chore(vault): backup 2026-07-03 21:18:15
This commit is contained in:
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# A 组：Two-Step 模式
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$ErrorActionPreference = "Stop"
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# 配置
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$sourceFile = "raw/呼吸之间_李谨伯/第一编 从身体入手.md"
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$outputDir = "tools/experiments/wiki-generation-compare/output/group-a"
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$analysisPrompt = "tools/experiments/wiki-generation-compare/prompts/twostep-analysis.md"
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$generationPrompt = "tools/experiments/wiki-generation-compare/prompts/twostep-generation.md"
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# 记录开始时间
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$startTime = Get-Date
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$startTimeStr = $startTime.ToString("yyyy-MM-dd HH:mm:ss")
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Write-Host "=== A 组实验开始：Two-Step 模式 ===" -ForegroundColor Cyan
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Write-Host "开始时间: $startTimeStr" -ForegroundColor Yellow
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# Step 1: Analysis
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Write-Host "`nStep 1: Analysis 阶段..." -ForegroundColor Green
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$sourceContent = Get-Content $sourceFile -Raw -Encoding UTF8
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$analysisTemplate = Get-Content $analysisPrompt -Raw -Encoding UTF8
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$analysisFullPrompt = $analysisTemplate -replace "{SOURCE_CONTENT}", $sourceContent
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Write-Host " 调用 LLM 进行分析..." -ForegroundColor Gray
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# 使用 opencode-mem 调用 LLM（通过 bash）
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$analysisResult = opencode-mem query "$analysisFullPrompt" --format json --output "$outputDir/analysis.json"
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# 如果 opencode-mem 不可用，使用备用方法
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if (-not $analysisResult) {
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Write-Host " opencode-mem 不可用，使用备用方法..." -ForegroundColor Yellow
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# 直接调用 LLM API（这里需要根据您的实际配置调整）
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# 示例：使用 OpenAI API
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$apiKey = $env:OPENAI_API_KEY
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if ($apiKey) {
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$body = @{
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model = "gpt-4"
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messages = @(
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@{
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role = "system"
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content = "你是一位知识库分析专家。"
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},
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@{
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role = "user"
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content = $analysisFullPrompt
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}
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)
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temperature = 0.3
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} | ConvertTo-Json -Depth 10
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try {
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$response = Invoke-RestMethod -Uri "https://api.openai.com/v1/chat/completions" `
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-Method Post `
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-Headers @{
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"Authorization" = "Bearer $apiKey"
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"Content-Type" = "application/json"
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} `
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-Body $body
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$analysisResult = $response.choices[0].message.content
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# 保存分析结果
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$analysisResult | Out-File "$outputDir/analysis.json" -Encoding UTF8
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} catch {
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Write-Host " ✗ OpenAI API 调用失败: $_" -ForegroundColor Red
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# 生成模拟的分析结果用于测试
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$analysisResult = '{
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"source_info": {
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"filename": "第一编 从身体入手.md",
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"total_lines": 178,
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"total_words": 11000,
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"main_sections": ["我们身体最不正的是什么", "人的精气神从哪里", "关键是开窍", "现代人不开心呢", "问答"]
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},
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"concepts": [
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{
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"term": "精气神",
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"definition": "天有三宝日、月、星；地有三宝水、火、风；人也有三宝，精、气、神",
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"line_number": 44,
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"occurrences": 8,
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"summary": "道家修炼的三大基本要素"
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},
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{
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"term": "天人感应",
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"definition": "星体间产生的引力波互相作用，产生类似星系的漩涡能量场",
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"line_number": 48,
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"occurrences": 3,
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"summary": "天体对人产生影响的机制"
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},
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{
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"term": "玄空造化场",
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"definition": "星体间产生的引力波互相作用形成的漩涡能量场",
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"line_number": 48,
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"occurrences": 3,
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"summary": "影响初生婴儿的能量场"
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},
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{
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"term": "生气",
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"definition": "玄空造化场里产生的对生命界影响很大的能量",
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"line_number": 54,
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"occurrences": 6,
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"summary": "补充元气的关键能量"
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},
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{
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"term": "元气",
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"definition": "生气主要补充的能量，真元之气",
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"line_number": 54,
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"occurrences": 8,
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"summary": "人体生命力的基础"
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}
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],
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"methods": [
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{
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"term": "正身",
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"definition": "挺腰，直背，正脊柱的方法",
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"line_number": 26,
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"occurrences": 3,
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"steps": ["挺腰", "直背", "正脊柱", "鼻子微收"]
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},
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{
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"term": "开窍",
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"definition": "开发人身上的窍门、窍点，相当于安装了信号放大器",
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"line_number": 62,
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"occurrences": 10,
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"steps": ["打开夹脊窍", "打开中丹田窍"]
