/**
 * Multi-Agent Swarm Simulation
 *
 * Tests concurrent access and coordination using agentic-flow
 */

import { createUnifiedDatabase } from '../../src/db-unified.js';
import { ReflexionMemory } from '../../src/controllers/ReflexionMemory.js';
import { SkillLibrary } from '../../src/controllers/SkillLibrary.js';
import { EmbeddingService } from '../../src/controllers/EmbeddingService.js';
import * as path from 'path';

export default {
  description: 'Multi-agent swarm with concurrent database access',

  async run(config: any) {
    const { verbosity = 2, size = 5, parallel = true } = config;

    if (verbosity >= 2) {
      console.log(`   🤖 Initializing ${size}-Agent Swarm Simulation`);
    }

    // Initialize shared AgentDB
    const embedder = new EmbeddingService({
      model: 'Xenova/all-MiniLM-L6-v2',
      dimension: 384,
      provider: 'transformers'
    });
    await embedder.initialize();

    const db = await createUnifiedDatabase(
      path.join(process.cwd(), 'simulation', 'data', 'swarm.graph'),
      embedder,
      { forceMode: 'graph' }
    );

    const results = {
      agents: size,
      operations: 0,
      conflicts: 0,
      avgLatency: 0,
      totalTime: 0
    };

    const startTime = performance.now();

    // Simulate agent tasks
    const agentTask = async (agentId: number) => {
      const reflexion = new ReflexionMemory(
        db.getGraphDatabase() as any,
        embedder,
        undefined,
        undefined,
        db.getGraphDatabase() as any
      );

      const skills = new SkillLibrary(
        db.getGraphDatabase() as any,
        embedder,
        undefined,  // vectorBackend
        db.getGraphDatabase() as any  // graphBackend
      );

      const taskStart = performance.now();

      try {
        // Each agent stores episodes
        await reflexion.storeEpisode({
          sessionId: `agent-${agentId}`,
          task: `agent ${agentId} completing task`,
          reward: 0.8 + (Math.random() * 0.2),
          success: true
        });

        // Each agent creates skills
        await skills.createSkill({
          name: `agent-${agentId}-skill`,
          description: `Skill created by agent ${agentId}`,
          code: `function agent${agentId}() { return true; }`,
          successRate: 0.9
        });

        // Each agent searches
        await reflexion.retrieveRelevant({
          task: 'completing task',
          k: 5
        });

        const taskEnd = performance.now();
        results.operations += 3; // store + create + retrieve

        return {
          agentId,
          duration: taskEnd - taskStart,
          success: true
        };
      } catch (error) {
        results.conflicts++;
        return {
          agentId,
          duration: performance.now() - taskStart,
          success: false,
          error
        };
      }
    };

    // Execute agent tasks
    let taskResults: any[];
    if (parallel) {
      // Parallel execution
      taskResults = await Promise.all(
        Array.from({ length: size }, (_, i) => agentTask(i))
      );
    } else {
      // Sequential execution
      taskResults = [];
      for (let i = 0; i < size; i++) {
        taskResults.push(await agentTask(i));
      }
    }

    const endTime = performance.now();
    results.totalTime = endTime - startTime;

    // Calculate metrics
    const successfulTasks = taskResults.filter(r => r.success);
    results.avgLatency = successfulTasks.reduce((sum, r) => sum + r.duration, 0) / successfulTasks.length;

    db.close();

    if (verbosity >= 2) {
      console.log(`      📊 Agents: ${results.agents}`);
      console.log(`      📊 Operations: ${results.operations}`);
      console.log(`      📊 Conflicts: ${results.conflicts}`);
      console.log(`      📊 Avg Agent Latency: ${results.avgLatency.toFixed(2)}ms`);
      console.log(`      ⏱️  Total Duration: ${results.totalTime.toFixed(2)}ms`);
    }

    if (verbosity >= 3) {
      console.log(`      📋 Agent Results:`, taskResults);
    }

    return results;
  }
};