synthia-ai-system
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Synthia Engine AI - 集成LLM的智能构建优化建议
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OpenAI from 'openai';\nimport chalk from 'chalk';\nimport ora from 'ora';\nimport type { AIOptimizerConfig, LLMResponse, AIPrompt } from './types';\n\nexport class LLMClient {\n private client: OpenAI;\n private config: AIOptimizerConfig;\n private spinner = ora();\n\n constructor(config: AIOptimizerConfig) {\n this.config = config;\n this.client = new OpenAI({\n apiKey: config.openai.apiKey,\n baseURL: config.openai.baseURL,\n });\n }\n\n /**\n * 发送提示到LLM\n */\n async sendPrompt(prompt: AIPrompt): Promise<LLMResponse> {\n this.spinner.start(`发送${prompt.type}提示到LLM...`);\n\n const startTime = Date.now();\n\n try {\n const messages = this.buildMessages(prompt);\n\n const response = await this.client.chat.completions.create({\n model: this.config.openai.model || 'gpt-4',\n messages,\n max_tokens: this.config.openai.maxTokens || 4000,\n temperature: this.config.openai.temperature || 0.1,\n });\n\n const endTime = Date.now();\n const responseTime = endTime - startTime;\n\n const llmResponse: LLMResponse = {\n content: response.choices[0]?.message?.content || '',\n model: response.model,\n tokens: {\n prompt: response.usage?.prompt_tokens || 0,\n completion: response.usage?.completion_tokens || 0,\n total: response.usage?.total_tokens || 0,\n },\n responseTime,\n success: true,\n };\n\n this.spinner.succeed(`LLM响应接收完成 (${responseTime}ms)`);\n return llmResponse;\n } catch (error) {\n const endTime = Date.now();\n const responseTime = endTime - startTime;\n\n this.spinner.fail(`LLM请求失败 (${responseTime}ms)`);\n console.error(chalk.red('LLM错误:'), error);\n\n return {\n content: '',\n model: this.config.openai.model || 'gpt-4',\n tokens: { prompt: 0, completion: 0, total: 0 },\n responseTime,\n success: false,\n error: error instanceof Error ? error.message : 'Unknown error',\n };\n }\n }\n\n /**\n * 分析代码\n */\n async analyzeCode(\n code: string,\n filePath: string,\n context: any\n ): Promise<LLMResponse> {\n const prompt: AIPrompt = {\n type: 'analysis',\n content: this.buildCodeAnalysisPrompt(code, filePath),\n context,\n input: { code },\n expectedFormat: 'json',\n };\n\n return this.sendPrompt(prompt);\n }\n\n /**\n * 生成优化建议\n */\n async generateOptimizationSuggestions(\n analysisResult: any,\n context: any\n ): Promise<LLMResponse> {\n const prompt: AIPrompt = {\n type: 'optimization',\n content: this.buildOptimizationPrompt(analysisResult),\n context,\n input: { stats: analysisResult },\n expectedFormat: 'json',\n };\n\n return this.sendPrompt(prompt);\n }\n\n /**\n * 解释优化建议\n */\n async explainOptimization(\n suggestion: any,\n context: any\n ): Promise<LLMResponse> {\n const prompt: AIPrompt = {\n type: 'explanation',\n content: this.buildExplanationPrompt(suggestion),\n context,\n input: { config: suggestion },\n expectedFormat: 'markdown',\n };\n\n return this.sendPrompt(prompt);\n }\n\n /**\n * 代码审查\n */\n async reviewCode(\n code: string,\n filePath: string,\n context: any\n ): Promise<LLMResponse> {\n const prompt: AIPrompt = {\n type: 'code-review',\n