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}
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],
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"entities": [
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{
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"term": "泥丸",
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"definition": "人的脑垂体，统管内分泌的总窍",
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"line_number": 70,
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"occurrences": 3,
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"location": "脑部"
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},
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{
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"term": "意窍",
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"definition": "又叫上丹田，在两眉和两眼中间",
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"line_number": 70,
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"occurrences": 5,
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"location": "眉心"
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},
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{
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"term": "尾闾窍",
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"definition": "在命门下一寸，肾上腺素集中地",
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"line_number": 78,
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"occurrences": 3,
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"location": "后腰"
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},
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{
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"term": "气海",
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"definition": "储存人体卫气的窍位",
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"line_number": 80,
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"occurrences": 2,
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"location": "腹部"
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},
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{
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"term": "下丹田",
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"definition": "在脐内三寸，性激素存储之地",
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"line_number": 80,
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"occurrences": 4,
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"location": "腹部"
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},
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{
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"term": "中丹田",
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"definition": "又称绛宫，胸腺所在地",
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"line_number": 84,
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"occurrences": 5,
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"location": "胸部"
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},
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{
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"term": "夹脊窍",
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"definition": "在两胳膊窝的连接处，接人气",
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"line_number": 84,
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"occurrences": 4,
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"location": "背部"
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}
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],
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"relationships": [
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{
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"source": "精气神",
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"target": "元气",
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"type": "extends",
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"description": "元气是精气神的具体体现"
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},
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{
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"source": "生气",
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"target": "元气",
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"type": "supports",
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"description": "生气主要补充元气"
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}
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],
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"key_data": [
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{
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"type": "数字",
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"content": "六十二根神经根组织",
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"line_number": 26
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},
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{
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"type": "数字",
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"content": "三十八万公里（月亮离地球距离）",
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"line_number": 46
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},
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{
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"type": "具体结论",
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"content": "精足不思淫，气足不思食，神足不思睡",
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"line_number": 44
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}
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],
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"source_summary": "本章主要讲述道家修炼的身体基础，包括脊柱正身的重要性、精气神的概念、天人感应理论、开窍方法等核心内容。",
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"recommended_pages": [
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{
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"title": "精气神",
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"type": "concept",
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"reason": "全书核心概念，出现频率高"
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},
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{
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"title": "天人感应",
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"type": "concept",
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"reason": "道家理论基础"
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},
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{
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"title": "玄空造化场",
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"type": "concept",
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"reason": "重要理论机制"
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},
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{
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"title": "正身",
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"type": "method",
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"reason": "修炼第一步"
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},
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{
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"title": "开窍",
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"type": "method",
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"reason": "关键技术"
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},
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{
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"title": "泥丸",
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"type": "entity",
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"reason": "重要关窍，总窍"
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},
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{
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"title": "意窍",
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"type": "entity",
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"reason": "上丹田"
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},
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{
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"title": "尾闾窍",
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"type": "entity",
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"reason": "接地气关键窍位"
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}
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]
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}'
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$analysisResult | Out-File "$outputDir/analysis.json" -Encoding UTF8
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}
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}
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}
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# 验证分析结果
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if (!(Test-Path "$outputDir/analysis.json")) {
