enkly-ai/pkg/mathkit/solve.go

package mathkit

import (
	"fmt"
	"math"
	"sort"
	"strings"
)

// Solve dispatches a math problem by string operation name against a
// loosely-typed params map — exactly the shape a JSON object (an LLM
// tool-call argument blob, decoded with encoding/json into
// map[string]any) takes once decoded. It exists as one layer above
// the typed functions in linalg.go/calculus.go/statistics.go/
// optimize.go/ml.go specifically so a caller at the JSON boundary
// (services/agent/internal/infrastructure/toolexec/mlmath.go) has one
// function to call and one error type to handle, instead of a type
// switch per operation.
//
// Returns a human-readable report (not raw JSON or a bare float) on
// success, because the caller here is ultimately an LLM deciding what
// to do next — a labeled, explained answer is directly usable in its
// response, where a bare number would have to be re-explained.
func Solve(operation string, params map[string]any) (string, error) {
	op := strings.ToLower(strings.TrimSpace(operation))
	switch op {
	// --- general ---
	case "evaluate":
		return solveEvaluate(params)

	// --- linear algebra ---
	case "matrix_add", "matrix_sub", "matrix_mul":
		return solveMatrixBinOp(op, params)
	case "matrix_transpose":
		return solveMatrixTranspose(params)
	case "matrix_determinant":
		return solveMatrixDeterminant(params)
	case "matrix_inverse":
		return solveMatrixInverse(params)
	case "matrix_rank":
		return solveMatrixRank(params)
	case "matrix_trace":
		return solveMatrixTrace(params)
	case "dot_product":
		return solveDotProduct(params)
	case "vector_norm":
		return solveVectorNorm(params)
	case "dominant_eigen":
		return solveDominantEigen(params)

	// --- calculus ---
	case "derivative":
		return solveDerivative(params)
	case "gradient":
		return solveGradient(params)
	case "integral":
		return solveIntegral(params)

	// --- optimization ---
	case "gradient_descent":
		return solveGradientDescent(params)
	case "newton_root":
		return solveNewtonRoot(params)

	// --- statistics & probability ---
	case "mean":
		return solveReduce1(params, "mean", func(d []float64) (float64, error) { return Mean(d) })
	case "variance":
		return solveReduce1Pop(params, "variance", Variance)
	case "std_dev":
		return solveReduce1Pop(params, "std_dev", StdDev)
	case "median":
		return solveReduce1(params, "median", Median)
	case "covariance":
		return solveReduce2Pop(params, "covariance", Covariance)
	case "correlation":
		return solveReduce2(params, "correlation", Correlation)
	case "z_score_normalize":
		return solveNormalize(params, "z_score_normalize", ZScoreNormalize)
	case "min_max_normalize":
		return solveNormalize(params, "min_max_normalize", MinMaxNormalize)
	case "normal_pdf":
		return solveNormalDist(params, "normal_pdf", NormalPDF)
	case "normal_cdf":
		return solveNormalDist(params, "normal_cdf", NormalCDF)
	case "binomial_pmf":
		return solveBinomialPMF(params)

	// --- ML primitives ---
	case "sigmoid":
		return solveElementwise(params, "sigmoid", Sigmoid)
	case "relu":
		return solveElementwise(params, "relu", ReLU)
	case "tanh":
		return solveElementwise(params, "tanh", math.Tanh)
	case "softmax":
		return solveSoftmax(params)
	case "mse_loss":
		return solveLoss(params, "mse_loss", MSELoss)
	case "cross_entropy_loss":
		return solveLoss(params, "cross_entropy_loss", CrossEntropyLoss)
	case "linear_regression":
		return solveLinearRegression(params)

	default:
		return "", fmt.Errorf("unknown operation %q — see the tool description for the full list of supported operations", operation)
	}
}

// ---------- param extraction helpers ----------
//
// Every helper below reports a specific, actionable error (which
// field was wrong and why) rather than a generic type-assertion
// panic recovery message, because these errors are fed straight back
// to the calling model as the tool result — see toolexec's rpcFail /
// IsError convention — and "field X must be a number, got a string"
// is something the model can act on; "interface conversion failed"
// is not.

