阶跃星辰Agent操作系统：从"工具"到"系统"的范式跃迁，WAIC 2026全球首发的智能体OS深度解析

"""
Agent OS vs Traditional OS: Architecture Paradigm Comparison
"""

class TraditionalOS:
    """
    传统操作系统（Windows/Android/macOS）
    
    核心抽象：文件和应用程序
    用户交互：图形界面、点击、拖拽
    任务执行：用户手动操作App
    """
    
    def __init__(self):
        self.filesystem = {}
        self.applications = {}
        self.user_actions = []
    
    def execute_user_intent(self, intent: str) -> str:
        """
        传统OS执行用户意图的方式：
        用户必须自己知道用哪个App、怎么操作
        """
        # 用户需要自己分解任务
        # 用户需要知道哪个App能做什么
        # 用户需要手动操作
        return "请在浏览器中搜索相关网站，然后..."


class AgentOS:
    """
    Agent操作系统（阶跃星辰）
    
    核心抽象：意图和任务
    用户交互：自然语言
    任务执行：Agent自动编排
    """
    
    def __init__(self):
        self.intent_engine = IntentEngine()
        self.task_orchestrator = TaskOrchestrator()
        self.tool_registry = ToolRegistry()
        self.multi_agent_coordinator = MultiAgentCoordinator()
        self.context_memory = ContextMemory()
    
    def process_intent(self, user_input: str) -> dict:
        """处理用户意图的完整流程"""
        # 1. 意图理解
        intent = self.intent_engine.parse(user_input)
        
        # 2. 任务拆解
        tasks = self.task_orchestrator.decompose(intent)
        
        # 3. 工具选择与调度
        for task in tasks:
            tool = self.tool_registry.find_best(task)
            task.assigned_tool = tool
        
        # 4. 多智能体协同（如需要）
        if intent.requires_collaboration:
            result = self.multi_agent_coordinator.coordinate(tasks)
        else:
            result = self._execute_sequential(tasks)
        
        # 5. 结果汇总
        return {
            "intent": intent,
            "tasks_executed": len(tasks),
            "tools_used": [t.assigned_tool for t in tasks if t.assigned_tool],
            "result": result,
        }
    
    def _execute_sequential(self, tasks: list) -> list:
        """串行执行任务列表"""
        results = []
        for task in tasks:
            if task.assigned_tool:
                result = task.assigned_tool.execute(task.params)
                results.append(result)
                # 将结果存入上下文供后续任务使用
                self.context_memory.store(task.id, result)
        return results


class IntentEngine:
    """意图理解引擎"""
    
    def parse(self, user_input: str) -> dict:
        """解析用户自然语言输入为结构化意图"""
        # 使用端侧模型进行意图识别
        return {
            "raw_input": user_input,
            "action_type": "complex_workflow",
            "requires_collaboration": False,
            "estimated_steps": 5,
            "domain": "productivity",
        }


class TaskOrchestrator:
    """任务编排器：将意图拆解为可执行任务"""
    
    def decompose(self, intent: dict) -> list:
        """将意图拆解为子任务"""
        return [
            Task("search_web", {"query": "..."}),
            Task("read_file", {"path": "..."}),
            Task("generate_document", {"format": "pptx"}),
            Task("send_email", {"to": "..."}),
        ]


class Task:
    """单个可执行任务"""
    
    def __init__(self, action: str, params: dict):
        self.action = action
        self.params = params
        self.assigned_tool = None


class ToolRegistry:
    """工具注册表：维护所有可用工具及其能力描述"""
    
    def __init__(self):
        self.tools = {
            "search_web": {"capabilities": ["web_search", "information_retrieval"]},
            "read_file": {"capabilities": ["file_read", "document_parsing"]},
            "generate_document": {"capabilities": ["document_creation", "formatting"]},
            "send_email": {"capabilities": ["communication", "email"]},
            "calendar": {"capabilities": ["scheduling", "time_management"]},
            "code_execution": {"capabilities": ["programming", "automation"]},
        }
    
    def find_best(self, task: Task):
        """为任务找到最合适的工具"""
        for name, info in self.tools.items():
            if task.action in info["capabilities"]:
                return Tool(name)
        return None


class Tool:
    """可调用的工具"""
    
    def __init__(self, name: str):
        self.name = name
    
    def execute(self, params: dict) -> str:
        return f"Tool {self.name} executed with {params}"


class MultiAgentCoordinator:
    """多智能体协调器"""
    
    def coordinate(self, tasks: list) -> list:
        """协调多个智能体并行/串行执行任务"""
        return [f"Agent completed: {t.action}" for t in tasks]


class ContextMemory:
    """上下文记忆：跨任务共享状态"""
    
    def __init__(self):
        self.store = {}
    
    def store(self, task_id: str, result: str):
        self.store[task_id] = result
    
    def retrieve(self, task_id: str) -> str:
        return self.store.get(task_id, "")


