// Skill示例：高级TypeScript类型推断挑战
// 任务：实现一个类型安全的深度Partial工具类型

type DeepPartial<T> = {
  [P in keyof T]?: T[P] extends object 
    ? T[P] extends Array<infer U> 
      ? Array<DeepPartial<U>> 
      : DeepPartial<T[P]> 
    : T[P];
};

// 验证用例
interface User {
  name: string;
  address: {
    city: string;
    coordinates: [number, number];
  };
  tags: string[];
}

const partialUser: DeepPartial<User> = {
  address: {
    city: "Beijing"
  }
};

# OpenMontage核心工作流示例
from openmontage import Project, Scene, Voiceover, Transition

# 创建视频项目
project = Project(
    title="微服务架构入门指南",
    resolution="1920x1080",
    fps=30
)

# 定义场景序列
scene1 = Scene.from_code_snippet(
    code="""
    @SpringBootApplication
    public class GatewayApplication {
        public static void main(String[] args) {
            SpringApplication.run(GatewayApplication.class, args);
        }
    }
    """,
    language="java",
    highlight_lines=[3, 4],
    caption="第一步：创建Spring Cloud Gateway入口类"
)

scene2 = Scene.from_diagram(
    diagram_type="architecture",
    data=gateway_arch_config,
    animation="build_step_by_step"
)

# 配置AI配音
voiceover = Voiceover(
    voice="zh-CN-XiaoxiaoNeural",
    speed=1.1,
    emotion="professional"
)

# 组装并渲染
project.add_scenes([scene1, scene2], transitions=[Transition.SLIDE_LEFT])
project.attach_voiceover(voiceover, script=generate_script_from_scenes())
project.render(output="microservice_guide.mp4")

# Strix扫描策略配置示例
scan_profile:
  name: "web_application_deep_scan"
  target: "https://api.example.com"
  scope: 
    include: ["/v1/", "/v2/", "/admin/"]
    exclude: ["/static/", "/health"]
  
  reconnaissance:
    subdomain_enum: true
    technology_fingerprinting: true
    endpoint_discovery: true
  
  vulnerability_agents:
    - agent: "sql_injection_agent"
      model: "strix-security/SQLi-Detector-7B"
      priority: "critical"
      parameters:
        time_based_detection: true
        error_based_detection: true
        union_based_detection: true
    
    - agent: "xss_agent"
      model: "strix-security/XSS-Hunter-4B"
      priority: "high"
      parameters:
        reflected_xss: true
        stored_xss: true
        dom_based_xss: true
    
    - agent: "auth_bypass_agent"
      model: "strix-security/Auth-Tester-3B"
      priority: "critical"
      parameters:
        jwt_weak_verification: true
        session_fixation: true
        privilege_escalation: true
  
  reporting:
    format: ["pdf", "html", "sarif"]
    cvss_scoring: true
    remediation_advice: "ai_enhanced"
    executive_summary: true

// Aura的AI上下文配置示例
{
  "aura_context": {
    "scope": "repository_wide",
    "history_depth": 100,
    "include_branches": ["main", "develop", "feature/*"],
    "context_sources": {
      "git_history": {
        "enabled": true,
        "weight": 0.3,
        "commit_message_analysis": true,
        "change_pattern_recognition": true
      },
      "code_review": {
        "enabled": true,
        "weight": 0.2,
        "include_resolved_threads": true,
        "style_guide_extraction": true
      },
      "documentation": {
        "enabled": true,
        "weight": 0.15,
        "sources": ["README.md", "docs/", "ARCHITECTURE.md"]
      },
      "active_files": {
        "enabled": true,
        "weight": 0.25,
        "lookahead": 5,
        "lookbehind": 3
      },
      "runtime_telemetry": {
        "enabled": true,
        "weight": 0.1,
        "error_patterns": true,
        "performance_hotspots": true
      }
    }
  }
}

# Aura CLI工作流示例
$ aura clone https://github.com/myorg/project.git
$ cd project

# 启动智能编码会话
$ aura session start --context-depth=50 --model=aura-pro

# 请求基于历史上下文的代码建议
$ aura suggest --task="implement OAuth2 refresh token rotation" \
               --consider="auth refactoring in commit 3a2f1b9" \
               --avoid="patterns flagged in review #234"

# 生成包含完整历史依据的代码审查
$ aura review --pr=456 --generate-report --confidence-threshold=0.85

# 可视化项目知识图谱
$ aura knowledge-graph --export=interactive.html

# 安装OpenMontage及相关依赖
npm install -g @openmontage/cli
pip install openmontage-engine openmontage-ai-voice

# 初始化项目
mkdir blog-to-video && cd blog-to-video
montage init --template=tech-tutorial

# 配置AI服务
montage config set ai.provider=openrouter
montage config set ai.model=anthropic/claude-sonnet-4-20260701
montage config set voice.provider=edge-tts
montage config set voice.language=zh-CN

// blog-parser.js
import { unified } from 'unified';
import remarkParse from 'remark-parse';
import remarkGfm from 'remark-gfm';
import { Project, Scene, Voiceover } from '@openmontage/core';

export async function convertBlogToVideo(markdownPath, options = {}) {
  const content = await fs.readFile(markdownPath, 'utf-8');
  const ast = await unified()
    .use(remarkParse)
    .use(remarkGfm)
    .parse(content);
  
  const project = new Project({
    title: extractTitle(ast),
    resolution: options.resolution || '1920x1080',
    theme: options.theme || 'dark-plus'
  });
  
  const scenes = [];
  let currentSection = null;
  
  for (const node of ast.children) {
    switch (node.type) {
      case 'heading':
        if (node.depth === 2) {
          // H2 作为新章节的开始
          if (currentSection) scenes.push(currentSection);
          currentSection = {
            type: 'chapter',
            title: node.children[0].value,
            scenes: []
          };
        }
        break;
      
      case 'code':
        // 代码块转换为代码场景
        currentSection?.scenes.push(
          Scene.fromCode({
            code: node.value,
            language: node.lang || 'text',
            highlightLines: extractHighlightLines(node.meta),
            caption: extractPrecedingText(ast, node)
          })
        );
        break;
      
      case 'paragraph':
        // 包含特定标记的段落转换为图表
        if (containsMermaid(node)) {
          currentSection?.scenes.push(
            Scene.fromMermaid({
              diagram: extractMermaidCode(node),
              animation: 'step-reveal'
            })
          );
        } else if (containsTable(node)) {
          currentSection?.scenes.push(
            Scene.fromTable({
              data: extractTableData(node),
              style: 'animated-row'
            })
          );
        }
        break;
      
      case 'list':
        // 列表转换为要点场景
        currentSection?.scenes.push(
          Scene.fromBulletPoints({
            items: node.children.map(li => li.children[0].value),
            animation: 'stagger-fade'
          })
        );
        break;
    }
  }
  
  // 组装最终项目
  scenes.forEach(section => {
    project.addChapter(section.title, section.scenes);
  });
  
  // 生成配音脚本
  const script = await generateVoiceScript(ast, {
    tone: 'professional',
    pace: 'moderate'
  });
  
  project.attachVoiceover(
    new Voiceover({ voice: 'zh-CN-YunxiNeural' }),
    script
  );
  
  return project;
}

// 渲染执行
const project = await convertBlogToVideo('./input.md', {
  resolution: '1920x1080',
  theme: 'github-dark'
});

await project.render({
  output: './output/tutorial.mp4',
  quality: 'high',
  hardwareAcceleration: 'nvenc'
});