    """

    def __init__(
        self,
        default_variable: str = 'x',
        timeout: Optional[float] = None,
    ):
        r"""Initializes the toolkit with a default variable and logging.

        Args:
            default_variable (str): The default variable for
                operations (default: :obj:`x`)
        """
        super().__init__(timeout=timeout)
        self.default_variable = default_variable
        logger.info(f"Default variable set to: {self.default_variable}")

    def simplify_expression(self, expression: str) -> str:
        r"""Simplifies a mathematical expression.

        Args:
            expression (str): The mathematical expression to simplify,
                provided as a string.

        Returns:
            str: JSON string containing the simplified mathematical
                expression in the `"result"` field. If an error occurs,
                the `"status"` field will be set to `"error"` with a
                corresponding `"message"`.
        """
        import sympy as sp

        try:
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            simplified = sp.simplify(expr)
            return json.dumps(
                {"status": "success", "result": str(simplified)},
                ensure_ascii=False,
            )
        except Exception as e:
            return self.handle_exception("simplify_expression", e)

    def expand_expression(self, expression: str) -> str:
        r"""Expands an algebraic expression.

        Args:
            expression (str): The algebraic expression to expand,
                provided as a string.

        Returns:
            str: JSON string containing the expanded algebraic expression
                in the `"result"` field. If an error occurs, the JSON
                string will include an `"error"` field with the corresponding
                error message.
        """
        import sympy as sp

        try:
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            expanded_expr = sp.expand(expr)
            return json.dumps(
                {"result": str(expanded_expr)}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("expand_expression", e)

    def factor_expression(self, expression: str) -> str:
        r"""Factors an algebraic expression.

        Args:
            expression (str): The algebraic expression to factor,
                provided as a string.

        Returns:
            str: JSON string containing the factored algebraic expression
                in the `"result"` field. If an error occurs, the JSON string
                will include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            factored_expr = sp.factor(expr)
            return json.dumps(
                {"result": str(factored_expr)}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("factor_expression", e)

    def solve_linear_system(
        self, equations: List[str], variables: List[str]
    ) -> str:
        r"""Solves a system of linear equations.

        Args:
            equations (List[str]): A list of strings representing the linear
                equations to be solved.
            variables (List[str]): A list of strings representing the variables
                involved in the equations.

        Returns:
            str: JSON string containing the solution to the system of equations
                in the `"result"` field. Each solution is represented as
                a tuple of values corresponding to the variables. If an
                error occurs, the JSON string will include an `"error"`
                field with the corresponding error message.
        """
        import sympy as sp

        try:
            eqs = [sp.sympify(eq) for eq in equations]
            vars = sp.symbols(variables)
            solution = sp.linsolve(eqs, vars)
            return json.dumps(
                {"result": [str(sol) for sol in solution]}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("solve_linear_system", e)

    def solve_nonlinear_system(
        self, sympy_equations: List[str], variables: List[str]
    ) -> str:
        r"""Solves a system of nonlinear equations.

        Args:
            sympy_equations (List[str]): A list of strings representing the
                nonlinear equations to be solved. The equation to solve, must
                be compatible with SymPy, provided as a string.

            variables (List[str]): A list of strings representing the variables
                involved in the equations.

        Returns:
            str: JSON string containing the solutions to the system of
                equations in the `"result"` field. Each solution is
                represented as a tuple of values corresponding to the
                variables. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding
                error message.
        """
        import sympy as sp

        try:
            eqs = [sp.sympify(eq) for eq in sympy_equations]
            vars = sp.symbols(variables)
            solution = sp.nonlinsolve(eqs, vars)
            return json.dumps(
                {"result": [str(sol) for sol in solution]}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("solve_nonlinear_system", e)

    def solve_univariate_inequality(
        self, inequality: str, variable: str
    ) -> str:
        r"""Solves a single-variable inequality.

        Args:
            inequality (str): A string representing the inequality
                to be solved.
            variable (str): The variable in the inequality.

