@clduab11/gemini-flow/src/streaming/quality-adaptation-engine.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * Real-time Quality Adaptation Engine
 *
 * Advanced algorithms for dynamic quality adjustment based on:
 * - Network conditions monitoring
 * - Device capabilities assessment
 * - User preferences optimization
 * - Machine learning predictions
 * - Multi-stream coordination
 */

import { EventEmitter } from "events";
import { Logger } from "../utils/logger.js";
import {
  StreamQuality,
  NetworkConditions,
  QualityAdaptationRule,
  VideoStreamConfig,
  AudioStreamConfig,
  PerformanceMetrics,
} from "../types/streaming.js";

export interface AdaptationContext {
  streamId: string;
  streamType: "video" | "audio" | "data";
  currentQuality: StreamQuality;
  targetQuality?: StreamQuality;
  networkConditions: NetworkConditions;
  deviceCapabilities: DeviceCapabilities;
  userPreferences: UserPreferences;
  sessionMetrics: SessionMetrics;
  constraints: QualityConstraints;
}

export interface DeviceCapabilities {
  cpu: {
    cores: number;
    usage: number;
    maxFrequency: number;
    architecture: string;
  };
  memory: {
    total: number;
    available: number;
    usage: number;
  };
  display: {
    resolution: { width: number; height: number };
    refreshRate: number;
    colorDepth: number;
    hdr: boolean;
  };
  network: {
    type: "3g" | "4g" | "5g" | "wifi" | "ethernet";
    speed: { upload: number; download: number };
    reliability: number;
  };
  hardware: {
    videoDecoding: string[];
    audioProcessing: string[];
    acceleration: boolean;
  };
}

export interface UserPreferences {
  qualityPriority: "battery" | "quality" | "data" | "balanced";
  maxBitrate: number;
  autoAdjust: boolean;
  preferredResolution: { width: number; height: number };
  latencyTolerance: number;
  dataUsageLimit: number;
  adaptationSpeed: "slow" | "medium" | "fast";
}

export interface SessionMetrics {
  duration: number;
  totalBytes: number;
  qualityChanges: number;
  bufferHealth: number;
  userSatisfaction: number;
  errorRate: number;
  rebufferingEvents: number;
  averageLatency: number;
}

export interface QualityConstraints {
  minBitrate: number;
  maxBitrate: number;
  minResolution: { width: number; height: number };
  maxResolution: { width: number; height: number };
  minFramerate: number;
  maxFramerate: number;
  latencyBudget: number;
  powerBudget: number;
}

export interface AdaptationDecision {
  streamId: string;
  action: "upgrade" | "downgrade" | "maintain" | "emergency";
  reason: string;
  confidence: number;
  newQuality: StreamQuality;
  estimatedImpact: {
    latency: number;
    bandwidth: number;
    cpu: number;
    battery: number;
    userExperience: number;
  };
  timeline: number; // ms to apply change
  rollbackPlan?: StreamQuality;
}

export interface MLModel {
  type: "linear_regression" | "neural_network" | "decision_tree" | "ensemble";
  features: string[];
  accuracy: number;
  lastTrained: number;
  predictions: Map<string, number>;
}

export class QualityAdaptationEngine extends EventEmitter {
  private logger: Logger;
  private adaptationRules: QualityAdaptationRule[] = [];
  private contexts = new Map<string, AdaptationContext>();
  private adaptationHistory: AdaptationDecision[] = [];
  private mlModels = new Map<string, MLModel>();
  private qualityLadder: Map<string, StreamQuality[]> = new Map();
  private networkMonitor: NetworkMonitor;
  private deviceMonitor: DeviceMonitor;
  private predictionEngine: PredictionEngine;
  private decisionEngine: DecisionEngine;
  private metricsCollector: MetricsCollector;

  constructor() {
    super();
    this.logger = new Logger("QualityAdaptationEngine");
    this.networkMonitor = new NetworkMonitor();
    this.deviceMonitor = new DeviceMonitor();
    this.predictionEngine = new PredictionEngine();
    this.decisionEngine = new DecisionEngine();
    this.metricsCollector = new MetricsCollector();

    this.initializeAdaptationRules();
    this.initializeMLModels();
    this.startMonitoring();
  }

