/**
 * Visual Workflow Engine
 * Backend engine for the enterprise visual workflow designer
 * Provides templates, tool integration, execution, and collaboration features
 */

import { createConsoleLogger } from '../utils/logger.ts';

const logger = createConsoleLogger('VisualWorkflowEngine');

export interface VisualWorkflowEngineConfig {
  enableCollaboration: boolean;
  enableRealtime: boolean;
  verbose: boolean;
}

export interface WorkflowTool {
  id: string;
  name: string;
  category: string;
  description: string;
  inputs: string[];
  outputs: string[];
  parameters: any;
}

export interface WorkflowConnection {
  from: string;
  to: string;
  fromOutput: string;
  toInput: string;
}

export interface Workflow {
  id: string;
  name: string;
  description: string;
  tools: WorkflowTool[];
  connections: WorkflowConnection[];
  metadata: {
    created: Date;
    lastModified: Date;
    version: string;
    author: string;
  };
}

export interface WorkflowTemplate {
  name: string;
  description: string;
  category: string;
  tools: string[];
  structure: any;
}

/**
 * MCP Tool Registry for Workflows
 */
const WORKFLOW_TOOL_REGISTRY = {
  neural: {
    count: 15,
    tools: [
      {
        name: 'neural_train',
        description: 'Train neural patterns with WASM acceleration',
        inputs: ['training_data', 'model_config'],
        outputs: ['trained_model', 'metrics'],
        category: 'neural'
      },
      {
        name: 'neural_predict',
        description: 'Make AI predictions with trained models',
        inputs: ['model', 'input_data'],
        outputs: ['predictions', 'confidence'],
        category: 'neural'
      },
      {
        name: 'neural_patterns',
        description: 'Analyze cognitive patterns',
        inputs: ['data', 'pattern_type'],
        outputs: ['patterns', 'analysis'],
        category: 'neural'
      },
      {
        name: 'model_save',
        description: 'Save trained models to disk',
        inputs: ['model', 'path'],
        outputs: ['saved_path', 'checksum'],
        category: 'neural'
      },
      {
        name: 'model_load',
        description: 'Load pre-trained models',
        inputs: ['model_path'],
        outputs: ['loaded_model', 'metadata'],
        category: 'neural'
      }
    ]
  },
  memory: {
    count: 10,
    tools: [
      {
        name: 'memory_backup',
        description: 'Create memory backup',
        inputs: ['source', 'destination'],
        outputs: ['backup_id', 'size'],
        category: 'memory'
      },
      {
        name: 'memory_restore',
        description: 'Restore from memory backup',
        inputs: ['backup_id', 'target'],
        outputs: ['restored_items', 'status'],
        category: 'memory'
      },
      {
        name: 'memory_analytics',
        description: 'Analyze memory usage patterns',
        inputs: ['timeframe', 'metrics'],
        outputs: ['analysis', 'recommendations'],
        category: 'memory'
      }
    ]
  },
  workflow: {
    count: 11,
    tools: [
      {
        name: 'workflow_create',
        description: 'Create new workflow',
        inputs: ['name', 'template'],
        outputs: ['workflow_id', 'structure'],
        category: 'workflow'
      },
      {
        name: 'workflow_execute',
        description: 'Execute workflow',
        inputs: ['workflow_id', 'parameters'],
        outputs: ['results', 'execution_log'],
        category: 'workflow'
      },
      {
        name: 'batch_process',
        description: 'Process items in batches',
        inputs: ['items', 'batch_size'],
        outputs: ['processed_items', 'summary'],
        category: 'workflow'
      }
    ]
  },
  monitoring: {
    count: 13,
    tools: [
      {
        name: 'performance_report',
        description: 'Generate performance reports',
        inputs: ['timeframe', 'metrics'],
        outputs: ['report', 'charts'],
        category: 'monitoring'
      },
      {
        name: 'bottleneck_analyze',
        description: 'Analyze system bottlenecks',
        inputs: ['system_metrics', 'threshold'],
        outputs: ['bottlenecks', 'recommendations'],
        category: 'monitoring'
      }
    ]
  }
};