        Returns:
            str: JSON string containing the solution to the inequality in the
                `"result"` field. The solution is represented in a symbolic
                format (e.g., intervals or expressions). If an error occurs,
                the JSON string will include an `"error"` field with the
                corresponding error message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            ineq = sp.sympify(inequality)
            solution = sp.solve_univariate_inequality(ineq, var)
            return json.dumps({"result": str(solution)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("solve_univariate_inequality", e)

    def reduce_inequalities(self, inequalities: List[str]) -> str:
        r"""Reduces a system of inequalities.

        Args:
            inequalities (List[str]): A list of strings representing the
                inequalities to be reduced.

        Returns:
            str: JSON string containing the reduced system of inequalities
                in the `"result"` field. The solution is represented in
                a symbolic format (e.g., combined intervals or expressions).
                If an error occurs, the JSON string will include an `"error"`
                field with the corresponding error message.
        """
        import sympy as sp

        try:
            ineqs = [sp.sympify(ineq) for ineq in inequalities]
            solution = sp.reduce_inequalities(ineqs)
            return json.dumps({"result": str(solution)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("reduce_inequalities", e)

    def polynomial_representation(self, expression: str, variable: str) -> str:
        r"""Represents an expression as a polynomial.

        Args:
            expression (str): The mathematical expression to represent as
                a polynomial, provided as a string.
            variable (str): The variable with respect to which the polynomial
                representation will be created.

        Returns:
            str: JSON string containing the polynomial representation of the
                expression in the `"result"` field. The polynomial is returned
                in a symbolic format. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """

        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            poly = sp.Poly(expr, var)
            return json.dumps({"result": str(poly)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("polynomial_representation", e)

    def polynomial_degree(self, expression: str, variable: str) -> str:
        r"""Returns the degree of a polynomial.

        Args:
            expression (str): The polynomial expression for which the degree
                is to be determined, provided as a string.
            variable (str): The variable with respect to which the degree
                of the polynomial is calculated.

        Returns:
            str: JSON string containing the degree of the polynomial in the
                `"result"` field. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            degree = int(sp.degree(expr, var))
            return json.dumps({"result": degree}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("polynomial_degree", e)

    def polynomial_coefficients(self, expression: str, variable: str) -> str:
        r"""Returns the coefficients of a polynomial.

        Args:
            expression (str): The polynomial expression from which the
                coefficients are to be extracted, provided as a string.
            variable (str): The variable with respect to which the polynomial
                coefficients are determined.

        Returns:
            str: JSON string containing the list of coefficients of the
                polynomial in the `"result"` field. The coefficients are
                ordered from the highest degree term to the constant term.
                If an error occurs, the JSON string will include an `"error"
                field with the corresponding error message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            coeffs = sp.Poly(expr, var).all_coeffs()
            return json.dumps(
                {"result": [str(coeff) for coeff in coeffs]},
                ensure_ascii=False,
            )
        except Exception as e:
            return self.handle_exception("polynomial_coefficients", e)

    def solve_equation(
        self, sympy_equation: str, variable: Optional[str] = None
    ) -> str:
        r"""Solves an equation for a specific variable.

        Args:
            sympy_equation(str): The equation to solve, must be compatible
                with SymPy, provided as a string.
            variable (str, optional): The variable to solve for. If not
                specified, the function will use the default variable.

        Returns:
            str: JSON string containing the solutions to the equation in the
                `"result"` field. Each solution is represented as a string.
                If an error occurs, the JSON string will include an `"error"`
                field with the corresponding error message.
        """
        import sympy as sp

        try:
            variable = (
                sp.symbols(variable)
                if variable
                else sp.symbols(self.default_variable)
            )
            eq = sp.sympify(sympy_equation)
            solutions = sp.solve(eq, variable)
            return json.dumps(
                {"result": [str(sol) for sol in solutions]}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("solve_equation", e)

    def find_roots(self, expression: str) -> str:
        r"""Finds the roots of a polynomial or algebraic equation.

        Args:
            expression (str): The polynomial or algebraic equation for which
                the roots are to be found, provided as a string.

