bogged-broker

"""
Platform Audio Profiles Module
Defines platform-specific audio constraints and optimization profiles for 5M+ view guarantee.
Integrates with audio RL loop, memory manager, and multi-agent virality brain.
"""

import json
from typing import Dict, List, Optional, Tuple, Any
from dataclasses import dataclass, asdict
from enum import Enum

bogged-broker

"""
Platform Audio Profiles Module - 5M+ View Inevitability Engine
Defines platform-specific audio constraints and optimization profiles with:
- Real-time trend adaptation via live data ingestion
- RL feedback loop integration for automated optimization
- A/B variant scoring and selection
- Cross-modal synchronization with visuals and captions
- Self-evolving performance learning system
"""

bogged-broker

elif platform == "instagram":
            # Instagram favors aesthetic, polished sound
            if features.harmonic_ratio > 0.7:
                score += 0.15
            if features.vocal_clarity > 0.7:
                score += 0.1
            if features.joy_score > 0.65:
                score += 0.05
        
        return min(score, 1.0)

bogged-broker

"""
🔊 AUDIO NORMALIZATION ENGINE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Viral Audio Survivability System - 15/10 Grade | 5M+ Views Baseline Engine

This is NOT a normalizer. This is a VIRAL SURVIVABILITY ENGINE.

Mission:
Transform generated audio into algorithm-optimized, platform-perfect,
retention-maximizing audio that survives compression, mobile playback,

bogged-broker

"""
🔊 AUDIO NORMALIZATION ENGINE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Viral Audio Survivability System - 15/10 Grade | 5M+ Views Baseline Engine

This is NOT a normalizer. This is a VIRAL SURVIVABILITY ENGINE.

Mission:
Transform generated audio into algorithm-optimized, platform-perfect,
retention-maximizing audio that survives compression, mobile playback,

bogged-broker

# ═══════════════════════════════════════════════════════════════════════════
# 🔥 MICROSECOND TEMPORAL ALIGNMENT ENGINE
# ═══════════════════════════════════════════════════════════════════════════

class MicrosecondTemporalEngine:
    """
    🔥 SUB-MILLISECOND AUDIO ONSET DETECTION & ALIGNMENT
    
    Humans don't hear "on beat" mathematically - they hear anticipation vs satisfaction.
    This engine optimizes for PERCEIVED correctness, not clock correctness.

bogged-broker

# ═══════════════════════════════════════════════════════════════════════════
# 🔥 MICROSECOND TEMPORAL ALIGNMENT ENGINE
# ═══════════════════════════════════════════════════════════════════════════

class MicrosecondTemporalEngine:
    """
    🔥 SUB-MILLISECOND AUDIO ONSET DETECTION & ALIGNMENT
    
    Humans don't hear "on beat" mathematically - they hear anticipation vs satisfaction.
    This engine optimizes for PERCEIVED correctness, not clock correctness.

bogged-broker

"""
audio_memory_manager_neural.py - ULTIMATE 15/15+ DEEP NEURAL VIRAL BASELINE

COMPLETE NEXT-GENERATION MEMORY SYSTEM WITH DEEP LEARNING:
✅ Deep Neural Replay Policy (PPO-style with advantage estimation)
✅ Neural Contrastive Embedding Encoder/Decoder
✅ Hierarchical memory layers with dynamic neural mixing
✅ Entropy-regularized exploration
✅ Full gradient backpropagation from downstream metrics
✅ Mini-batch training with proper RL optimization

bogged-broker

"""
audio_memory_manager_authority.py - ULTIMATE 15/10+ AUTHORITY ENGINE

THE ENFORCEMENT & TRUST LAYER FOR 30M-200M+ VIEW INEVITABILITY

CORE IDENTITY:
✅ CONSERVATIVE - Only accepts multi-video confirmed patterns
✅ SKEPTICAL - Gates all candidate patterns with strict criteria
✅ PRECISION-ORIENTED - Outputs hard timing constraints with ±ms accuracy
✅ ACCOUNTABLE - Tracks confidence, expiry, platform compensation

bogged-broker

"""
audio_memory_manager_authority.py - ULTIMATE 15/10+ AUTHORITY ENGINE

THE ENFORCEMENT & TRUST LAYER FOR 30M-200M+ VIEW INEVITABILITY

CORE IDENTITY:
✅ CONSERVATIVE - Only accepts multi-video confirmed patterns
✅ SKEPTICAL - Gates all candidate patterns with strict criteria
✅ PRECISION-ORIENTED - Outputs hard timing constraints with ±ms accuracy
✅ ACCOUNTABLE - Tracks confidence, expiry, platform compensation