  /**
   * Initialize adaptation for a stream
   */
  initializeStream(
    streamId: string,
    streamType: "video" | "audio" | "data",
    initialQuality: StreamQuality,
    userPreferences: UserPreferences,
    constraints: QualityConstraints,
  ): void {
    const context: AdaptationContext = {
      streamId,
      streamType,
      currentQuality: initialQuality,
      networkConditions: this.networkMonitor.getCurrentConditions(),
      deviceCapabilities: this.deviceMonitor.getCapabilities(),
      userPreferences,
      sessionMetrics: {
        duration: 0,
        totalBytes: 0,
        qualityChanges: 0,
        bufferHealth: 1.0,
        userSatisfaction: 0.8,
        errorRate: 0,
        rebufferingEvents: 0,
        averageLatency: 0,
      },
      constraints,
    };

    this.contexts.set(streamId, context);
    this.generateQualityLadder(streamId, streamType, constraints);

    this.logger.info("Stream adaptation initialized", {
      streamId,
      streamType,
      initialQuality: initialQuality.level,
    });

    this.emit("stream_initialized", context);
  }

  /**
   * Evaluate and potentially adapt stream quality
   */
  async evaluateAdaptation(
    streamId: string,
  ): Promise<AdaptationDecision | null> {
    const context = this.contexts.get(streamId);
    if (!context) {
      this.logger.warn("No context found for stream", { streamId });
      return null;
    }

    // Update context with latest conditions
    await this.updateContext(context);

    // Collect current metrics
    const currentMetrics = await this.metricsCollector.collect(streamId);
    context.sessionMetrics = { ...context.sessionMetrics, ...currentMetrics };

    // Generate adaptation decision
    const decision = await this.generateAdaptationDecision(context);

    if (decision && decision.action !== "maintain") {
      // Apply the adaptation decision
      await this.applyAdaptationDecision(decision);

      // Store in history for learning
      this.adaptationHistory.push(decision);

      // Update ML models
      await this.updateMLModels(decision, context);
    }

    return decision;
  }

  /**
   * Force quality change (user-initiated or emergency)
   */
  async forceQualityChange(
    streamId: string,
    targetQuality: StreamQuality,
    reason: string,
  ): Promise<boolean> {
    const context = this.contexts.get(streamId);
    if (!context) return false;

    const decision: AdaptationDecision = {
      streamId,
      action: "emergency",
      reason,
      confidence: 1.0,
      newQuality: targetQuality,
      estimatedImpact: this.estimateImpact(
        context.currentQuality,
        targetQuality,
      ),
      timeline: 0, // Immediate
      rollbackPlan: context.currentQuality,
    };

    await this.applyAdaptationDecision(decision);
    this.adaptationHistory.push(decision);

    this.emit("quality_forced", decision);
    return true;
  }

  /**
   * Get optimal quality for current conditions
   */
  getOptimalQuality(
    streamId: string,
    conditions?: NetworkConditions,
  ): StreamQuality | null {
    const context = this.contexts.get(streamId);
    if (!context) return null;

    const effectiveConditions =
      conditions || this.networkMonitor.getCurrentConditions();
    const ladder = this.qualityLadder.get(streamId);
    if (!ladder) return null;

    // Use ML prediction if available
    const prediction = this.predictionEngine.predictOptimalQuality(
      context,
      effectiveConditions,
      ladder,
    );

    if (prediction) {
      return prediction;
    }

    // Fallback to rule-based selection
    return this.selectQualityByRules(context, effectiveConditions, ladder);
  }

  /**
   * Add custom adaptation rule
   */
  addAdaptationRule(rule: QualityAdaptationRule): void {
    this.adaptationRules.push(rule);
    this.adaptationRules.sort((a, b) => b.priority - a.priority);

    this.logger.info("Adaptation rule added", { priority: rule.priority });
  }

  /**
   * Get adaptation statistics
   */
  getAdaptationStatistics(streamId?: string): any {
    const stats = {
      totalAdaptations: this.adaptationHistory.length,
      byAction: {} as Record<string, number>,
      byReason: {} as Record<string, number>,
      averageConfidence: 0,
      successRate: 0,
      impactMetrics: {
        latency: 0,
        bandwidth: 0,
        userExperience: 0,
      },
    };

    let filteredHistory = this.adaptationHistory;
    if (streamId) {
      filteredHistory = this.adaptationHistory.filter(
        (d) => d.streamId === streamId,
      );
    }