/**
 * Enterprise Workflow Templates
 */
const ENTERPRISE_TEMPLATES: WorkflowTemplate[] = [
  {
    name: 'ai-pipeline',
    description: 'Neural network training and inference pipeline',
    category: 'AI/ML',
    tools: ['neural_train', 'model_save', 'neural_predict', 'performance_report'],
    structure: {
      steps: [
        { tool: 'neural_train', position: { x: 100, y: 100 } },
        { tool: 'model_save', position: { x: 300, y: 100 } },
        { tool: 'neural_predict', position: { x: 500, y: 100 } },
        { tool: 'performance_report', position: { x: 700, y: 100 } }
      ],
      connections: [
        { from: 'neural_train', to: 'model_save' },
        { from: 'model_save', to: 'neural_predict' },
        { from: 'neural_predict', to: 'performance_report' }
      ]
    }
  },
  {
    name: 'data-processing',
    description: 'Complete data ETL and transformation workflow',
    category: 'Data',
    tools: ['memory_backup', 'workflow_create', 'batch_process', 'memory_analytics'],
    structure: {
      steps: [
        { tool: 'memory_backup', position: { x: 100, y: 150 } },
        { tool: 'batch_process', position: { x: 300, y: 150 } },
        { tool: 'memory_analytics', position: { x: 500, y: 150 } }
      ],
      connections: [
        { from: 'memory_backup', to: 'batch_process' },
        { from: 'batch_process', to: 'memory_analytics' }
      ]
    }
  },
  {
    name: 'github-automation',
    description: 'Automated GitHub repository management',
    category: 'DevOps',
    tools: ['github_repo_analyze', 'github_pr_manage', 'github_workflow_auto'],
    structure: {
      steps: [
        { tool: 'github_repo_analyze', position: { x: 100, y: 200 } },
        { tool: 'github_pr_manage', position: { x: 300, y: 200 } },
        { tool: 'github_workflow_auto', position: { x: 500, y: 200 } }
      ],
      connections: [
        { from: 'github_repo_analyze', to: 'github_pr_manage' },
        { from: 'github_pr_manage', to: 'github_workflow_auto' }
      ]
    }
  },
  {
    name: 'memory-management',
    description: 'Advanced memory operations and optimization',
    category: 'Infrastructure',
    tools: ['memory_usage', 'memory_compress', 'memory_sync', 'cache_manage'],
    structure: {
      steps: [
        { tool: 'memory_usage', position: { x: 100, y: 250 } },
        { tool: 'memory_compress', position: { x: 300, y: 250 } },
        { tool: 'memory_sync', position: { x: 500, y: 250 } }
      ],
      connections: [
        { from: 'memory_usage', to: 'memory_compress' },
        { from: 'memory_compress', to: 'memory_sync' }
      ]
    }
  },
  {
    name: 'monitoring-setup',
    description: 'Comprehensive system monitoring workflow',
    category: 'Monitoring',
    tools: ['health_check', 'performance_report', 'bottleneck_analyze', 'metrics_collect'],
    structure: {
      steps: [
        { tool: 'health_check', position: { x: 100, y: 300 } },
        { tool: 'metrics_collect', position: { x: 300, y: 300 } },
        { tool: 'performance_report', position: { x: 500, y: 300 } },
        { tool: 'bottleneck_analyze', position: { x: 700, y: 300 } }
      ],
      connections: [
        { from: 'health_check', to: 'metrics_collect' },
        { from: 'metrics_collect', to: 'performance_report' },
        { from: 'performance_report', to: 'bottleneck_analyze' }
      ]
    }
  },
  {
    name: 'enterprise-security',
    description: 'Security scanning and compliance workflow',
    category: 'Security',
    tools: ['security_scan', 'backup_create', 'log_analysis', 'diagnostic_run'],
    structure: {
      steps: [
        { tool: 'security_scan', position: { x: 100, y: 350 } },
        { tool: 'log_analysis', position: { x: 300, y: 350 } },
        { tool: 'diagnostic_run', position: { x: 500, y: 350 } },
        { tool: 'backup_create', position: { x: 700, y: 350 } }
      ],
      connections: [
        { from: 'security_scan', to: 'log_analysis' },
        { from: 'log_analysis', to: 'diagnostic_run' },
        { from: 'diagnostic_run', to: 'backup_create' }
      ]
    }
  }
];

export class VisualWorkflowEngine {
  private config: VisualWorkflowEngineConfig;
  private workflows = new Map<string, Workflow>();
  private collaborationSessions = new Map<string, any>();
  private isInitialized = false;

  constructor(config: VisualWorkflowEngineConfig) {
    this.config = config;
  }

  /**
   * Initialize the workflow engine
   */
  async initialize(): Promise<void> {
    logger.info('🔧 Initializing Visual Workflow Engine...');
    
    try {
      // Initialize collaboration if enabled
      if (this.config.enableCollaboration) {
        await this.initializeCollaboration();
      }

      this.isInitialized = true;
      logger.info('✅ Visual Workflow Engine initialized successfully');

    } catch (error) {
      logger.error('❌ Failed to initialize Visual Workflow Engine:', error);
      throw error;
    }
  }

  /**
   * Get available tool categories
   */
  async getToolCategories(): Promise<any> {
    const categories: any = {};
    
    for (const [categoryName, categoryInfo] of Object.entries(WORKFLOW_TOOL_REGISTRY)) {
      categories[categoryName] = categoryInfo.tools;
    }
    
    return categories;
  }

  /**
   * Get available templates
   */
  async getTemplates(): Promise<WorkflowTemplate[]> {
    return ENTERPRISE_TEMPLATES;
  }