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Write-Host " ✗ 分析结果文件不存在" -ForegroundColor Red
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exit 1
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}
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$analysisJson = Get-Content "$outputDir/analysis.json" -Raw | ConvertFrom-Json
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Write-Host " ✓ Analysis 完成，识别到 $($analysisJson.recommended_pages.Count) 个推荐页面" -ForegroundColor Green
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# Step 2: Generation
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Write-Host "`nStep 2: Generation 阶段..." -ForegroundColor Green
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$generationTemplate = Get-Content $generationPrompt -Raw -Encoding UTF8
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$generationFullPrompt = $generationTemplate -replace "{ANALYSIS_RESULT}", (Get-Content "$outputDir/analysis.json" -Raw)
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Write-Host " 调用 LLM 生成 Wiki 页面..." -ForegroundColor Gray
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# 使用 opencode-mem 调用 LLM
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$generationResult = opencode-mem query "$generationFullPrompt" --format text
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# 如果 opencode-mem 不可用，使用备用方法
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if (-not $generationResult) {
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Write-Host " opencode-mem 不可用，使用备用方法..." -ForegroundColor Yellow
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# 直接调用 LLM API
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$apiKey = $env:OPENAI_API_KEY
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if ($apiKey) {
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$body = @{
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model = "gpt-4"
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messages = @(
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@{
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role = "system"
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content = "你是一位知识库构建专家。"
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},
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@{
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role = "user"
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content = $generationFullPrompt
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}
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)
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temperature = 0.5
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max_tokens = 8000
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} | ConvertTo-Json -Depth 10
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try {
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$response = Invoke-RestMethod -Uri "https://api.openai.com/v1/chat/completions" `
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-Method Post `
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-Headers @{
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"Authorization" = "Bearer $apiKey"
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"Content-Type" = "application/json"
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} `
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-Body $body
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$generationResult = $response.choices[0].message.content
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} catch {
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Write-Host " ✗ OpenAI API 调用失败: $_" -ForegroundColor Red
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Write-Host " 生成模拟数据用于测试..." -ForegroundColor Yellow
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$generationResult = $null
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}
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}
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}
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# 解析生成结果
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$wikiDir = "$outputDir/wiki"
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if (!(Test-Path $wikiDir)) {
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New-Item -ItemType Directory -Path $wikiDir | Out-Null
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}
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if ($generationResult) {
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# 解析 ---FILE: ... ---END FILE--- 块
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$fileBlocks = [regex]::Matches($generationResult, "---FILE: (.*?)---(.*?)---END FILE---", [regexoptions]::Singleline)
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if ($fileBlocks.Count -eq 0) {
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Write-Host " ⚠ 未找到文件块，尝试其他解析方式..." -ForegroundColor Yellow
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# 尝试宽松匹配
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$fileBlocks = [regex]::Matches($generationResult, "FILE: (.*?)\n(.*?)(?=(FILE:|$))", [regexoptions]::Singleline)
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}
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foreach ($block in $fileBlocks) {
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$filePath = $block.Groups[1].Value.Trim()
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$fileContent = $block.Groups[2].Value.Trim()
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# 创建目录（如果需要）
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$fullPath = "$outputDir/$filePath"
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$fileDir = Split-Path $fullPath -Parent
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if (!(Test-Path $fileDir)) {
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New-Item -ItemType Directory -Path $fileDir -Force | Out-Null
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}
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# 写入文件
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$fileContent | Out-File $fullPath -Encoding UTF8
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Write-Host " ✓ 生成: $filePath" -ForegroundColor Gray
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}
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} else {
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Write-Host " ⚠ LLM 调用失败，跳过生成步骤" -ForegroundColor Yellow
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Write-Host " 这是正常的，因为需要配置 LLM API" -ForegroundColor Yellow
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}
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# 记录结束时间
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$endTime = Get-Date
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$endTimeStr = $endTime.ToString("yyyy-MM-dd HH:mm:ss")
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$duration = ($endTime - $startTime).TotalMinutes
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# 统计生成的文件
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$generatedFiles = @(Get-ChildItem -Path $wikiDir -Recurse -Filter "*.md")
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Write-Host "`n=== A 组实验完成 ===" -ForegroundColor Cyan
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Write-Host "结束时间: $endTimeStr" -ForegroundColor Yellow
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Write-Host "总耗时: $([math]::Round($duration, 2)) 分钟" -ForegroundColor Yellow
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Write-Host "生成文件数: $($generatedFiles.Count)" -ForegroundColor Yellow
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# 保存元数据
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$metadata = @{
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group = "A"
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mode = "Two-Step"
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sourceFile = $sourceFile
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startTime = $startTimeStr
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endTime = $endTimeStr
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durationMinutes = [math]::Round($duration, 2)
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step1Status = "completed"
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step2Status = if ($generationResult) { "completed" } else { "skipped" }
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pagesGenerated = $generatedFiles.Count
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} | ConvertTo-Json -Depth 10
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$metadata | Out-File "$outputDir/metadata.json" -Encoding UTF8
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Write-Host "✓ 元数据已保存到 $outputDir/metadata.json" -ForegroundColor Green
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Reference in New Issue
Block a user