# 演示对比
def demo_comparison():
    """对比传统OS和Agent OS处理同一任务的方式"""
    user_intent = "帮我准备下周去上海出差的行程，包括订机票、查天气、约接机"
    
    traditional = TraditionalOS()
    agent_os = AgentOS()
    
    print("=" * 60)
    print("传统OS vs Agent OS：处理同一任务")
    print("=" * 60)
    
    print(f"\n用户意图: 「{user_intent}」")
    
    print(f"\n传统OS:")
    print(f"  1. 打开浏览器 → 搜索航班")
    print(f"  2. 打开天气App → 查上海天气")
    print(f"  3. 打开日历 → 确认行程")
    print(f"  4. 打开通讯App → 联系接机")
    print(f"  耗时: 5-10分钟，手动操作6-8步")
    
    result = agent_os.process_intent(user_intent)
    print(f"\nAgent OS:")
    print(f"  1. 意图理解: 识别「出差筹备」意图")
    print(f"  2. 任务拆解: 5个子任务")
    print(f"  3. 自动编排: 搜索+订票+天气+日程+接机")
    print(f"  4. 多Agent协同: 并行执行")
    print(f"  耗时: 30秒，自然语言一句话")
    print(f"  工具调用: {result['tools_used']}")


if __name__ == "__main__":
    demo_comparison()

// Go实现：跨应用调度引擎
package main

import (
    "fmt"
    "strings"
    "time"
)

// App represents a third-party application
type App struct {
    Name        string
    Capabilities []string
    APIVersion   string
}

// Intent represents user's parsed intention
type Intent struct {
    Raw          string
    Tasks        []Task
    Priority     int
}

// Task represents a single executable step
type Task struct {
    Action      string
    TargetApp   string
    Parameters  map[string]string
    Dependencies []string
}

// CrossAppScheduler manages cross-application task scheduling
type CrossAppScheduler struct {
    apps     map[string]App
    taskQueue []Task
}

func (s *CrossAppScheduler) RegisterApp(app App) {
    if s.apps == nil {
        s.apps = make(map[string]App)
    }
    s.apps[app.Name] = app
}

func (s *CrossAppScheduler) Schedule(tasks []Task) []TaskResult {
    var results []TaskResult
    
    // Topological sort by dependencies
    sorted := s.topologicalSort(tasks)
    
    for _, task := range sorted {
        // Check if app supports this action
        app, exists := s.apps[task.TargetApp]
        if !exists {
            results = append(results, TaskResult{
                Task:    task,
                Success: false,
                Error:   fmt.Sprintf("App %s not found", task.TargetApp),
            })
            continue
        }
        
        // Execute via app's API
        result := s.executeOnApp(app, task)
        results = append(results, result)
    }
    
    return results
}

func (s *CrossAppScheduler) topologicalSort(tasks []Task) []Task {
    // Simple topological sort based on dependencies
    visited := make(map[string]bool)
    var sorted []Task
    
    var dfs func(task Task)
    dfs = func(task Task) {
        if visited[task.Action] {
            return
        }
        visited[task.Action] = true
        
        for _, dep := range task.Dependencies {
            for _, t := range tasks {
                if t.Action == dep {
                    dfs(t)
                }
            }
        }
        sorted = append(sorted, task)
    }
    
    for _, task := range tasks {
        dfs(task)
    }
    
    return sorted
}

func (s *CrossAppScheduler) executeOnApp(app App, task Task) TaskResult {
    // Simulate API call to the app
    time.Sleep(100 * time.Millisecond)
    
    return TaskResult{
        Task:    task,
        Success: true,
        Data:    fmt.Sprintf("Executed %s on %s", task.Action, app.Name),
    }
}

type TaskResult struct {
    Task    Task
    Success bool
    Error   string
    Data    string
}

func main() {
    scheduler := &CrossAppScheduler{}
    
    // Register apps
    scheduler.RegisterApp(App{"Browser", []string{"search", "browse"}, "2.1"})
    scheduler.RegisterApp(App{"Calendar", []string{"read", "create", "update"}, "1.3"})
    scheduler.RegisterApp(App{"Email", []string{"send", "read", "draft"}, "3.0"})
    scheduler.RegisterApp(App{"Maps", []string{"navigate", "search_poi"}, "2.0"})
    
    // Process a complex intent
    userIntent := Intent{
        Raw: "下周去上海出差，帮我安排行程",
        Tasks: []Task{
            {"search_flights", "Browser", map[string]string{"from": "北京", "to": "上海"}, nil},
            {"check_weather", "Browser", map[string]string{"city": "上海", "date": "下周"}, []string{"search_flights"}},
            {"create_calendar", "Calendar", map[string]string{"title": "上海出差"}, []string{"search_flights"}},
            {"book_hotel", "Browser", map[string]string{"city": "上海"}, []string{"search_flights"}},
            {"send_itinerary", "Email", map[string]string{"to": "本人"}, []string{"create_calendar", "book_hotel"}},
        },
    }
    
    fmt.Println(strings.Repeat("=", 60))
    fmt.Println("Cross-App Scheduling: Complex Intent Processing")
    fmt.Println(strings.Repeat("=", 60))
    fmt.Printf("User Intent: %s\n", userIntent.Raw)
    fmt.Printf("Decomposed into: %d tasks\n", len(userIntent.Tasks))
    fmt.Println(strings.Repeat("-", 60))
    
    results := scheduler.Schedule(userIntent.Tasks)
    
    for _, r := range results {
        status := "✅" 
        if !r.Success { status = "❌" }
        fmt.Printf("%s %s → %s\n", status, r.Task.Action, r.Task.TargetApp)
    }
}