  /**
   * Create new workflow
   */
  async createWorkflow(name: string): Promise<Workflow> {
    const workflow: Workflow = {
      id: `wf_${Date.now()}`,
      name,
      description: '',
      tools: [],
      connections: [],
      metadata: {
        created: new Date(),
        lastModified: new Date(),
        version: '1.0.0',
        author: 'flowx-user'
      }
    };

    this.workflows.set(workflow.id, workflow);
    logger.info(`✅ Created workflow: ${name} (${workflow.id})`);
    
    return workflow;
  }

  /**
   * Load template
   */
  async loadTemplate(templateName: string): Promise<Workflow> {
    const template = ENTERPRISE_TEMPLATES.find(t => t.name === templateName);
    
    if (!template) {
      throw new Error(`Template not found: ${templateName}`);
    }

    const workflow = await this.createWorkflow(`${template.name}-${Date.now()}`);
    workflow.description = template.description;

    // Add tools from template
    for (const toolName of template.tools) {
      await this.addTool(workflow, toolName);
    }

    // Add connections if defined in template structure
    if (template.structure && template.structure.connections) {
      for (const conn of template.structure.connections) {
        await this.connectTools(workflow, conn.from, conn.to);
      }
    }

    logger.info(`✅ Loaded template: ${templateName}`);
    return workflow;
  }

  /**
   * Add tool to workflow
   */
  async addTool(workflow: Workflow, toolName: string): Promise<void> {
    // Find tool in registry
    let toolDef: any = null;
    let category = '';

    for (const [catName, catInfo] of Object.entries(WORKFLOW_TOOL_REGISTRY)) {
      const tool = catInfo.tools.find((t: any) => t.name === toolName);
      if (tool) {
        toolDef = tool;
        category = catName;
        break;
      }
    }

    if (!toolDef) {
      throw new Error(`Tool not found: ${toolName}`);
    }

    const workflowTool: WorkflowTool = {
      id: `${toolName}_${Date.now()}`,
      name: toolName,
      category,
      description: toolDef.description,
      inputs: toolDef.inputs || [],
      outputs: toolDef.outputs || [],
      parameters: {}
    };

    workflow.tools.push(workflowTool);
    workflow.metadata.lastModified = new Date();
    
    logger.info(`✅ Added tool ${toolName} to workflow ${workflow.name}`);
  }

  /**
   * Connect tools in workflow
   */
  async connectTools(workflow: Workflow, fromTool: string, toTool: string): Promise<void> {
    const fromToolObj = workflow.tools.find(t => t.name === fromTool);
    const toToolObj = workflow.tools.find(t => t.name === toTool);

    if (!fromToolObj || !toToolObj) {
      throw new Error(`Cannot connect tools: ${fromTool} -> ${toTool}`);
    }

    const connection: WorkflowConnection = {
      from: fromToolObj.id,
      to: toToolObj.id,
      fromOutput: fromToolObj.outputs[0] || 'output',
      toInput: toToolObj.inputs[0] || 'input'
    };

    workflow.connections.push(connection);
    workflow.metadata.lastModified = new Date();
    
    logger.info(`✅ Connected ${fromTool} -> ${toTool}`);
  }

  /**
   * Remove tool from workflow
   */
  async removeTool(workflow: Workflow, toolName: string): Promise<void> {
    const toolIndex = workflow.tools.findIndex(t => t.name === toolName);
    
    if (toolIndex === -1) {
      throw new Error(`Tool not found in workflow: ${toolName}`);
    }

    const tool = workflow.tools[toolIndex];
    
    // Remove connections involving this tool
    workflow.connections = workflow.connections.filter(conn => 
      conn.from !== tool.id && conn.to !== tool.id
    );
    
    // Remove the tool
    workflow.tools.splice(toolIndex, 1);
    workflow.metadata.lastModified = new Date();
    
    logger.info(`✅ Removed tool ${toolName} from workflow`);
  }

  /**
   * Get workflow details
   */
  async getWorkflowDetails(workflow: Workflow): Promise<any> {
    return {
      name: workflow.name,
      description: workflow.description,
      tools: workflow.tools,
      connections: workflow.connections,
      estimatedRuntime: workflow.tools.length * 2, // Mock estimation
      toolCount: workflow.tools.length,
      connectionCount: workflow.connections.length
    };
  }

  /**
   * Get workflow status
   */
  async getWorkflowStatus(workflow: Workflow): Promise<any> {
    const errors: string[] = [];
    
    // Basic validation
    if (workflow.tools.length === 0) {
      errors.push('Workflow has no tools');
    }