func reqFloat(params map[string]any, key string) (float64, error) {
	v, ok := params[key]
	if !ok {
		return 0, fmt.Errorf("missing required field %q", key)
	}
	f, ok := toFloat(v)
	if !ok {
		return 0, fmt.Errorf("field %q must be a number", key)
	}
	return f, nil
}

func optFloat(params map[string]any, key string, fallback float64) float64 {
	v, ok := params[key]
	if !ok {
		return fallback
	}
	if f, ok := toFloat(v); ok {
		return f
	}
	return fallback
}

func optInt(params map[string]any, key string, fallback int) int {
	v, ok := params[key]
	if !ok {
		return fallback
	}
	if f, ok := toFloat(v); ok {
		return int(f)
	}
	return fallback
}

func optBool(params map[string]any, key string, fallback bool) bool {
	v, ok := params[key]
	if !ok {
		return fallback
	}
	if b, ok := v.(bool); ok {
		return b
	}
	return fallback
}

func toFloat(v any) (float64, bool) {
	switch n := v.(type) {
	case float64:
		return n, true
	case int:
		return float64(n), true
	case int64:
		return float64(n), true
	}
	return 0, false
}

func reqString(params map[string]any, key string) (string, error) {
	v, ok := params[key]
	if !ok {
		return "", fmt.Errorf("missing required field %q", key)
	}
	s, ok := v.(string)
	if !ok || strings.TrimSpace(s) == "" {
		return "", fmt.Errorf("field %q must be a non-empty string", key)
	}
	return s, nil
}

func optString(params map[string]any, key, fallback string) string {
	v, ok := params[key]
	if !ok {
		return fallback
	}
	s, ok := v.(string)
	if !ok {
		return fallback
	}
	return s
}

func reqFloatSlice(params map[string]any, key string) ([]float64, error) {
	v, ok := params[key]
	if !ok {
		return nil, fmt.Errorf("missing required field %q (expected an array of numbers)", key)
	}
	raw, ok := v.([]any)
	if !ok {
		return nil, fmt.Errorf("field %q must be an array of numbers", key)
	}
	out := make([]float64, len(raw))
	for i, x := range raw {
		f, ok := toFloat(x)
		if !ok {
			return nil, fmt.Errorf("field %q: element %d is not a number", key, i)
		}
		out[i] = f
	}
	return out, nil
}

func reqStringSlice(params map[string]any, key string) ([]string, error) {
	v, ok := params[key]
	if !ok {
		return nil, fmt.Errorf("missing required field %q (expected an array of strings)", key)
	}
	raw, ok := v.([]any)
	if !ok {
		return nil, fmt.Errorf("field %q must be an array of strings", key)
	}
	out := make([]string, len(raw))
	for i, x := range raw {
		s, ok := x.(string)
		if !ok {
			return nil, fmt.Errorf("field %q: element %d is not a string", key, i)
		}
		out[i] = s
	}
	return out, nil
}

func reqMatrix(params map[string]any, key string) (Matrix, error) {
	v, ok := params[key]
	if !ok {
		return nil, fmt.Errorf("missing required field %q (expected a 2D array of numbers)", key)
	}
	rows, ok := v.([]any)
	if !ok {
		return nil, fmt.Errorf("field %q must be a 2D array of numbers, e.g. [[1,2],[3,4]]", key)
	}
	m := make(Matrix, len(rows))
	for i, r := range rows {
		rowRaw, ok := r.([]any)
		if !ok {
			return nil, fmt.Errorf("field %q: row %d is not an array", key, i)
		}
		row := make([]float64, len(rowRaw))
		for j, x := range rowRaw {
			f, ok := toFloat(x)
			if !ok {
				return nil, fmt.Errorf("field %q: row %d, column %d is not a number", key, i, j)
			}
			row[j] = f
		}
		m[i] = row
	}
	return m, nil
}

