import { SQLiteMemoryCore } from './sqlite-memory-core';
import { MemoryIntelligence } from './memory-intelligence';
import { ToolExecutor } from './tool-executor';
import { ToolRegistry } from './tool-registry';
import { Logger } from '../../utils/logger';

/**
 * @class ToolIntegration
 * @description Connects the tool ecosystem with existing systems like SQLite memory, Google AI services, and agent coordination.
 */
export class ToolIntegration {
  private dbCore: SQLiteMemoryCore;
  private memoryIntelligence: MemoryIntelligence;
  private toolExecutor: ToolExecutor;
  private toolRegistry: ToolRegistry;
  private logger: Logger;

  constructor(
    dbCore: SQLiteMemoryCore,
    memoryIntelligence: MemoryIntelligence,
    toolExecutor: ToolExecutor,
    toolRegistry: ToolRegistry
  ) {
    this.dbCore = dbCore;
    this.memoryIntelligence = memoryIntelligence;
    this.toolExecutor = toolExecutor;
    this.toolRegistry = toolRegistry;
    this.logger = new Logger('ToolIntegration');
  }

  /**
   * Integrates tool state persistence with the SQLite memory system.
   * @param {string} toolName The name of the tool.
   * @param {string} stateKey A key to store the tool's state.
   * @param {any} state The state data to persist.
   * @returns {Promise<void>}
   */
  public async persistToolState(toolName: string, stateKey: string, state: any): Promise<void> {
    this.logger.info(`Persisting state for tool ${toolName} with key ${stateKey}...`);
    const agentId = 'system_tool_agent'; // A generic agent for tool state
    const namespace = `tool_state_${toolName}`;
    const memoryId = `${agentId}-${namespace}-${stateKey}`;

    const existingMemory = await this.dbCore.getMemory(stateKey, namespace);

    if (existingMemory) {
      await this.dbCore.updateMemory(existingMemory.id, { value: JSON.stringify(state), updated_at: Date.now() });
    } else {
      await this.dbCore.insertMemory({
        id: memoryId,
        agent_id: agentId,
        key: stateKey,
        value: JSON.stringify(state),
        namespace: namespace,
        retrieval_count: 0,
        last_retrieved: undefined,
        created_at: Date.now(),
        updated_at: Date.now(),
      });
    }
    this.logger.debug(`Tool state for ${toolName}:${stateKey} persisted.`);
  }

  /**
   * Retrieves persisted tool state from the SQLite memory system.
   * @param {string} toolName The name of the tool.
   * @param {string} stateKey The key for the tool's state.
   * @returns {Promise<any | undefined>} The persisted state data.
   */
  public async retrieveToolState(toolName: string, stateKey: string): Promise<any | undefined> {
    this.logger.info(`Retrieving state for tool ${toolName} with key ${stateKey}...`);
    const namespace = `tool_state_${toolName}`;
    const memory = await this.dbCore.getMemory(stateKey, namespace);
    if (memory && memory.value) {
      this.logger.debug(`Tool state for ${toolName}:${stateKey} retrieved.`);
      return JSON.parse(memory.value);
    }
    this.logger.debug(`No tool state found for ${toolName}:${stateKey}.`);
    return undefined;
  }

  /**
   * Enhances tool capabilities by integrating with Google AI services.
   * @param {string} toolName The name of the tool to enhance.
   * @param {string} aiServiceMethod The method from a Google AI service to use.
   * @param {any[]} args Arguments for the AI service method.
   * @returns {Promise<any>}
   */
  public async enhanceToolWithAI(toolName: string, aiServiceMethod: string, args: any[]): Promise<any> {
    this.logger.info(`Enhancing tool ${toolName} with AI service: ${aiServiceMethod}...`);
    // This would involve calling a method on a Google AI service (e.g., Gemini, Vertex AI).
    // For now, it's a placeholder.
    const simulatedAIResult = `AI enhanced result for ${toolName} using ${aiServiceMethod} with args: ${JSON.stringify(args)}`;
    this.logger.debug(simulatedAIResult);
    return simulatedAIResult;
  }

  /**
   * Optimizes MCP protocol communication for tool execution.
   * @param {string} toolName The name of the tool.
   * @param {any} data The data being communicated.
   * @returns {Promise<any>} Optimized communication data.
   */
  public async optimizeMcpCommunication(toolName: string, data: any): Promise<any> {
    this.logger.info(`Optimizing MCP communication for tool ${toolName}...`);
    // This would involve:
    // - Data compression.
    // - Batching requests.
    // - Protocol-specific optimizations (e.g., gRPC for high-throughput).
    const optimizedData = { ...data, optimized: true, compression: 'gzip' };
    this.logger.debug('MCP communication optimized.', optimizedData);
    return optimizedData;
  }

  /**
   * Coordinates multiple tools for complex multi-tool workflows.
   * @param {Array<{ toolName: string, methodName: string, args: any[] }>} workflowSteps A sequence of tool calls.
   * @param {string} agentId The ID of the agent orchestrating the workflow.
   * @returns {Promise<any[]>} Results of the workflow steps.
   */
  public async coordinateMultiToolWorkflow(workflowSteps: Array<{ toolName: string, methodName: string, args: any[] }>, agentId: string): Promise<any[]> {
    this.logger.info(`Agent ${agentId} coordinating multi-tool workflow...`);
    const results: any[] = [];
    for (const step of workflowSteps) {
      this.logger.debug(`Executing workflow step: ${step.toolName}.${step.methodName}`);
      const stepResult = await this.toolExecutor.executeTool(step.toolName, step.methodName, step.args);
      results.push(stepResult);
      // Optionally, persist intermediate state or context for the agent
      await this.persistToolState(step.toolName, `${agentId}_workflow_step_result`, stepResult);
    }
    this.logger.info(`Multi-tool workflow coordinated by agent ${agentId} completed.`);
    return results;
  }

  /**
   * Sets up real-time monitoring and alerting for tool usage and performance.
   * @returns {Promise<void>}
   */
  public async setupRealtimeMonitoringAndAlerting(): Promise<void> {
    this.logger.info('Setting up real-time tool monitoring and alerting...');
    // This would involve:
    // - Registering metrics with a monitoring system (e.g., Cloud Monitoring).
    // - Defining alert policies based on tool performance (latency, error rate).
    // - Sending notifications to relevant channels.

    // Simulate a periodic check for tool performance
    setInterval(async () => {
      const allTools = this.toolRegistry.listAllToolMetadata();
      for (const tool of allTools) {
        if (tool.errorRate > 0.1) {
          this.logger.warn(`ALERT: High error rate (${(tool.errorRate * 100).toFixed(2)}%) for tool: ${tool.name}`);
          // Trigger actual alert (e.g., send to Cloud Monitoring, Pub/Sub, or email)
        }
        if (tool.avgExecutionTime > 1000) {
          this.logger.warn(`ALERT: High average execution time (${tool.avgExecutionTime.toFixed(2)}ms) for tool: ${tool.name}`);
        }
      }
    }, 5 * 60 * 1000); // Check every 5 minutes

    this.logger.info('Real-time monitoring and alerting configured.');
  }
}