    // Check for disconnected tools
    const connectedTools = new Set();
    workflow.connections.forEach(conn => {
      connectedTools.add(conn.from);
      connectedTools.add(conn.to);
    });

    workflow.tools.forEach(tool => {
      if (workflow.tools.length > 1 && !connectedTools.has(tool.id)) {
        errors.push(`Tool ${tool.name} is not connected`);
      }
    });

    return {
      state: errors.length === 0 ? 'valid' : 'invalid',
      toolCount: workflow.tools.length,
      connectionCount: workflow.connections.length,
      lastModified: workflow.metadata.lastModified.toISOString(),
      isValid: errors.length === 0,
      errors: errors.length > 0 ? errors : undefined
    };
  }

  /**
   * Execute workflow
   */
  async executeWorkflow(workflow: Workflow): Promise<any> {
    logger.info(`🚀 Executing workflow: ${workflow.name}`);
    
    const results: any = {
      workflowId: workflow.id,
      executionId: `exec_${Date.now()}`,
      startTime: new Date().toISOString(),
      status: 'running',
      toolResults: []
    };

    try {
      // Execute tools in order (simplified execution model)
      for (const tool of workflow.tools) {
        logger.info(`  🔧 Executing tool: ${tool.name}`);
        
        // Mock tool execution
        const toolResult = await this.executeTool(tool);
        results.toolResults.push({
          toolId: tool.id,
          toolName: tool.name,
          status: 'completed',
          result: toolResult,
          executionTime: Math.random() * 1000
        });
        
        // Simulate processing delay
        await new Promise(resolve => setTimeout(resolve, 100));
      }

      results.status = 'completed';
      results.endTime = new Date().toISOString();
      results.totalTime = results.toolResults.reduce((sum: number, r: any) => sum + r.executionTime, 0);

      logger.info(`✅ Workflow execution completed: ${workflow.name}`);
      return results;

    } catch (error) {
      results.status = 'failed';
      results.error = (error as Error).message;
      results.endTime = new Date().toISOString();
      
      logger.error(`❌ Workflow execution failed: ${workflow.name}`, error);
      throw error;
    }
  }

  /**
   * Execute individual tool (mock implementation)
   */
  private async executeTool(tool: WorkflowTool): Promise<any> {
    // This is a mock implementation - in reality this would interface with actual MCP tools
    switch (tool.category) {
      case 'neural':
        return {
          type: 'neural_result',
          model_id: `model_${Date.now()}`,
          accuracy: 0.95 + Math.random() * 0.05,
          training_time: Math.random() * 1000
        };
        
      case 'memory':
        return {
          type: 'memory_result',
          operation: tool.name,
          items_processed: Math.floor(Math.random() * 100),
          memory_used: Math.random() * 1024
        };
        
      case 'workflow':
        return {
          type: 'workflow_result',
          status: 'success',
          items_processed: Math.floor(Math.random() * 50)
        };
        
      default:
        return {
          type: 'generic_result',
          status: 'success',
          message: `${tool.name} executed successfully`
        };
    }
  }

  /**
   * Export workflow to file
   */
  async exportWorkflow(workflow: Workflow, filename: string): Promise<void> {
    const fs = await import('fs/promises');
    
    const exportData = {
      ...workflow,
      exportedAt: new Date().toISOString(),
      exportVersion: '1.0',
      engineVersion: '2.0.0'
    };

    await fs.writeFile(filename, JSON.stringify(exportData, null, 2));
    logger.info(`✅ Exported workflow to: ${filename}`);
  }

  /**
   * Import workflow from file
   */
  async importWorkflow(filename: string): Promise<Workflow> {
    const fs = await import('fs/promises');
    
    const data = await fs.readFile(filename, 'utf-8');
    const workflowData = JSON.parse(data);
    
    // Convert dates back to Date objects
    workflowData.metadata.created = new Date(workflowData.metadata.created);
    workflowData.metadata.lastModified = new Date(workflowData.metadata.lastModified);
    
    // Generate new ID for imported workflow
    workflowData.id = `wf_${Date.now()}`;
    workflowData.name = `${workflowData.name} (imported)`;
    
    this.workflows.set(workflowData.id, workflowData);
    
    logger.info(`✅ Imported workflow from: ${filename}`);
    return workflowData;
  }

  /**
   * Initialize collaboration features
   */
  private async initializeCollaboration(): Promise<void> {
    logger.info('🤝 Initializing collaboration features...');
    
    // Mock collaboration initialization
    // In a real implementation, this would set up WebSocket servers, etc.
    
    logger.info('✅ Collaboration features initialized');
  }

  /**
   * Enable collaboration for current session
   */
  async enableCollaboration(): Promise<void> {
    if (!this.config.enableCollaboration) {
      this.config.enableCollaboration = true;
      await this.initializeCollaboration();
    }
    
    logger.info('✅ Collaboration mode enabled');
  }
}