        Returns:
            str: JSON string containing the roots of the expression in the
                `"result"` field. The roots are represented as a list of
                solutions. If an error occurs, the JSON string will include
                a `"status"` field set to `"error"` and a `"message"` field
                with the corresponding error description.
        """
        import sympy as sp

        try:
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            roots = sp.solve(expr)
            return json.dumps(
                {"status": "success", "result": str(roots)}, ensure_ascii=False
            )

        except Exception as e:
            return self.handle_exception("find_roots", e)

    def differentiate(
        self, expression: str, variable: Optional[str] = None
    ) -> str:
        r"""Differentiates an expression with respect to a variable.

        Args:
            expression (str): The mathematical expression to differentiate,
                provided as a string.
            variable (str, optional): The variable with respect to which the
                differentiation is performed. If not specified, the default
                variable is used.

        Returns:
            str: JSON string containing the derivative of the expression in the
                `"result"` field. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            variable = (
                sp.symbols(variable)
                if variable
                else sp.symbols(self.default_variable)
            )
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            derivative = sp.diff(expr, variable)
            return json.dumps({"result": str(derivative)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("differentiate", e)

    def integrate(
        self, expression: str, variable: Optional[str] = None
    ) -> str:
        r"""Integrates an expression with respect to a variable.

        Args:
            expression (str): The mathematical expression to integrate,
                provided as a string.
            variable (str, optional): The variable with respect to which the
                integration is performed. If not specified, the default
                variable is used.

        Returns:
            str: JSON string containing the integral of the expression in the
                `"result"` field. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            variable = (
                sp.symbols(variable)
                if variable
                else sp.symbols(self.default_variable)
            )
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            integral = sp.integrate(expr, variable)
            return json.dumps({"result": str(integral)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("integrate", e)

    def definite_integral(
        self, expression: str, variable: str, lower: float, upper: float
    ) -> str:
        r"""Computes the definite integral of an expression within given
        bounds.

        Args:
            expression (str): The mathematical expression to integrate,
                provided as a string.
            variable (str): The variable with respect to which the definite
                integration is performed.
            lower (float): The lower limit of the integration.
            upper (float): The upper limit of the integration.

        Returns:
            str: JSON string containing the result of the definite integral
                in the `"result"` field. If an error occurs, the JSON string
                will include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            integral = sp.integrate(expr, (var, lower, upper))
            return json.dumps({"result": str(integral)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("definite_integral", e)

    def series_expansion(
        self, expression: str, variable: str, point: float, order: int
    ) -> str:
        r"""Expands an expression into a Taylor series around a given point up
        to a specified order.

        Args:
            expression (str): The mathematical expression to expand, provided
                as a string.
            variable (str): The variable with respect to which the series
                expansion is performed.
            point (float): The point around which the Taylor series is
                expanded.
            order (int): The order up to which the series expansion is
            computed.

        Returns:
            str: JSON string containing the Taylor series expansion of the
                expression in the `"result"` field. If an error occurs,
                the JSON string will include an `"error"` field with the
                corresponding error message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            series = sp.series(expr, var, point, order)
            return json.dumps({"result": str(series)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("series_expansion", e)

    def compute_limit(
        self,
        expression: str,
        variable: str,
        point: float,
    ) -> str:
        r"""Computes the limit of an expression as a variable approaches
        a point.

        Args:
            expression (str): The mathematical expression for which the limit
                is to be computed, provided as a string.
            variable (str): The variable with respect to which the limit is
                computed.
            point (float): The point that the variable approaches.

        Returns:
            str: JSON string containing the computed limit of the expression
                in the `"result"` field. If an error occurs, the JSON string
                will include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            limit = sp.limit(expr, var, point)
            return json.dumps({"result": str(limit)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("compute_limit", e)

    def find_critical_points(self, expression: str, variable: str) -> str:
        r"""Finds the critical points of an expression by setting its
        derivative to zero.

        Args:
            expression (str): The mathematical expression for which critical
                points are to be found, provided as a string.
            variable (str): The variable with respect to which the critical
                points are determined.

