configs/phase5_config.yaml

# ================================================================
# Phase 5 Configuration — AdapterRouter Integration & Fine-tuning
# ================================================================
#
# Centralizes all Phase 5 parameters for:
# - Reinforcement learning coefficients (boost/penalize amounts)
# - Router memory integration settings
# - Gamma stabilization thresholds
# - Monitoring and observability
#
# Usage:
#   import yaml
#   with open('configs/phase5_config.yaml', 'r') as f:
#       config = yaml.safe_load(f)
#   reinforcement_cfg = ReinforcementConfig.from_dict(config['reinforcement'])
#

# ================================================================
# REINFORCEMENT LEARNING (Phase 4)
# ================================================================
# Controls how adapter weights are updated based on debate outcomes
reinforcement:
  # Boost amount when conflict resolution succeeds (resolution_rate > 40%)
  boost_successful: 0.08

  # Penalize amount when conflict gets worse (resolution_type == "worsened")
  penalize_failed: 0.08

  # Partial reward for soft progress (resolution_type == "soft_consensus")
  reward_soft_consensus: 0.03

  # Advanced: Dynamic tuning (reserved for A/B testing)
  enable_dynamic_tuning: false
  tuning_interval_queries: 100

# ================================================================
# ADAPTER ROUTER INTEGRATION (Phase 5)
# ================================================================
# Controls how memory-weighting integrates with routing decisions
adapter_router:
  # Enable memory-aware routing (use learned adapter weights)
  enable_memory_weighting: true

  # Confidence modulation strategy
  # - "soft": ±50% confidence boost/penalty (keeps keyword routing primary)
  # - "hard": Full weight-based selection (memory-first routing)
  memory_boost_strategy: "soft"

  # Range of confidence modulation [low, high]
  # soft boost adjusts confidence by ±50% = [0.5, 1.5] multiplier
  confidence_modulation_range: [0.5, 1.5]

  # Cold-start default weight for adapters with no history
  cold_start_default_weight: 1.0

  # Minimum confidences before memory boost applies
  min_confidence_to_boost: 0.2

# ================================================================
# COHERENCE FIELD GAMMA (Phase 5A)
# ================================================================
# System health monitoring and stabilization
gamma_stabilization:
  # Enable Γ (Gamma) health monitoring
  enable_gamma_field: true

  # Health score thresholds
  stable_zone: [0.4, 0.8]           # γ ∈ [0.4, 0.8] = healthy
  collapse_threshold: 0.4           # γ < 0.4 = instability
  groupthink_threshold: 0.8         # γ > 0.8 = groupthink risk

  # Target epistemic tension zone (productive conflict)
  target_tension_range: [0.1, 0.4]

  # Health metric weights (sum to 1.0)
  # How Γ is computed from component signals
  weights:
    diversity: 0.25                 # Perspectives diversity contribution
    tension: 0.25                   # Productive conflict contribution
    distribution: 0.25              # Adapter weight spreading
    resolution: 0.25                # Conflict resolution progress

  # Intervention strategies
  interventions:
    # When system collapses (γ < 0.4): inject unused perspective
    collapse_response: "diversity_injection"

    # When system groupthinks (γ > 0.8): force debate pair
    groupthink_response: "conflict_injection"

# ================================================================
# MONITORING & OBSERVABILITY
# ================================================================
# Expose metrics for real-time monitoring and debugging
monitoring:
  # Enable routing metrics tracking
  enable_routing_metrics: true

  # Log routing decisions to console/file
  log_routing_decisions: true

  # Include memory context in logs (weight explanations)
  log_memory_context: true

  # Export frequency for aggregated metrics
  metrics_export_interval_seconds: 300

  # Keep rolling window of recent routes (for /recent endpoint)
  recent_routes_window: 20

  # Log interventions (both Phase 4C runaway and Phase 5A gamma)
  log_interventions: true

  # Verbose output levels
  verbose: false
  debug_gamma: false

# ================================================================
# MEMORY INTEGRATION
# ================================================================
# Controls how LivingMemory integrates with adapter selection
memory:
  # Recompute adapter weights every N hours
  update_interval_hours: 1.0

  # Minimum memories before weighting an adapter
  min_examples_to_weight: 3

  # Recency decay half-life (older memories fade out)
  recency_half_life_days: 7

  # Edge case: disable weight clamping (for research)
  enable_weight_bounds: true
  weight_min: 0.0
  weight_max: 2.0

# ================================================================
# EDGE CASES & FALLBACKS
# ================================================================
edge_cases:
  # Cold start: no memory history yet
  cold_start_mode: "default"        # "default" | "keyword_only" | "random"

  # Adapter not found: fallback strategy
  missing_adapter_fallback: "multi_perspective"

  # Memory load fails: continue without memory?
  continue_without_memory: true

  # Router crashes: fallback to base model
  router_failure_fallback: null

  # Gamma monitoring fails
  skip_gamma_on_error: true

# ================================================================
# DEVELOPMENT & TESTING
# ================================================================
development:
  # Enable in-memory metrics tracking (slower, for testing)
  track_all_routes: false

  # Replay mode: load previous routing decisions
  replay_routing: false
  replay_file: null

  # Dry-run: log but don't execute interventions
  dry_run_gamma: false

  # Unit testing: use dummy memory
  testing_mode: false