// varMap builds the variable bindings an expression needs from an
// "at" (or "variables") object field — {"x": 1, "y": 2} — falling
// back to an empty map if the field is absent (a single-variable
// expression evaluated via the "variable"/"at" pair still works).
func varMap(params map[string]any, key string) (map[string]float64, error) {
	v, ok := params[key]
	if !ok {
		return map[string]float64{}, nil
	}
	raw, ok := v.(map[string]any)
	if !ok {
		return nil, fmt.Errorf("field %q must be an object mapping variable names to numbers, e.g. {\"x\": 1.5}", key)
	}
	out := make(map[string]float64, len(raw))
	for k, x := range raw {
		f, ok := toFloat(x)
		if !ok {
			return nil, fmt.Errorf("field %q: value for %q is not a number", key, k)
		}
		out[k] = f
	}
	return out, nil
}

func parseExprField(params map[string]any) (*Expr, error) {
	src, err := reqString(params, "expression")
	if err != nil {
		return nil, err
	}
	expr, err := ParseExpr(src)
	if err != nil {
		return nil, err
	}
	return expr, nil
}

func fmtFloat(f float64) string {
	if math.IsNaN(f) {
		return "NaN"
	}
	if math.IsInf(f, 1) {
		return "+Inf"
	}
	if math.IsInf(f, -1) {
		return "-Inf"
	}
	return strings.TrimRight(strings.TrimRight(fmt.Sprintf("%.10f", f), "0"), ".")
}

func fmtFloats(fs []float64) string {
	parts := make([]string, len(fs))
	for i, f := range fs {
		parts[i] = fmtFloat(f)
	}
	return "[" + strings.Join(parts, ", ") + "]"
}

func fmtMatrix(m Matrix) string {
	var sb strings.Builder
	for _, row := range m {
		sb.WriteString(fmtFloats(row))
		sb.WriteByte('\n')
	}
	return strings.TrimRight(sb.String(), "\n")
}

// ---------- operation implementations ----------

func solveEvaluate(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	vars, err := varMap(params, "variables")
	if err != nil {
		return "", err
	}
	result, err := expr.Eval(vars)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s = %s", expr.String(), fmtFloat(result)), nil
}

func solveMatrixBinOp(op string, params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	b, err := reqMatrix(params, "b")
	if err != nil {
		return "", err
	}
	var out Matrix
	switch op {
	case "matrix_add":
		out, err = MatAdd(a, b)
	case "matrix_sub":
		out, err = MatSub(a, b)
	case "matrix_mul":
		out, err = MatMul(a, b)
	}
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s result:\n%s", op, fmtMatrix(out)), nil
}

func solveMatrixTranspose(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	out, err := Transpose(a)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("transpose result:\n%s", fmtMatrix(out)), nil
}

func solveMatrixDeterminant(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	det, err := Determinant(a)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("det(A) = %s", fmtFloat(det)), nil
}

func solveMatrixInverse(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	inv, err := Inverse(a)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("A^-1:\n%s", fmtMatrix(inv)), nil
}

func solveMatrixRank(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	r, err := Rank(a)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("rank(A) = %d", r), nil
}

func solveMatrixTrace(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	tr, err := Trace(a)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("trace(A) = %s", fmtFloat(tr)), nil
}

func solveDotProduct(params map[string]any) (string, error) {
	a, err := reqFloatSlice(params, "a")
	if err != nil {
		return "", err
	}
	b, err := reqFloatSlice(params, "b")
	if err != nil {
		return "", err
	}
	d, err := Dot(a, b)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("a · b = %s", fmtFloat(d)), nil
}

func solveVectorNorm(params map[string]any) (string, error) {
	a, err := reqFloatSlice(params, "a")
	if err != nil {
		return "", err
	}
	p := optFloat(params, "p", 2)
	n := Norm(a, p)
	label := fmt.Sprintf("L%g", p)
	if math.IsInf(p, 1) {
		label = "L∞"
	}
	return fmt.Sprintf("%s norm = %s", label, fmtFloat(n)), nil
}