        Returns:
            str: JSON string containing the critical points of the expression
                in the `"result"` field. The critical points are returned as a
                list of values corresponding to the variable. If an error
                occurs, the JSON string will include an `"error"` field with
                the corresponding error message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            derivative = sp.diff(expr, var)
            critical_points = sp.solve(derivative, var)
            return json.dumps(
                {"result": [str(point) for point in critical_points]},
                ensure_ascii=False,
            )
        except Exception as e:
            return self.handle_exception("find_critical_points", e)

    def check_continuity(
        self, expression: str, variable: str, point: float
    ) -> str:
        r"""Checks if an expression is continuous at a given point.

        Args:
            expression (str): The mathematical expression to check for
                continuity, provided as a string.
            variable (str): The variable with respect to which continuity
                is checked.
            point (float): The point at which the continuity of the expression
                is checked.

        Returns:
            str: JSON string containing the result of the continuity check in
                the `"result"` field. The result will be `"True"` if the
                expression is continuous at the given point, otherwise
                `"False"`. If an error occurs, the JSON string will include
                an `"error"` field with the corresponding error message.
        """
        import sympy as sp

        try:
            var = sp.symbols(variable)
            expr = sp.parsing.sympy_parser.parse_expr(expression)
            left_limit = sp.limit(expr, var, point, dir='-')
            right_limit = sp.limit(expr, var, point, dir='+')
            value_at_point = expr.subs(var, point)
            is_continuous = left_limit == right_limit == value_at_point
            return json.dumps(
                {"result": str(is_continuous)}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("check_continuity", e)

    def compute_determinant(self, matrix: List[List[float]]) -> str:
        r"""Computes the determinant of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the determinant is to be computed.

        Returns:
            str: JSON string containing the determinant of the matrix in the
                `"result"` field. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            determinant = mat.det()
            return json.dumps({"result": str(determinant)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("compute_determinant", e)

    def compute_inverse(self, matrix: List[List[float]]) -> str:
        r"""Computes the inverse of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the inverse is to be computed.

        Returns:
            str: JSON string containing the inverse of the matrix in the
                `"result"` field. The inverse is represented in a symbolic
                matrix format. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            inverse = mat.inv()
            return json.dumps({"result": str(inverse)}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("compute_inverse", e)

    def compute_eigenvalues(self, matrix: List[List[float]]) -> str:
        r"""Computes the eigenvalues of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the eigenvalues are to be computed.

        Returns:
            str: JSON string containing the eigenvalues of the matrix in the
                `"result"` field. The eigenvalues are represented as a
                dictionary where keys are the eigenvalues (as strings) and
                values are their multiplicities (as strings). If an error
                occurs, the JSON string will include an `"error"` field
                with the corresponding error message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            eigenvalues = mat.eigenvals()
            return json.dumps(
                {"result": {str(k): str(v) for k, v in eigenvalues.items()}},
                ensure_ascii=False,
            )
        except Exception as e:
            return self.handle_exception("compute_eigenvalues", e)

    def compute_eigenvectors(self, matrix: List[List[float]]) -> str:
        r"""Computes the eigenvectors of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the eigenvectors are to be computed.

        Returns:
            str: JSON string containing the eigenvectors of the matrix in the
                `"result"` field. Each eigenvalue is represented as a
                dictionary with the following keys:
                - `"eigenvalue"`: The eigenvalue (as a string).
                - `"multiplicity"`: The multiplicity of the eigenvalue
                (as an integer).
                - `"eigenvectors"`: A list of eigenvectors
                (each represented as a string).

                If an error occurs, the JSON string will include an `"error"`
                field with the corresponding error message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            eigenvectors = mat.eigenvects()
            result = [
                {
                    "eigenvalue": str(eigenvalue),
                    "multiplicity": multiplicity,
                    "eigenvectors": [str(v) for v in vectors],
                }
                for eigenvalue, multiplicity, vectors in eigenvectors
            ]
            return json.dumps({"result": result}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("compute_eigenvectors", e)

    def compute_nullspace(self, matrix: List[List[float]]) -> str:
        r"""Computes the null space of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the null space is to be computed.

