from typing import List, Dict
import asyncio

class TaskDecomposer:
    def __init__(self, llm_service):
        self.llm = llm_service

    async def decompose_task(self, task_description: str) -> Dict:
        """Intelligent task decomposition"""
        prompt = f"""
        Task Description: {task_description}
        Please decompose this task into subtasks, output format:
        {{
            "subtasks": [
                {{
                    "id": "task_1",
                    "name": "subtask name",
                    "description": "detailed description",
                    "dependencies": [],
                    "estimated_time": "estimated duration (minutes)"
                }}
            ]
        }}
        Requirements:
        1. Appropriate subtask granularity
        2. Clear task dependencies
        3. Suitable for parallel processing
        """

        response = await self.llm.generate(prompt)
        return self._validate_and_process(response)

    def _validate_and_process(self, decomposition_result: dict) -> dict:
        """Validate and process decomposition results"""
        # Validate task dependency relationships
        self._check_circular_dependencies(decomposition_result["subtasks"])
        # Build task execution graph
        return self._build_execution_graph(decomposition_result["subtasks"])

class TaskExecutor:
    def __init__(self, max_workers: int = 5):
        self.max_workers = max_workers
        self.task_queue = asyncio.Queue()
        self.results = {}
        self.semaphore = asyncio.Semaphore(max_workers)

    async def execute_tasks(self, task_graph: Dict):
        """Execute task graph"""
        # Create worker pool
        workers = [
            self._worker(f"worker_{i}") 
            for i in range(self.max_workers)
        ]

        # Add executable tasks to queue
        ready_tasks = self._get_ready_tasks(task_graph)
        for task in ready_tasks:
            await self.task_queue.put(task)

        # Wait for all tasks to complete
        await asyncio.gather(*workers)

    async def _worker(self, worker_id: str):
        """Worker coroutine"""
        while True:
            try:
                async with self.semaphore:
                    task = await self.task_queue.get()
                    if task is None:
                        break

                    # Execute task
                    result = await self._execute_single_task(task)
                    self.results[task["id"]] = result

                    # Check and add new executable tasks
                    new_ready_tasks = self._get_ready_tasks(task_graph)
                    for task in new_ready_tasks:
                        await self.task_queue.put(task)
            except Exception as e:
                logger.error(f"Worker {worker_id} error: {str(e)}")

class ResourceManager:
    def __init__(self):
        self.resource_pool = {
            'cpu': ResourcePool(max_units=16),
            'memory': ResourcePool(max_units=32),
            'gpu': ResourcePool(max_units=4)
        }

    async def allocate(self, requirements: Dict[str, int]):
        """Allocate resources"""
        allocated = {}
        try:
            for resource_type, amount in requirements.items():
                allocated[resource_type] = await self.resource_pool[resource_type].acquire(amount)
            return allocated
        except InsufficientResourceError:
            # Rollback allocated resources
            await self.release(allocated)
            raise

    async def release(self, allocated_resources: Dict):
        """Release resources"""
        for resource_type, resource in allocated_resources.items():
            await self.resource_pool[resource_type].release(resource)

class SystemMonitor:
    def __init__(self):
        self.metrics = {}
        self.alerts = AlertManager()

    async def monitor_task(self, task_id: str):
        """Monitor single task"""
        start_time = time.time()
        try:
            # Log task start
            self.log_task_start(task_id)

            # Monitor resource usage
            resource_usage = await self.track_resource_usage(task_id)

            # Check performance metrics
            if resource_usage['cpu'] > 80:
                await self.alerts.send_alert(
                    f"High CPU usage for task {task_id}"
                )

            return resource_usage
        finally:
            # Log task completion
            duration = time.time() - start_time
            self.log_task_completion(task_id, duration)

class PerformanceOptimizer:
    def __init__(self):
        self.cache = LRUCache(maxsize=1000)
        self.batch_processor = BatchProcessor()

    async def optimize_execution(self, tasks: List[Dict]):
        """Optimize task execution"""
        # 1. Task grouping
        task_groups = self._group_similar_tasks(tasks)

        # 2. Batch processing optimization
        optimized_groups = []
        for group in task_groups:
            if len(group) > 1:
                # Merge similar tasks
                optimized = await self.batch_processor.process(group)
            else:
                optimized = group[0]
            optimized_groups.append(optimized)

        # 3. Resource pre-allocation
        for group in optimized_groups:
            await self._preallocate_resources(group)

        return optimized_groups

class PluginManager:
    def __init__(self):
        self.plugins = {}

    def register_plugin(self, name: str, plugin: Any):
        """Register plugin"""
        if not hasattr(plugin, 'execute'):
            raise InvalidPluginError(
                "Plugin must implement execute method"
            )
        self.plugins[name] = plugin

    async def execute_plugin(self, name: str, *args, **kwargs):
        """Execute plugin"""
        if name not in self.plugins:
            raise PluginNotFoundError(f"Plugin {name} not found")

        try:
            return await self.plugins[name].execute(*args, **kwargs)
        except Exception as e:
            logger.error(f"Plugin {name} execution failed: {str(e)}")
            raise

class CustomTaskRegistry:
    _task_types = {}

    @classmethod
    def register(cls, task_type: str):
        """Register custom task type"""
        def decorator(task_class):
            cls._task_types[task_type] = task_class
            return task_class
        return decorator

    @classmethod
    def create_task(cls, task_type: str, **kwargs):
        """Create task instance"""
        if task_type not in cls._task_types:
            raise UnknownTaskTypeError(f"Unknown task type: {task_type}")

        return cls._task_types[task_type](**kwargs)

@CustomTaskRegistry.register("data_processing")
class DataProcessingTask:
    async def execute(self, data):
        # Implement data processing logic
        pass

@CustomTaskRegistry.register("report_generation")
class ReportGenerationTask:
    async def execute(self, data):
        # Implement report generation logic
        pass

async def generate_market_report(topic: str):
    # Initialize system components
    orchestrator = TaskOrchestrator()
    optimizer = PerformanceOptimizer()
    monitor = SystemMonitor()

    try:
        # 1. Task planning
        task_graph = await orchestrator.plan_tasks({
            "topic": topic,
            "required_sections": [
                "market_overview",
                "competitor_analysis",
                "trends_analysis",
                "recommendations"
            ]
        })

        # 2. Performance optimization
        optimized_tasks = await optimizer.optimize_execution(
            task_graph["tasks"]
        )

        # 3. Execute tasks
        with monitor.track_execution():
            results = await orchestrator.execute_dag({
                "tasks": optimized_tasks
            })

        # 4. Generate report
        report = await orchestrator.compile_results(results)

        return report

    except Exception as e:
        logger.error(f"Report generation failed: {str(e)}")
        # Trigger alert
        await monitor.alerts.send_alert(
            f"Report generation failed for topic: {topic}"
        )
        raise