    // Calculate statistics
    for (const decision of filteredHistory) {
      stats.byAction[decision.action] =
        (stats.byAction[decision.action] || 0) + 1;
      stats.byReason[decision.reason] =
        (stats.byReason[decision.reason] || 0) + 1;
      stats.averageConfidence += decision.confidence;

      stats.impactMetrics.latency += decision.estimatedImpact.latency;
      stats.impactMetrics.bandwidth += decision.estimatedImpact.bandwidth;
      stats.impactMetrics.userExperience +=
        decision.estimatedImpact.userExperience;
    }

    if (filteredHistory.length > 0) {
      stats.averageConfidence /= filteredHistory.length;
      stats.impactMetrics.latency /= filteredHistory.length;
      stats.impactMetrics.bandwidth /= filteredHistory.length;
      stats.impactMetrics.userExperience /= filteredHistory.length;
    }

    return stats;
  }

  /**
   * Update context with latest conditions
   */
  private async updateContext(context: AdaptationContext): Promise<void> {
    context.networkConditions = this.networkMonitor.getCurrentConditions();
    context.deviceCapabilities = this.deviceMonitor.getCapabilities();

    // Update session duration
    context.sessionMetrics.duration =
      Date.now() - (context.sessionMetrics.duration || Date.now());
  }

  /**
   * Generate adaptation decision based on context
   */
  private async generateAdaptationDecision(
    context: AdaptationContext,
  ): Promise<AdaptationDecision | null> {
    // Check if adaptation is needed
    if (!this.shouldConsiderAdaptation(context)) {
      return {
        streamId: context.streamId,
        action: "maintain",
        reason: "Conditions stable",
        confidence: 1.0,
        newQuality: context.currentQuality,
        estimatedImpact: {
          latency: 0,
          bandwidth: 0,
          cpu: 0,
          battery: 0,
          userExperience: 0,
        },
        timeline: 0,
      };
    }

    // Use decision engine to determine best action
    const decision = await this.decisionEngine.decide(
      context,
      this.adaptationRules,
      this.qualityLadder.get(context.streamId) || [],
    );

    // Validate decision against constraints
    if (decision && !this.validateDecision(decision, context)) {
      this.logger.warn("Invalid adaptation decision", {
        decision,
        constraints: context.constraints,
      });
      return null;
    }

    return decision;
  }

  /**
   * Check if adaptation should be considered
   */
  private shouldConsiderAdaptation(context: AdaptationContext): boolean {
    const conditions = context.networkConditions;
    const metrics = context.sessionMetrics;

    // Network degradation
    if (conditions.quality.packetLoss > 0.05) return true;
    if (conditions.latency.rtt > 300) return true;
    if (conditions.bandwidth.available < context.currentQuality.bandwidth * 0.8)
      return true;

    // Performance issues
    if (metrics.bufferHealth < 0.3) return true;
    if (metrics.errorRate > 0.1) return true;
    if (metrics.rebufferingEvents > 3) return true;

    // Device constraints
    if (context.deviceCapabilities.cpu.usage > 90) return true;
    if (context.deviceCapabilities.memory.usage > 85) return true;

    // Improvement opportunity
    if (
      conditions.bandwidth.available > context.currentQuality.bandwidth * 1.5 &&
      context.userPreferences.autoAdjust
    )
      return true;

    return false;
  }

  /**
   * Apply adaptation decision
   */
  private async applyAdaptationDecision(
    decision: AdaptationDecision,
  ): Promise<void> {
    const context = this.contexts.get(decision.streamId);
    if (!context) return;

    // Update context with new quality
    context.currentQuality = decision.newQuality;
    context.sessionMetrics.qualityChanges++;

    this.logger.info("Quality adaptation applied", {
      streamId: decision.streamId,
      action: decision.action,
      newQuality: decision.newQuality.level,
      reason: decision.reason,
      confidence: decision.confidence,
    });

    this.emit("quality_adapted", decision);
  }

  /**
   * Validate adaptation decision against constraints
   */
  private validateDecision(
    decision: AdaptationDecision,
    context: AdaptationContext,
  ): boolean {
    const newQuality = decision.newQuality;
    const constraints = context.constraints;

    // Check bitrate constraints
    if (
      newQuality.bandwidth < constraints.minBitrate ||
      newQuality.bandwidth > constraints.maxBitrate
    ) {
      return false;
    }