content: this.buildCodeReviewPrompt(code, filePath),\n context,\n input: { code },\n expectedFormat: 'json',\n };\n\n return this.sendPrompt(prompt);\n }\n\n /**\n * 构建消息\n */\n private buildMessages(\n prompt: AIPrompt\n ): OpenAI.Chat.Completions.ChatCompletionMessageParam[] {\n const systemMessage = this.getSystemMessage(prompt.type);\n const userMessage = this.buildUserMessage(prompt);\n\n return [\n { role: 'system', content: systemMessage },\n { role: 'user', content: userMessage },\n ];\n }\n\n /**\n * 获取系统消息\n */\n private getSystemMessage(type: string): string {\n const baseSystemMessage = `你是一个专业的前端工程化专家，专门帮助优化前端项目的构建性能、代码质量和开发体验。\n\n你的任务是根据用户提供的代码、配置和项目信息，提供专业的分析和优化建议。\n\n请确保你的建议：\n1. 基于最佳实践和行业标准\n2. 考虑项目的具体技术栈和约束\n3. 提供可操作的具体步骤\n4. 评估风险和收益\n5. 提供替代方案\n\n请用中文回复，并使用JSON格式输出结构化的结果。`;\n\n switch (type) {\n case 'analysis':\n return (\n baseSystemMessage + '\\n\\n请分析代码的性能、可维护性和最佳实践问题。'\n );\n case 'optimization':\n return baseSystemMessage + '\\n\\n请提供具体的优化建议和实施步骤。';\n case 'explanation':\n return baseSystemMessage + '\\n\\n请详细解释优化建议的原理和实施方法。';\n case 'code-review':\n return baseSystemMessage + '\\n\\n请进行代码审查，指出问题和改进建议。';\n default:\n return baseSystemMessage;\n }\n }\n\n /**\n * 构建用户消息\n */\n private buildUserMessage(prompt: AIPrompt): string {\n let message = prompt.content;\n\n if (prompt.input.code) {\n message += `\\n\\n代码内容:\\n\\`\\`\\`\\n${prompt.input.code}\\n\\`\\`\\``;\n }\n\n if (prompt.input.config) {\n message += `\\n\\n配置信息:\\n\\`\\`\\`json\\n${JSON.stringify(prompt.input.config, null, 2)}\\n\\`\\`\\``;\n }\n\n if (prompt.input.stats) {\n message += `\\n\\n统计信息:\\n\\`\\`\\`json\\n${JSON.stringify(prompt.input.stats, null, 2)}\\n\\`\\`\\``;\n }\n\n if (prompt.context) {\n message += `\\n\\n项目上下文:\\n\\`\\`\\`json\\n${JSON.stringify(prompt.context, null, 2)}\\n\\`\\`\\``;\n }\n\n return message;\n }\n\n /**\n * 构建代码分析提示\n */\n private buildCodeAnalysisPrompt(_code: string, filePath: string): string {\n return `请分析以下代码文件，识别性能问题、可维护性问题和最佳实践违规：\n\n文件路径: ${filePath}\n文件类型: ${this.getFileType(filePath)}\n\n请重点关注：\n1. 性能优化机会\n2. 代码质量问题\n3. 最佳实践违规\n4. 潜在的安全问题\n5. 可维护性改进\n\n请以JSON格式返回分析结果，包含问题列表和优化建议。`;\n }\n\n /**\n * 构建优化提示\n */\n private buildOptimizationPrompt(analysisResult: any): string {\n return `基于以下分析结果，请提供具体的优化建议：\n\n${JSON.stringify(analysisResult, null, 2)}\n\n请为每个问题提供：\n1. 具体的解决方案\n2. 实施步骤\n3. 预期收益\n4. 风险评估\n5. 替代方案\n\n请以JSON格式返回优化建议。`;\n }\n\n /**\n * 构建解释提示\n */\n private buildExplanationPrompt(suggestion: any): string {\n return `请详细解释以下优化建议：\n\n${JSON.stringify(suggestion, null, 2)}\n\n请包括：\n1. 为什么这个优化是有效的\n2. 如何实施这个优化\n3. 可能遇到的问题和解决方案\n4. 相关的技术背景知识\n5. 进一步的优化建议\n\n请用Markdown格式返回详细解释。`;\n }\n\n /**\n * 构建代码审查提示\n */\n private buildCodeReviewPrompt(_code: string, filePath: string): string {\n return `请对以下代码进行全面的代码审查：\n\n文件路径: ${filePath}\n\n请检查：\n1. 代码风格和规范\n2. 性能问题\n3. 安全性问题\n4. 可维护性问题\n5. 最佳实践遵循情况\n6. 潜在的bug\n7. 代码重复\n8. 注释和文档\n\n请以JSON格式返回审查结果。