func solveDominantEigen(params map[string]any) (string, error) {
	a, err := reqMatrix(params, "a")
	if err != nil {
		return "", err
	}
	iters := optInt(params, "iterations", 0)
	lambda, v, err := DominantEigen(a, iters)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("dominant eigenvalue ≈ %s\neigenvector ≈ %s", fmtFloat(lambda), fmtFloats(v)), nil
}

func solveDerivative(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	variable, err := reqString(params, "variable")
	if err != nil {
		return "", err
	}
	at, err := varMap(params, "at")
	if err != nil {
		return "", err
	}
	if _, ok := at[variable]; !ok {
		at[variable] = optFloat(params, "value", 0)
	}
	h := optFloat(params, "h", 0)
	d, err := Derivative(expr, variable, at, h)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("d/d%s[%s] at %s=%s ≈ %s", variable, expr.String(), variable, fmtFloat(at[variable]), fmtFloat(d)), nil
}

func solveGradient(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	variables, err := reqStringSlice(params, "variables")
	if err != nil {
		return "", err
	}
	at, err := varMap(params, "at")
	if err != nil {
		return "", err
	}
	h := optFloat(params, "h", 0)
	grad, err := Gradient(expr, variables, at, h)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("∇[%s] with respect to %s ≈ %s", expr.String(), strings.Join(variables, ","), fmtFloats(grad)), nil
}

func solveIntegral(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	variable, err := reqString(params, "variable")
	if err != nil {
		return "", err
	}
	from, err := reqFloat(params, "from")
	if err != nil {
		return "", err
	}
	to, err := reqFloat(params, "to")
	if err != nil {
		return "", err
	}
	steps := optInt(params, "steps", 0)
	fixed, err := varMap(params, "variables")
	if err != nil {
		return "", err
	}
	result, err := Integrate(expr, variable, from, to, steps, fixed)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("∫[%s to %s] %s d%s ≈ %s", fmtFloat(from), fmtFloat(to), expr.String(), variable, fmtFloat(result)), nil
}

func solveGradientDescent(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	variables, err := reqStringSlice(params, "variables")
	if err != nil {
		return "", err
	}
	start, err := reqFloatSlice(params, "start")
	if err != nil {
		return "", err
	}
	lr, err := reqFloat(params, "learning_rate")
	if err != nil {
		return "", err
	}
	iterations := optInt(params, "iterations", 100)
	tol := optFloat(params, "tolerance", 1e-8)
	res, err := GradientDescent(expr, variables, start, lr, iterations, tol)
	if err != nil {
		return "", err
	}
	last := len(res.Path) - 1
	var sb strings.Builder
	fmt.Fprintf(&sb, "gradient descent on f(%s) = %s\n", strings.Join(variables, ","), expr.String())
	fmt.Fprintf(&sb, "start: %s -> f = %s\n", fmtFloats(res.Path[0]), fmtFloat(res.Values[0]))
	fmt.Fprintf(&sb, "ran %d step(s), converged=%v\n", last, res.Converged)
	fmt.Fprintf(&sb, "final: %s -> f = %s\n", fmtFloats(res.Path[last]), fmtFloat(res.Values[last]))
	// Show a short trajectory sample so the model can see the descent
	// shape without a huge wall of numbers for large iteration counts.
	sampleN := 5
	if last+1 <= sampleN*2 {
		for i := 0; i <= last; i++ {
			fmt.Fprintf(&sb, "  step %d: x=%s f=%s\n", i, fmtFloats(res.Path[i]), fmtFloat(res.Values[i]))
		}
	} else {
		for i := 0; i < sampleN; i++ {
			fmt.Fprintf(&sb, "  step %d: x=%s f=%s\n", i, fmtFloats(res.Path[i]), fmtFloat(res.Values[i]))
		}
		sb.WriteString("  ...\n")
		for i := last - sampleN + 1; i <= last; i++ {
			fmt.Fprintf(&sb, "  step %d: x=%s f=%s\n", i, fmtFloats(res.Path[i]), fmtFloat(res.Values[i]))
		}
	}
	return strings.TrimRight(sb.String(), "\n"), nil
}