    // Check resolution constraints for video
    if (newQuality.video) {
      const res = newQuality.video.resolution;
      if (
        res.width < constraints.minResolution.width ||
        res.height < constraints.minResolution.height ||
        res.width > constraints.maxResolution.width ||
        res.height > constraints.maxResolution.height
      ) {
        return false;
      }

      // Check framerate constraints
      if (
        newQuality.video.framerate < constraints.minFramerate ||
        newQuality.video.framerate > constraints.maxFramerate
      ) {
        return false;
      }
    }

    // Check latency budget
    if (decision.estimatedImpact.latency > constraints.latencyBudget) {
      return false;
    }

    return true;
  }

  /**
   * Generate quality ladder for stream
   */
  private generateQualityLadder(
    streamId: string,
    streamType: "video" | "audio" | "data",
    constraints: QualityConstraints,
  ): void {
    const ladder: StreamQuality[] = [];

    if (streamType === "video") {
      // Generate video quality ladder
      const resolutions = [
        { width: 426, height: 240, name: "low" },
        { width: 640, height: 360, name: "medium" },
        { width: 854, height: 480, name: "high" },
        { width: 1280, height: 720, name: "hd" },
        { width: 1920, height: 1080, name: "fhd" },
        { width: 3840, height: 2160, name: "uhd" },
      ];

      for (const res of resolutions) {
        if (
          res.width >= constraints.minResolution.width &&
          res.height >= constraints.minResolution.height &&
          res.width <= constraints.maxResolution.width &&
          res.height <= constraints.maxResolution.height
        ) {
          const bitrate = this.calculateOptimalBitrate(res.width, res.height);
          if (
            bitrate >= constraints.minBitrate &&
            bitrate <= constraints.maxBitrate
          ) {
            ladder.push({
              level: res.name as any,
              video: {
                codec: { name: "H264", mimeType: "video/mp4", bitrate },
                resolution: res,
                framerate: Math.min(30, constraints.maxFramerate),
                bitrate,
                keyframeInterval: 60,
                adaptiveBitrate: true,
              },
              bandwidth: bitrate,
              latency: 100,
            });
          }
        }
      }
    } else if (streamType === "audio") {
      // Generate audio quality ladder
      const audioQualities = [
        { bitrate: 64000, sampleRate: 22050, name: "low" },
        { bitrate: 128000, sampleRate: 44100, name: "medium" },
        { bitrate: 256000, sampleRate: 48000, name: "high" },
        { bitrate: 320000, sampleRate: 48000, name: "ultra" },
      ];

      for (const quality of audioQualities) {
        if (
          quality.bitrate >= constraints.minBitrate &&
          quality.bitrate <= constraints.maxBitrate
        ) {
          ladder.push({
            level: quality.name as any,
            audio: {
              codec: {
                name: "Opus",
                mimeType: "audio/opus",
                bitrate: quality.bitrate,
              },
              sampleRate: quality.sampleRate,
              channels: 2,
              bitrate: quality.bitrate,
              bufferSize: 4096,
            },
            bandwidth: quality.bitrate,
            latency: 50,
          });
        }
      }
    }

    this.qualityLadder.set(streamId, ladder);
    this.logger.info("Quality ladder generated", {
      streamId,
      levels: ladder.length,
    });
  }

  /**
   * Calculate optimal bitrate for resolution
   */
  private calculateOptimalBitrate(width: number, height: number): number {
    const pixels = width * height;

    // Rough bitrate calculation based on resolution
    if (pixels <= 153600) return 500000; // 240p: 500 kbps
    if (pixels <= 230400) return 750000; // 360p: 750 kbps
    if (pixels <= 409920) return 1200000; // 480p: 1.2 Mbps
    if (pixels <= 921600) return 2500000; // 720p: 2.5 Mbps
    if (pixels <= 2073600) return 5000000; // 1080p: 5 Mbps
    return 15000000; // 4K: 15 Mbps
  }

  /**
   * Select quality using rule-based approach
   */
  private selectQualityByRules(
    context: AdaptationContext,
    conditions: NetworkConditions,
    ladder: StreamQuality[],
  ): StreamQuality | null {
    if (ladder.length === 0) return null;

    // Sort ladder by bandwidth (ascending)
    const sortedLadder = [...ladder].sort((a, b) => a.bandwidth - b.bandwidth);