`;\n }\n\n /**\n * 获取文件类型\n */\n private getFileType(filePath: string): string {\n const ext = filePath.split('.').pop()?.toLowerCase();\n\n switch (ext) {\n case 'ts':\n case 'tsx':\n return 'TypeScript';\n case 'js':\n case 'jsx':\n return 'JavaScript';\n case 'vue':\n return 'Vue';\n case 'css':\n return 'CSS';\n case 'scss':\n case 'sass':\n return 'SCSS';\n case 'html':\n return 'HTML';\n case 'json':\n return 'JSON';\n default:\n return 'Unknown';\n }\n }\n}\n","import { readFileSync, readdirSync, statSync } from 'fs-extra';\nimport { join, extname } from 'path';\nimport chalk from 'chalk';\nimport ora from 'ora';\nimport type {\n CodeAnalysisResult,\n CodeIssue,\n OptimizationSuggestion,\n AIOptimizerConfig,\n OptimizationContext,\n} from './types';\nimport { LLMClient } from './llm-client';\n\nexport class CodeAnalyzer {\n private config: AIOptimizerConfig;\n private llmClient: LLMClient;\n private spinner = ora();\n\n constructor(config: AIOptimizerConfig) {\n this.config = config;\n this.llmClient = new LLMClient(config);\n }\n\n /**\n * 分析项目代码\n */\n async analyzeProject(\n projectPath: string,\n context: OptimizationContext\n ): Promise<CodeAnalysisResult[]> {\n this.spinner.start('分析项目代码...');\n\n try {\n const files = this.getProjectFiles(projectPath);\n const results: CodeAnalysisResult[] = [];\n\n for (const file of files) {\n try {\n const analysis = await this.analyzeFile(file, context);\n results.push(analysis);\n } catch (error) {\n console.warn(chalk.yellow(`跳过文件 ${file}: ${error}`));\n }\n }\n\n this.spinner.succeed(`代码分析完成: ${results.length} 个文件`);\n return results;\n } catch (error) {\n this.spinner.fail('代码分析失败');\n throw error;\n }\n }\n\n /**\n * 分析单个文件\n */\n async analyzeFile(\n filePath: string,\n context: OptimizationContext\n ): Promise<CodeAnalysisResult> {\n const content = readFileSync(filePath, 'utf-8');\n const stats = statSync(filePath);\n\n // 基础分析\n const basicAnalysis = this.performBasicAnalysis(content, filePath);\n\n // AI分析\n let aiAnalysis: any = {};\n if (this.config.analysis.enableCodeAnalysis) {\n try {\n const aiResponse = await this.llmClient.analyzeCode(\n content,\n filePath,\n context\n );\n if (aiResponse.success) {\n aiAnalysis = this.parseAIResponse(aiResponse.content);\n }\n } catch (error) {\n console.warn(chalk.yellow(`AI分析失败 ${filePath}: ${error}`));\n }\n }\n\n return {\n filePath,\n fileSize: stats.size,\n linesOfCode: content.split('\\n').length,\n complexity: basicAnalysis.complexity,\n dependencies: basicAnalysis.dependencies,\n issues: [...basicAnalysis.issues, ...(aiAnalysis.issues || [])],\n suggestions: [\n ...basicAnalysis.suggestions,\n ...(aiAnalysis.suggestions || []),\n ],\n };\n }\n\n /**\n * 获取项目文件\n */\n private getProjectFiles(projectPath: string): string[] {\n const files: string[] = [];\n const extensions = ['.ts', '.tsx', '.js', '.jsx', '.vue', '.css', '.scss'];\n\n const scanDirectory = (dir: string) => {\n try {\n const items = readdirSync(dir);\n\n for (const item of items) {\n const fullPath = join(dir, item);\n const stat = statSync(fullPath);\n\n if (stat.isDirectory()) {\n // 跳过特定目录\n if (\n !