func solveNewtonRoot(params map[string]any) (string, error) {
	expr, err := parseExprField(params)
	if err != nil {
		return "", err
	}
	variable, err := reqString(params, "variable")
	if err != nil {
		return "", err
	}
	start, err := reqFloat(params, "start")
	if err != nil {
		return "", err
	}
	iterations := optInt(params, "iterations", 0)
	tol := optFloat(params, "tolerance", 0)
	fixed, err := varMap(params, "variables")
	if err != nil {
		return "", err
	}
	res, err := NewtonRoot(expr, variable, start, iterations, tol, fixed)
	if err != nil {
		return "", err
	}
	last := res.Path[len(res.Path)-1]
	return fmt.Sprintf("newton's method on %s(%s)=0: converged=%v after %d step(s), root ≈ %s=%s",
		expr.String(), variable, res.Converged, len(res.Path)-1, variable, fmtFloat(last)), nil
}

func solveReduce1(params map[string]any, name string, f func([]float64) (float64, error)) (string, error) {
	data, err := reqFloatSlice(params, "data")
	if err != nil {
		return "", err
	}
	v, err := f(data)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s(%s) = %s", name, fmtFloats(data), fmtFloat(v)), nil
}

func solveReduce1Pop(params map[string]any, name string, f func([]float64, bool) (float64, error)) (string, error) {
	data, err := reqFloatSlice(params, "data")
	if err != nil {
		return "", err
	}
	population := optBool(params, "population", false)
	v, err := f(data, population)
	if err != nil {
		return "", err
	}
	kind := "sample"
	if population {
		kind = "population"
	}
	return fmt.Sprintf("%s %s(%s) = %s", kind, name, fmtFloats(data), fmtFloat(v)), nil
}

func solveReduce2(params map[string]any, name string, f func([]float64, []float64) (float64, error)) (string, error) {
	x, err := reqFloatSlice(params, "x")
	if err != nil {
		return "", err
	}
	y, err := reqFloatSlice(params, "y")
	if err != nil {
		return "", err
	}
	v, err := f(x, y)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s(x, y) = %s", name, fmtFloat(v)), nil
}

func solveReduce2Pop(params map[string]any, name string, f func([]float64, []float64, bool) (float64, error)) (string, error) {
	x, err := reqFloatSlice(params, "x")
	if err != nil {
		return "", err
	}
	y, err := reqFloatSlice(params, "y")
	if err != nil {
		return "", err
	}
	population := optBool(params, "population", false)
	v, err := f(x, y, population)
	if err != nil {
		return "", err
	}
	kind := "sample"
	if population {
		kind = "population"
	}
	return fmt.Sprintf("%s %s(x, y) = %s", kind, name, fmtFloat(v)), nil
}

func solveNormalize(params map[string]any, name string, f func([]float64) ([]float64, error)) (string, error) {
	data, err := reqFloatSlice(params, "data")
	if err != nil {
		return "", err
	}
	out, err := f(data)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s(%s) = %s", name, fmtFloats(data), fmtFloats(out)), nil
}

func solveNormalDist(params map[string]any, name string, f func(float64, float64, float64) (float64, error)) (string, error) {
	x, err := reqFloat(params, "x")
	if err != nil {
		return "", err
	}
	mean := optFloat(params, "mean", 0)
	std := optFloat(params, "std_dev", 1)
	v, err := f(x, mean, std)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s(x=%s, mean=%s, std_dev=%s) = %s", name, fmtFloat(x), fmtFloat(mean), fmtFloat(std), fmtFloat(v)), nil
}