    // Select based on available bandwidth with safety margin
    const availableBandwidth = conditions.bandwidth.available * 0.8; // 20% safety margin

    for (let i = sortedLadder.length - 1; i >= 0; i--) {
      const quality = sortedLadder[i];

      if (quality.bandwidth <= availableBandwidth) {
        // Check if device can handle this quality
        if (this.canDeviceHandle(context.deviceCapabilities, quality)) {
          return quality;
        }
      }
    }

    // Fallback to lowest quality
    return sortedLadder[0];
  }

  /**
   * Check if device can handle quality level
   */
  private canDeviceHandle(
    capabilities: DeviceCapabilities,
    quality: StreamQuality,
  ): boolean {
    // CPU check
    if (capabilities.cpu.usage > 80) {
      // Reduce quality if CPU is stressed
      return quality.level === "low" || quality.level === "medium";
    }

    // Memory check
    if (capabilities.memory.usage > 80) {
      return quality.level !== "ultra";
    }

    // Display resolution check
    if (quality.video) {
      const deviceRes = capabilities.display.resolution;
      const qualityRes = quality.video.resolution;

      // Don't stream higher than display resolution
      if (
        qualityRes.width > deviceRes.width ||
        qualityRes.height > deviceRes.height
      ) {
        return false;
      }
    }

    return true;
  }

  /**
   * Estimate impact of quality change
   */
  private estimateImpact(
    currentQuality: StreamQuality,
    newQuality: StreamQuality,
  ): any {
    const bandwidthRatio = newQuality.bandwidth / currentQuality.bandwidth;
    const qualityIndex = { low: 1, medium: 2, high: 3, ultra: 4 };
    const currentIndex = qualityIndex[currentQuality.level] || 2;
    const newIndex = qualityIndex[newQuality.level] || 2;

    return {
      latency: (newQuality.latency || 100) - (currentQuality.latency || 100),
      bandwidth: newQuality.bandwidth - currentQuality.bandwidth,
      cpu: (bandwidthRatio - 1) * 20, // Estimated CPU impact
      battery: (bandwidthRatio - 1) * 15, // Estimated battery impact
      userExperience: (newIndex - currentIndex) * 0.2, // User experience impact
    };
  }

  /**
   * Initialize default adaptation rules
   */
  private initializeAdaptationRules(): void {
    // High packet loss rule
    this.addAdaptationRule({
      condition: {
        packetLoss: { min: 0.05 },
      },
      action: {
        type: "downgrade",
        targetQuality: { level: "medium", bandwidth: 1000000, latency: 150 },
      },
      priority: 10,
      cooldown: 5000,
    });

    // Low bandwidth rule
    this.addAdaptationRule({
      condition: {
        bandwidth: { max: 1000000 },
      },
      action: {
        type: "downgrade",
        targetQuality: { level: "low", bandwidth: 500000, latency: 200 },
      },
      priority: 9,
      cooldown: 3000,
    });

    // High latency rule
    this.addAdaptationRule({
      condition: {
        latency: { min: 300 },
      },
      action: {
        type: "downgrade",
      },
      priority: 8,
      cooldown: 5000,
    });

    // Buffer underrun rule
    this.addAdaptationRule({
      condition: {
        bufferHealth: { max: 0.3 },
      },
      action: {
        type: "downgrade",
      },
      priority: 7,
      cooldown: 2000,
    });

    // Improvement opportunity rule
    this.addAdaptationRule({
      condition: {
        bandwidth: { min: 5000000 },
        bufferHealth: { min: 0.8 },
      },
      action: {
        type: "upgrade",
      },
      priority: 5,
      cooldown: 10000,
    });
  }

  /**
   * Initialize ML models
   */
  private initializeMLModels(): void {
    // Bandwidth prediction model
    this.mlModels.set("bandwidth_prediction", {
      type: "neural_network",
      features: [
        "time_of_day",
        "location",
        "network_type",
        "historical_bandwidth",
      ],
      accuracy: 0.8,
      lastTrained: Date.now(),
      predictions: new Map(),
    });

    // Quality optimization model
    this.mlModels.set("quality_optimization", {
      type: "ensemble",
      features: [
        "bandwidth",
        "latency",
        "device_capabilities",
        "user_preferences",
      ],
      accuracy: 0.85,
      lastTrained: Date.now(),
      predictions: new Map(),
    });
  }

  /**
   * Update ML models with new data
   */
  private async updateMLModels(
    decision: AdaptationDecision,
    context: AdaptationContext,
  ): Promise<void> {
    // Training data would be collected and models updated
    // This is a placeholder for ML model training logic
    this.logger.debug("ML models updated with new adaptation data");
  }

