// Go实现：AlphaEvolve的核心进化循环

package alphaevolve

import (
	"context"
	"fmt"
	"math/rand"
	"sort"
	"time"
)

// Candidate 表示一个候选程序
type Candidate struct {
	ID        string
	Code      string
	Score     float64
	Metrics   ProgramMetrics
	Generation int
	ParentID  string
}

// ProgramMetrics 程序性能指标
type ProgramMetrics struct {
	Correctness   float64 // 功能正确性 0-1
	Speed         float64 // 运行效率 0-1
	MemoryUsage   float64 // 内存占用 0-1
	Maintainability float64 // 代码可维护性 0-1
}

// AlphaEvolveEngine 进化引擎
type AlphaEvolveEngine struct {
	population    []Candidate
	populationSize int
	llm           *GeminiLLM
	evaluator     *ProgramEvaluator
	programDB     *ProgramDatabase
}

// GeminiLLM 模拟Gemini大语言模型
type GeminiLLM struct {
	flashMode bool // true=Gemini Flash, false=Gemini Pro
}

// ProgramEvaluator 程序评估器
type ProgramEvaluator struct{}

// ProgramDatabase 候选程序数据库
type ProgramDatabase struct {
	programs []Candidate
}

// NewAlphaEvolveEngine 创建AlphaEvolve引擎
func NewAlphaEvolveEngine(popSize int) *AlphaEvolveEngine {
	return &AlphaEvolveEngine{
		populationSize: popSize,
		llm:            &GeminiLLM{},
		evaluator:      &ProgramEvaluator{},
		programDB:      &ProgramDatabase{},
	}
}

// Evolve 执行进化循环
func (e *AlphaEvolveEngine) Evolve(ctx context.Context, problem string, generations int) (*Candidate, error) {
	fmt.Printf("开始进化优化: %s (%d 代)\n", problem, generations)

	// 第1步：Gemini Flash生成初始种群
	e.llm.flashMode = true
	initialCodes := e.llm.GenerateMany(problem, e.populationSize)
	
	for i, code := range initialCodes {
		candidate := Candidate{
			ID:        fmt.Sprintf("gen0-%d", i),
			Code:      code,
			Generation: 0,
		}
		e.population = append(e.population, candidate)
	}

	// 第2-4步：测试→评分→进化，循环迭代
	for gen := 0; gen < generations; gen++ {
		fmt.Printf("\n=== 第 %d 代 ===\n", gen+1)

		// 测试 + 评分
		for i := range e.population {
			if e.population[i].Generation == gen {
				metrics := e.evaluator.Evaluate(e.population[i].Code)
				e.population[i].Metrics = metrics
				e.population[i].Score = e.calculateScore(metrics)
			}
		}

		// 按分数排序
		sort.Slice(e.population, func(i, j int) bool {
			return e.population[i].Score > e.population[j].Score
		})

		// 保留Top 10%作为精英
		eliteCount := e.populationSize / 10
		elites := e.population[:eliteCount]

		// 存入数据库
		for _, c := range elites {
			e.programDB.Add(c)
		}

		// 如果达到目标分数，提前结束
		if elites[0].Score > 0.99 {
			fmt.Printf("在第 %d 代达到目标!\n", gen+1)
			return &elites[0], nil
		}

		// 进化：精英进入下一代，其他由LLM变异生成
		e.llm.flashMode = gen%3 == 0 // 每3代用一次Flash模式
		nextGen := e.evolvePopulation(elites, problem, gen+1)
		e.population = nextGen
	}

	// 返回最优解
	sort.Slice(e.population, func(i, j int) bool {
		return e.population[i].Score > e.population[j].Score
	})
	return &e.population[0], nil
}

// evolvePopulation 使用LLM进行种群进化
func (e *AlphaEvolveEngine) evolvePopulation(elites []Candidate, problem string, nextGen int) []Candidate {
	var newPopulation []Candidate

	// 精英直接保留
	for _, elite := range elites {
		newPopulation = append(newPopulation, Candidate{
			ID:        fmt.Sprintf("gen%d-elite-%s", nextGen, elite.ID),
			Code:      elite.Code,
			Generation: nextGen,
			ParentID:  elite.ID,
		})
	}

	// 通过LLM变异生成新个体
	remaining := e.populationSize - len(newPopulation)
	for i := 0; i < remaining; i++ {
		parent := elites[rand.Intn(len(elites))]
		mutatedCode := e.llm.Mutate(problem, parent.Code)
		newPopulation = append(newPopulation, Candidate{
			ID:        fmt.Sprintf("gen%d-%d", nextGen, i),
			Code:      mutatedCode,
			Generation: nextGen,
			ParentID:  parent.ID,
		})
	}

	return newPopulation
}

func (e *AlphaEvolveEngine) calculateScore(m ProgramMetrics) float64 {
	// 加权评分：正确性 > 速度 > 可维护性 > 内存
	return m.Correctness*0.4 + m.Speed*0.3 + m.Maintainability*0.2 + m.MemoryUsage*0.1
}

// GenerateMany 生成多个候选程序
func (g *GeminiLLM) GenerateMany(problem string, count int) []string {
	codes := make([]string, count)
	for i := 0; i < count; i++ {
		codes[i] = fmt.Sprintf("// %s 的候选方案 %d\nfunc solve() { ... }", problem, i)
	}
	return codes
}

// Mutate 对程序进行语义有意义的变异
func (g *GeminiLLM) Mutate(problem string, code string) string {
	// 变异方式：重构循环、替换算法、调整数据结构
	mutations := []string{
		"// 重构循环，使用并行计算",
		"// 替换为更高效的算法",
		"// 优化数据结构",
		"// 减少内存分配",
	}
	return code + "\n" + mutations[rand.Intn(len(mutations))]
}

// Evaluate 评估程序
func (e *ProgramEvaluator) Evaluate(code string) ProgramMetrics {
	time.Sleep(10 * time.Millisecond) // 模拟评估延迟
	return ProgramMetrics{
		Correctness:   0.7 + rand.Float64()*0.3,
		Speed:         0.5 + rand.Float64()*0.5,
		MemoryUsage:   0.6 + rand.Float64()*0.4,
		Maintainability: 0.7 + rand.Float64()*0.3,
	}
}

// Add 添加程序到数据库
func (db *ProgramDatabase) Add(c Candidate) {
	db.programs = append(db.programs, c)
	if len(db.programs) > 1000 {
		db.programs = db.programs[1:]
	}
}

func main() {
	ctx := context.Background()
	engine := NewAlphaEvolveEngine(100)

	// 优化4×4复数矩阵乘法
	result, err := engine.Evolve(ctx, "优化4×4复数矩阵乘法，减少标量乘法次数", 50)
	if err != nil {
		panic(err)
	}
	
	fmt.Printf("\n最优解: ID=%s, Score=%.4f\n", result.ID, result.Score)
	fmt.Printf("代码:\n%s\n", result.Code)
}