['node_modules', '.git', 'dist', 'build', '.next'].includes(item)\n ) {\n scanDirectory(fullPath);\n }\n } else if (stat.isFile()) {\n const ext = extname(item);\n if (extensions.includes(ext)) {\n files.push(fullPath);\n }\n }\n }\n } catch (error) {\n // 忽略无法访问的目录\n }\n };\n\n scanDirectory(projectPath);\n return files;\n }\n\n /**\n * 执行基础分析\n */\n private performBasicAnalysis(\n content: string,\n filePath: string\n ): {\n complexity: number;\n dependencies: string[];\n issues: CodeIssue[];\n suggestions: OptimizationSuggestion[];\n } {\n const complexity = this.calculateComplexity(content);\n const dependencies = this.extractDependencies(content);\n const issues = this.detectBasicIssues(content, filePath);\n const suggestions = this.generateBasicSuggestions(\n content,\n filePath,\n issues\n );\n\n return {\n complexity,\n dependencies,\n issues,\n suggestions,\n };\n }\n\n /**\n * 计算代码复杂度\n */\n private calculateComplexity(content: string): number {\n let complexity = 1; // 基础复杂度\n\n // 计算控制流复杂度\n const controlFlowKeywords = [\n 'if',\n 'else',\n 'for',\n 'while',\n 'do',\n 'switch',\n 'case',\n 'catch',\n 'try',\n '&&',\n '||',\n '?',\n ':',\n 'return',\n 'throw',\n ];\n\n for (const keyword of controlFlowKeywords) {\n const regex = new RegExp(`\\\\b${keyword}\\\\b`, 'g');\n const matches = content.match(regex);\n if (matches) {\n complexity += matches.length;\n }\n }\n\n return complexity;\n }\n\n /**\n * 提取依赖关系\n */\n private extractDependencies(content: string): string[] {\n const dependencies: string[] = [];\n\n // 提取 import 语句\n const importRegex = /import\\s+.*?\\s+from\\s+['\"]([^'\"]+)['\"]/g;\n let match;\n while ((match = importRegex.exec(content)) !== null) {\n dependencies.push(match[1]);\n }\n\n // 提取 require 语句\n const requireRegex = /require\\s*\\(\\s*['\"]([^'\"]+)['\"]\\s*\\)/g;\n while ((match = requireRegex.exec(content)) !== null) {\n dependencies.push(match[1]);\n }\n\n return [...new Set(dependencies)]; // 去重\n }\n\n /**\n * 检测基础问题\n */\n private detectBasicIssues(content: string, _filePath: string): CodeIssue[] {\n const issues: CodeIssue[] = [];\n\n // 检查长函数\n const functionRegex = /function\\s+\\w+\\s*\\([^)]*\\)\\s*{/g;\n let match;\n while ((match = functionRegex.exec(content)) !== null) {\n const lineNumber = content.substring(0, match.index).split('\\n').length;\n const functionContent = this.extractFunctionContent(content, match.index);\n\n if (functionContent.split('\\n').length > 50) {\n issues.push({\n type: 'maintainability',\n severity: 'medium',\n message: '函数过长，建议拆分为更小的函数',\n line: lineNumber,\n fix: '将函数拆分为多个更小的函数',\n });\n }\n }\n\n // 检查未使用的变量\n const varRegex = /(?:let|const|var)\\s+(\\w+)/g;\n const declaredVars = new Set<string>();\n\n while ((match = varRegex.exec(content)) !== null) {\n declaredVars.add(match[1]);\n }\n\n // 检查变量使用\n for (const varName of declaredVars) {\n const useRegex = new RegExp(`\\\\b${varName}\\\\b`, 'g');\n const uses = content.match(useRegex);\n if (uses && uses.length === 1) {\n const lineNumber =\n content.indexOf(`let ${varName}`) ||\n content.indexOf(`const ${varName}`) ||\n content.indexOf(`var ${varName}`);\n if (lineNumber !== -1) {\n issues.push({\n type: 'maintainability',\n severity: 'low',\n message: `变量 '${varName}' 声明但未使用`,\n line: content.substring(0, lineNumber).split('\\n').length,\n fix: `删除未使用的变量 '${varName}'`,\n });\n }\n }\n }\n\n // 检查console.log\n const consoleRegex = /console\\.