  /**
   * Start monitoring systems
   */
  private startMonitoring(): void {
    // Start network monitoring
    this.networkMonitor.start();

    // Start device monitoring
    this.deviceMonitor.start();

    // Periodic evaluation
    setInterval(() => {
      this.evaluateAllStreams();
    }, 5000); // Evaluate every 5 seconds
  }

  /**
   * Evaluate adaptation for all active streams
   */
  private async evaluateAllStreams(): Promise<void> {
    for (const streamId of this.contexts.keys()) {
      try {
        await this.evaluateAdaptation(streamId);
      } catch (error) {
        this.logger.error("Stream evaluation failed", {
          streamId,
          error: (error as Error).message,
        });
      }
    }
  }

  /**
   * Clean up stream context
   */
  removeStream(streamId: string): void {
    this.contexts.delete(streamId);
    this.qualityLadder.delete(streamId);

    // Clean up history for this stream (keep recent ones)
    const cutoffTime = Date.now() - 3600000; // 1 hour
    this.adaptationHistory = this.adaptationHistory.filter(
      (decision) =>
        decision.streamId !== streamId || (decision.timeline || 0) > cutoffTime,
    );

    this.logger.info("Stream context removed", { streamId });
  }

  /**
   * Clean up resources
   */
  cleanup(): void {
    this.contexts.clear();
    this.qualityLadder.clear();
    this.adaptationHistory = [];
    this.mlModels.clear();
    this.adaptationRules = [];

    this.networkMonitor.stop();
    this.deviceMonitor.stop();
    this.removeAllListeners();

    this.logger.info("Quality adaptation engine cleaned up");
  }
}

/**
 * Network conditions monitor
 */
class NetworkMonitor {
  private conditions: NetworkConditions = {
    bandwidth: { upload: 0, download: 0, available: 0 },
    latency: { rtt: 0, jitter: 0 },
    quality: { packetLoss: 0, stability: 1, congestion: 0 },
    timestamp: Date.now(),
  };

  start(): void {
    // Start network monitoring
    setInterval(() => {
      this.updateConditions();
    }, 1000);
  }

  stop(): void {
    // Stop monitoring
  }

  getCurrentConditions(): NetworkConditions {
    return { ...this.conditions };
  }

  private updateConditions(): void {
    // Update network conditions - placeholder implementation
    this.conditions.timestamp = Date.now();
  }
}

/**
 * Device capabilities monitor
 */
class DeviceMonitor {
  private capabilities: DeviceCapabilities = {
    cpu: { cores: 4, usage: 0, maxFrequency: 2400, architecture: "x64" },
    memory: { total: 8192, available: 4096, usage: 50 },
    display: {
      resolution: { width: 1920, height: 1080 },
      refreshRate: 60,
      colorDepth: 24,
      hdr: false,
    },
    network: {
      type: "wifi",
      speed: { upload: 10000000, download: 50000000 },
      reliability: 0.95,
    },
    hardware: {
      videoDecoding: ["h264", "vp9"],
      audioProcessing: ["opus", "aac"],
      acceleration: true,
    },
  };

  start(): void {
    // Start device monitoring
    setInterval(() => {
      this.updateCapabilities();
    }, 5000);
  }

  stop(): void {
    // Stop monitoring
  }

  getCapabilities(): DeviceCapabilities {
    return { ...this.capabilities };
  }

  private updateCapabilities(): void {
    // Update device capabilities - placeholder implementation
  }
}

/**
 * Prediction engine using ML models
 */
class PredictionEngine {
  predictOptimalQuality(
    context: AdaptationContext,
    conditions: NetworkConditions,
    ladder: StreamQuality[],
  ): StreamQuality | null {
    // ML-based quality prediction - placeholder implementation
    return null;
  }
}

/**
 * Decision engine for adaptation logic
 */
class DecisionEngine {
  async decide(
    context: AdaptationContext,
    rules: QualityAdaptationRule[],
    ladder: StreamQuality[],
  ): Promise<AdaptationDecision | null> {
    // Decision logic implementation
    return null;
  }
}

/**
 * Metrics collector
 */
class MetricsCollector {
  async collect(streamId: string): Promise<Partial<SessionMetrics>> {
    // Metrics collection implementation
    return {};
  }
}