func solveBinomialPMF(params map[string]any) (string, error) {
	k := optInt(params, "k", -1)
	if k < 0 {
		return "", fmt.Errorf("missing required field %q", "k")
	}
	n := optInt(params, "n", -1)
	if n < 0 {
		return "", fmt.Errorf("missing required field %q", "n")
	}
	p, err := reqFloat(params, "p")
	if err != nil {
		return "", err
	}
	v, err := BinomialPMF(k, n, p)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("P(X=%d) for X~Binomial(n=%d, p=%s) = %s", k, n, fmtFloat(p), fmtFloat(v)), nil
}

func solveElementwise(params map[string]any, name string, f func(float64) float64) (string, error) {
	if raw, ok := params["x"].([]any); ok {
		data := make([]float64, len(raw))
		for i, v := range raw {
			fv, ok := toFloat(v)
			if !ok {
				return "", fmt.Errorf("field \"x\": element %d is not a number", i)
			}
			data[i] = fv
		}
		out := make([]float64, len(data))
		for i, v := range data {
			out[i] = f(v)
		}
		return fmt.Sprintf("%s(%s) = %s", name, fmtFloats(data), fmtFloats(out)), nil
	}
	x, err := reqFloat(params, "x")
	if err != nil {
		return "", fmt.Errorf(`field "x" must be a number or an array of numbers: %w`, err)
	}
	return fmt.Sprintf("%s(%s) = %s", name, fmtFloat(x), fmtFloat(f(x))), nil
}

func solveSoftmax(params map[string]any) (string, error) {
	x, err := reqFloatSlice(params, "x")
	if err != nil {
		return "", err
	}
	out := Softmax(x)
	sum := 0.0
	for _, v := range out {
		sum += v
	}
	return fmt.Sprintf("softmax(%s) = %s (sums to %s)", fmtFloats(x), fmtFloats(out), fmtFloat(sum)), nil
}

func solveLoss(params map[string]any, name string, f func([]float64, []float64) (float64, error)) (string, error) {
	pred, err := reqFloatSlice(params, "predictions")
	if err != nil {
		return "", err
	}
	target, err := reqFloatSlice(params, "targets")
	if err != nil {
		return "", err
	}
	v, err := f(pred, target)
	if err != nil {
		return "", err
	}
	return fmt.Sprintf("%s(predictions, targets) = %s", name, fmtFloat(v)), nil
}

func solveLinearRegression(params map[string]any) (string, error) {
	X, err := reqMatrix(params, "x")
	if err != nil {
		return "", err
	}
	y, err := reqFloatSlice(params, "y")
	if err != nil {
		return "", err
	}
	res, err := LinearRegression(X, y)
	if err != nil {
		return "", err
	}
	var sb strings.Builder
	fmt.Fprintf(&sb, "ordinary least squares fit: y ≈ %s", fmtFloat(res.Coefficients[0]))
	for i, c := range res.Coefficients[1:] {
		fmt.Fprintf(&sb, " + %s*x%d", fmtFloat(c), i+1)
	}
	fmt.Fprintf(&sb, "\nR² = %s\n", fmtFloat(res.RSquared))
	fmt.Fprintf(&sb, "predictions: %s\n", fmtFloats(res.Predictions))
	fmt.Fprintf(&sb, "residuals: %s", fmtFloats(res.Residuals))
	return sb.String(), nil
}

// Operations returns the sorted list of every operation name Solve
// accepts — used by the agent's tool-catalog description so the
// supported operation list is generated from the real dispatch table
// instead of hand-copied prose that can drift out of sync with it.
func Operations() []string {
	ops := []string{
		"evaluate",
		"matrix_add", "matrix_sub", "matrix_mul", "matrix_transpose", "matrix_determinant",
		"matrix_inverse", "matrix_rank", "matrix_trace", "dot_product", "vector_norm", "dominant_eigen",
		"derivative", "gradient", "integral",
		"gradient_descent", "newton_root",
		"mean", "variance", "std_dev", "median", "covariance", "correlation",
		"z_score_normalize", "min_max_normalize", "normal_pdf", "normal_cdf", "binomial_pmf",
		"sigmoid", "relu", "tanh", "softmax", "mse_loss", "cross_entropy_loss", "linear_regression",
	}
	sort.Strings(ops)
	return ops
}