(log|warn|error|info)/g;\n while ((match = consoleRegex.exec(content)) !== null) {\n const lineNumber = content.substring(0, match.index).split('\\n').length;\n issues.push({\n type: 'best-practice',\n severity: 'low',\n message: '生产代码中不应包含console语句',\n line: lineNumber,\n fix: '移除console语句或使用适当的日志库',\n });\n }\n\n return issues;\n }\n\n /**\n * 生成基础建议\n */\n private generateBasicSuggestions(\n _content: string,\n filePath: string,\n issues: CodeIssue[]\n ): OptimizationSuggestion[] {\n const suggestions: OptimizationSuggestion[] = [];\n\n // 基于问题生成建议\n const issueTypes = new Set(issues.map(issue => issue.type));\n\n if (issueTypes.has('maintainability')) {\n suggestions.push({\n id: `maintainability-${Date.now()}`,\n title: '提高代码可维护性',\n description: '重构代码以提高可读性和可维护性',\n impact: 'medium',\n difficulty: 'medium',\n estimatedSavings: {\n buildTime: 5,\n },\n steps: ['拆分长函数', '提取重复代码', '添加类型注解', '改进变量命名'],\n affectedFiles: [filePath],\n risk: 'low',\n autoApplicable: false,\n });\n }\n\n if (issueTypes.has('performance')) {\n suggestions.push({\n id: `performance-${Date.now()}`,\n title: '优化性能',\n description: '优化代码以提高运行时性能',\n impact: 'high',\n difficulty: 'medium',\n estimatedSavings: {\n runtimePerformance: 10,\n },\n steps: [\n '优化循环和条件判断',\n '减少不必要的计算',\n '使用更高效的数据结构',\n '实现缓存机制',\n ],\n affectedFiles: [filePath],\n risk: 'medium',\n autoApplicable: false,\n });\n }\n\n return suggestions;\n }\n\n /**\n * 提取函数内容\n */\n private extractFunctionContent(content: string, startIndex: number): string {\n let braceCount = 0;\n let inFunction = false;\n let endIndex = startIndex;\n\n for (let i = startIndex; i < content.length; i++) {\n const char = content[i];\n\n if (char === '{') {\n braceCount++;\n inFunction = true;\n } else if (char === '}') {\n braceCount--;\n if (inFunction && braceCount === 0) {\n endIndex = i;\n break;\n }\n }\n }\n\n return content.substring(startIndex, endIndex + 1);\n }\n\n /**\n * 解析AI响应\n */\n private parseAIResponse(content: string): any {\n try {\n return JSON.parse(content);\n } catch (error) {\n console.warn(chalk.yellow('AI响应解析失败，使用默认值'));\n return { issues: [], suggestions: [] };\n }\n }\n}\n","import chalk from 'chalk';\nimport ora from 'ora';\nimport type {\n OptimizationSuggestion,\n ProjectAnalysisResult,\n AIOptimizerConfig,\n OptimizationContext,\n CodeAnalysisResult,\n} from './types';\nimport { LLMClient } from './llm-client';\n\nexport class SuggestionGenerator {\n private config: AIOptimizerConfig;\n private llmClient: LLMClient;\n private spinner = ora();\n\n constructor(config: AIOptimizerConfig) {\n this.config = config;\n this.llmClient = new LLMClient(config);\n }\n\n /**\n * 生成优化建议\n */\n async generateSuggestions(\n analysisResult: ProjectAnalysisResult,\n context: OptimizationContext\n ): Promise<OptimizationSuggestion[]> {\n this.spinner.start('生成AI优化建议...');\n\n try {\n const suggestions: OptimizationSuggestion[] = [];\n\n // 基础建议\n const basicSuggestions = this.generateBasicSuggestions(\n analysisResult,\n context\n );\n suggestions.push(...basicSuggestions);\n\n // AI建议\n if (this.config.analysis.enableCodeAnalysis) {\n const aiSuggestions = await this.generateAISuggestions(\n analysisResult,\n context\n );\n suggestions.push(...aiSuggestions);\n }\n\n // 去重和排序\n const uniqueSuggestions = this.deduplicateSuggestions(suggestions);\n const sortedSuggestions = this.prioritizeSuggestions(\n uniqueSuggestions,\n analysisResult\n );\n\n this.spinner.succeed(`优化建议生成完成: ${sortedSuggestions.length} 个`);\n return sortedSuggestions.slice(\n 0,\n this.config.optimization.maxSuggestions\n );\n } catch (error) {\n this.spinner.fail('优化建议生成失败');\n throw error;\n }\n }\n\n /**\n * 生成基础建议\n */\n private generateBasicSuggestions(\n analysisResult: ProjectAnalysisResult,\n _context: OptimizationContext\n ): OptimizationSuggestion[] {\n const suggestions: OptimizationSuggestion[] = [];\n\n // 包大小优化建议\n if (analysisResult.stats.bundleSize > 1024 * 1024) {\n // 1MB\n suggestions.push({\n id: 'bundle-size-optimization',\n title: '优化包大小',\n description: '当前包大小超过1MB，建议进行代码分割和懒加载优化',\n impact: 'high',\n difficulty: 'medium',\n estimatedSavings: {\n bundleSize: 30,\n },\n steps: [\n '启用代码分割',\n '实现路由级别的懒加载',\n '移除未使用的依赖',\n '优化图片和静态资源',\n ],\n affectedFiles: this.getAffectedFiles(analysisResult, [\n 'config',\n 'router',\n 'components',\n ]),\n risk: 'low',\n autoApplicable: true,\n });\n }\n\n // 构建时间优化建议\n if (analysisResult.stats.buildTime > 30000) {\n // 30s\n suggestions.push({\n id: 'build-time-optimization',\n title: '优化构建时间',\n description: '当前构建时间超过30秒，建议启用缓存和并行构建',\n impact: 'high',\n difficulty: 'easy',\n estimatedSavings: {\n buildTime: 50,\n },\n steps: [\n '启用构建缓存',\n '配置并行构建',\n '优化依赖解析',\n '使用更快的构建工具',\n ],\n affectedFiles: this.getAffectedFiles(analysisResult, ['config']),\n risk: 'low',\n autoApplicable: true,\n });\n }\n\n // 依赖优化建议\n if (analysisResult.stats.dependencies > 100) {\n suggestions.push({\n id: 'dependency-optimization',\n title: '优化依赖管理',\n description: '依赖数量过多，建议清理未使用的依赖',\n impact: 'medium',\n difficulty: 'easy',\n estimatedSavings: {\n bundleSize: 20,\n buildTime: 15,\n },\n steps: [\n '分析依赖使用情况',\n '移除未使用的依赖',\n '合并相似功能的依赖',\n '使用更轻量的替代方案',\n ],\n affectedFiles: ['package.json'],\n risk: 'medium',\n autoApplicable: false,\n });\n }\n\n // 代码质量建议\n const codeQualityIssues = this.analyzeCodeQuality(\n analysisResult.codeAnalysis\n );\n if (codeQualityIssues.length > 0) {\n suggestions.push({\n id: 'code-quality-improvement',\n title: '提升代码质量',\n description: '发现代码质量问题，建议进行重构和优化',\n impact: 'medium',\n difficulty: 'medium',\n estimatedSavings: {\n buildTime: 10,\n runtimePerformance: 15,\n },\n steps: ['重构复杂函数', '添加类型注解', '改进错误处理', '增加单元测试'],\n affectedFiles: codeQualityIssues.map(issue => issue.filePath),\n risk: 'medium',\n autoApplicable: false,\n });\n }\n\n return suggestions;\n }\n\n /**\n * 生成AI建议\n */\n private async generateAISuggestions(\n analysisResult: ProjectAnalysisResult,\n context: OptimizationContext\n ): Promise<OptimizationSuggestion[]> {\n try {\n const aiResponse = await this.llmClient.generateOptimizationSuggestions(\n analysisResult,\n context\n );\n\n if (!aiResponse.success) {\n console.warn(chalk.yellow('AI建议生成失败，使用基础建议'));\n return [];\n }\n\n return this.parseAISuggestions(aiResponse.content);\n } catch (error) {\n console.warn(chalk.yellow(`AI建议生成失败: ${error}`));\n return [];\n }\n }\n\n /**\n * 解析AI建议\n */\n private parseAISuggestions(content: string): OptimizationSuggestion[] {\n try {\n const data = JSON.parse(content);\n\n if (Array.isArray(data.suggestions)) {\n return data.suggestions.map((suggestion: any, index: number) => ({\n id: suggestion.id || `ai-suggestion-${index}`,\n title: suggestion.title || 'AI优化建议',\n description: suggestion.description || '',\n impact: suggestion.impact || 'medium',\n difficulty: suggestion.difficulty || 'medium',\n estimatedSavings: suggestion.estimatedSavings || {},\n steps: suggestion.steps || [],\n affectedFiles: suggestion.affectedFiles || [],\n risk: suggestion.risk || 'medium',\n autoApplicable: suggestion.autoApplicable || false,\n }));\n }\n\n return [];\n } catch (error) {\n console.warn(chalk.yellow('AI建议解析失败'));\n return [];\n }\n }\n\n /**\n * 去重建议\n */\n private deduplicateSuggestions(\n suggestions: OptimizationSuggestion[]\n ): OptimizationSuggestion[] {\n const seen = new Set<string>();\n const unique: OptimizationSuggestion[] = [];\n\n for (const suggestion of suggestions) {\n const key = `${suggestion.title}-${suggestion.description}`;\n if (!seen.has(key)) {\n seen.add(key);\n unique.push(suggestion);\n }\n }\n\n return unique;\n }\n\n /**\n * 优先级排序\n */\n private prioritizeSuggestions(\n suggestions: OptimizationSuggestion[],\n analysisResult: ProjectAnalysisResult\n ): OptimizationSuggestion[] {\n return suggestions.sort((a, b) => {\n // 计算优先级分数\n const scoreA = this.calculatePriorityScore(a, analysisResult);\n const scoreB = this.calculatePriorityScore(b, analysisResult);\n\n return scoreB - scoreA; // 降序排列\n });\n }\n\n /**\n * 计算优先级分数\n */\n private calculatePriorityScore(\n suggestion: OptimizationSuggestion,\n _analysisResult: ProjectAnalysisResult\n ): number {\n let score = 0;\n\n // 影响程度权重\n const impactWeights = { low: 1, medium: 2, high: 3 };\n score += impactWeights[suggestion.impact] * 10;\n\n // 实施难度权重（难度越低分数越高）\n const difficultyWeights = { easy: 3, medium: 2, hard: 1 };\n score += difficultyWeights[suggestion.difficulty] * 5;\n\n // 风险权重（风险越低分数越高）\n const riskWeights = { low: 3, medium: 2, high: 1 };\n score += riskWeights[suggestion.risk] * 3;\n\n // 自动应用权重\n if (suggestion.autoApplicable) {\n score += 5;\n }\n\n // 预计节省权重\n const estimatedSavings = suggestion.estimatedSavings;\n if (estimatedSavings.bundleSize) {\n score += Math.min(estimatedSavings.bundleSize / 10, 10);\n }\n if (estimatedSavings.buildTime) {\n score += Math.min(estimatedSavings.buildTime / 5, 10);\n }\n if (estimatedSavings.runtimePerformance) {\n score += Math.min(estimatedSavings.runtimePerformance / 5, 10);\n }\n\n return score;\n }\n\n /**\n * 分析代码质量\n */\n private analyzeCodeQuality(\n codeAnalysis: CodeAnalysisResult[]\n ): CodeAnalysisResult[] {\n return codeAnalysis.filter(analysis => {\n const hasIssues = analysis.issues.length > 0;\n const hasHighComplexity = analysis.complexity > 10;\n const hasManyDependencies = analysis.dependencies.length > 20;\n\n return hasIssues || hasHighComplexity || hasManyDependencies;\n });\n }\n\n /**\n * 获取受影响的文件\n */\n private getAffectedFiles(\n analysisResult: ProjectAnalysisResult,\n fileTypes: string[]\n ): string[] {\n return analysisResult.codeAnalysis\n .map(analysis => analysis.filePath)\n .filter(filePath => fileTypes.some(type => filePath.includes(type)));\n }\n}\n","import {\n readFileSync,\n writeFileSync,\n existsSync,\n copyFileSync,\n} from 'fs-extra';\nimport { join, dirname } from 'path';\nimport chalk from 'chalk';\nimport ora from 'ora';\nimport type {\n OptimizationSuggestion,\n OptimizationResult,\n AIOptimizerConfig,\n} from './types';\n\nexport class OptimizationApplier {\n private config: AIOptimizerConfig;\n private spinner = ora();\n private appliedOptimizations: Map<string, OptimizationResult> = new Map();\n\n constructor(config: AIOptimizerConfig) {\n this.config = config;\n }\n\n /**\n * 应用优化建议\n */\n async applyOptimization(\n suggestion: OptimizationSuggestion,\n projectPath: string\n ): Promise<OptimizationResult> {\n this.spinner.start(`应用优化建议: ${suggestion.title}`);\n\n try {\n // 创建备份\n if (this.config.optimization.createBackup) {\n await this.createBackup(suggestion.affectedFiles, projectPath);\n }\n\n // 应用优化\n const result = await this.executeOptimization(suggestion, projectPath);\n\n // 记录结果\n this.appliedOptimizations.set(suggestion.id, result);\n\n this.spinner.succeed(`优化建议应用完成: ${suggestion.title}`);\n return result;\n } catch (error) {\n this.spinner.fail(`优化建议应用失败: ${suggestion.title}`);\n console.error(chalk.red('应用错误:'), error);\n\n // 回滚更改\n if (this.config.optimization.createBackup) {\n await this.rollbackOptimization(suggestion.id);\n }\n\n throw error;\n }\n }\n\n /**\n * 批量应用优化建议\n */\n async applyOptimizations(\n suggestions: OptimizationSuggestion[],\n projectPath: string\n ): Promise<OptimizationResult[]> {\n this.spinner.start(`批量应用 ${suggestions.length} 个优化建议...`);\n\n const results: OptimizationResult[] = [];\n\n for (const suggestion of suggestions) {\n try {\n const result = await this.applyOptimization(suggestion, projectPath);\n results.push(result);\n } catch (error) {\n console.warn(\n chalk.yellow(`跳过优化建议 ${suggestion.title}: ${error}`)\n );\n results.push({\n id: suggestion.id,\n type: 'code',\n before: { value: null, metrics: {} },\n after: { value: null, metrics: {} },\n improvement: { percentage: 0, absolute: 0, unit: '' },\n status: 'failed',\n error: error instanceof Error ? error.message : 'Unknown error',\n });\n }\n }\n\n this.spinner.succeed(`批量应用完成: ${results.length} 个`);\n return results;\n }\n\n /**\n * 执行优化\n */\n private async executeOptimization(\n suggestion: OptimizationSuggestion,\n projectPath: string\n ): Promise<OptimizationResult> {\n // 记录优化前状态\n const beforeState = await this.captureState(\n suggestion.affectedFiles,\n projectPath\n );\n\n // 根据建议类型执行不同的优化\n let afterState: any;\n\n switch (suggestion.id) {\n case 'bundle-size-optimization':\n afterState = await this.applyBundleSizeOptimization(\n suggestion,\n projectPath\n );\n break;\n case 'build-time-optimization':\n afterState = await this.applyBuildTimeOptimization(\n suggestion,\n projectPath\n );\n break;\n case 'dependency-optimization':\n afterState = await this.applyD