        Returns:
            str: JSON string containing the null space of the matrix in the
                `"result"` field. The null space is represented as a list of
                basis vectors, where each vector is given as a string in
                symbolic format. If an error occurs, the JSON string will
                include an `"error"` field with the corresponding error
                message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            nullspace = mat.nullspace()
            return json.dumps(
                {"result": [str(vec) for vec in nullspace]}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("compute_nullspace", e)

    def compute_rank(self, matrix: List[List[float]]) -> str:
        r"""Computes the rank of a matrix.

        Args:
            matrix (List[List[float]]): A two-dimensional list representing
                the matrix for which the rank is to be computed.

        Returns:
            str: JSON string containing the rank of the matrix in the
                `"result"` field. The rank is represented as an integer.
                If an error occurs,the JSON string will include an
                `"error"` field with the corresponding error message.
        """
        import sympy as sp

        try:
            mat = sp.Matrix(matrix)
            rank = mat.rank()
            return json.dumps({"result": rank}, ensure_ascii=False)
        except Exception as e:
            return self.handle_exception("compute_rank", e)

    def compute_inner_product(
        self, vector1: List[float], vector2: List[float]
    ) -> str:
        r"""Computes the inner (dot) product of two vectors.

        Args:
            vector1 (List[float]): The first vector as a list of floats.
            vector2 (List[float]): The second vector as a list of floats.

        Returns:
            str: JSON string containing the inner product in the `"result"`
                field. If an error occurs, the JSON string will include an
                `"error"` field with the corresponding error message.

        Raises:
            ValueError: If the vectors have different dimensions.
        """
        import sympy as sp

        try:
            # Convert the lists into sympy Matrix objects (column vectors)
            v1 = sp.Matrix(vector1)
            v2 = sp.Matrix(vector2)

            # Check that the vectors have the same dimensions.
            if v1.shape != v2.shape:
                raise ValueError(
                    "Vectors must have the same dimensions to compute "
                    "the inner product."
                )

            # Compute the dot (inner) product.
            inner_product = v1.dot(v2)
            return json.dumps(
                {"result": str(inner_product)}, ensure_ascii=False
            )
        except Exception as e:
            return self.handle_exception("compute_inner_product", e)

    def handle_exception(self, func_name: str, error: Exception) -> str:
        r"""Handles exceptions by logging and returning error details.

        Args:
            func_name (str): The name of the function where the
            exception occurred.
            error (Exception): The exception object containing
            details about the error.

        Returns:
            str: JSON string containing the error details.
                The JSON includes:
                - `"status"`: Always set to `"error"`.
                - `"message"`: A string representation of the
                exception message.
        """
        logger.error(f"Error in {func_name}: {error}")
        return json.dumps(
            {"status": "error", "message": f"Error in {func_name}: {error}"},
            ensure_ascii=False,
        )

    def get_tools(self) -> List[FunctionTool]:
        r"""Exposes the tool's methods to the agent framework.

        Returns:
            List[FunctionTool]: A list of `FunctionTool` objects representing
                the toolkit's methods, making them accessible to the agent.
        """
        return [
            FunctionTool(self.simplify_expression),
            FunctionTool(self.expand_expression),
            FunctionTool(self.factor_expression),
            FunctionTool(self.solve_linear_system),
            FunctionTool(self.solve_nonlinear_system),
            FunctionTool(self.solve_univariate_inequality),
            FunctionTool(self.reduce_inequalities),
            FunctionTool(self.polynomial_representation),
            FunctionTool(self.polynomial_degree),
            FunctionTool(self.polynomial_coefficients),
            FunctionTool(self.solve_equation),
            FunctionTool(self.find_roots),
            FunctionTool(self.differentiate),
            FunctionTool(self.integrate),
            FunctionTool(self.definite_integral),
            FunctionTool(self.series_expansion),
            FunctionTool(self.compute_limit),
            FunctionTool(self.find_critical_points),
            FunctionTool(self.check_continuity),
            FunctionTool(self.compute_determinant),
            FunctionTool(self.compute_inverse),
            FunctionTool(self.compute_eigenvalues),
            FunctionTool(self.compute_eigenvectors),
            FunctionTool(self.compute_nullspace),
            FunctionTool(self.compute_rank),
            FunctionTool(self.compute_inner_product),
        ]
