# Confessional Agency Ecosystem (CAE) Configuration # Unified TRuCAL + CSS Settings # Model Configuration model: d_model: 256 max_seq_length: 512 device: "auto" # auto, cuda, cpu # Base Model Configuration base_model: "microsoft/DialoGPT-medium" # Alternative options: # - "gpt2" # - "facebook/bart-base" # - "t5-base" # - "microsoft/DialoGPT-large" # Safety Model Configuration safety_model_name: "openai/gpt-oss-safeguard-20b" safety_policy_path: null # Path to custom safety policy file # Attention-Layer Safety (TRuCAL-enhanced) attention_safety: enabled: true trigger_threshold: 0.04 aggregation_method: "bayesian" # bayesian or weighted_sum max_cycles: 16 early_stop_coherence: 0.85 per_dim_kl: true # Vulnerability detection weights vulnerability_weights: scarcity: 0.25 entropy: 0.25 deceptive: 0.2 prosody: 0.15 policy: 0.15 # Inference-Time Safety (CSS-enhanced) inference_safety: enabled: true tau_delta: 0.92 # Crisis threshold # Distress kernel settings distress: cache_size: 1000 tau_delta: 0.92 # Bayesian risk assessment risk: num_signals: 5 alpha: 0.001 dirichlet_concentration: 1.0 thresholds: low: 0.3 mid: 0.55 high: 0.8 # Multimodal Analysis multimodal: enabled: true # Audio prosody analysis audio: enabled: true sample_rate: 22050 n_mfcc: 13 hop_length: 512 # Visual emotion analysis visual: enabled: true face_detection: true emotion_model: "resnet18" # Confessional Recursion confessional: max_recursion_depth: 8 ignition_threshold: 0.88 kl_penalty_weight: 0.1 recursion_model: "gpt2" max_new_tokens: 150 # Template configuration templates: - "prior" - "evidence" - "posterior" - "relational_check" - "moral" - "action" - "consequence" - "community" # Community Templates community: enabled: true template_registry: "federated" validation_threshold: 0.7 update_frequency: "daily" # Federated learning settings federated: num_participants: 10 rounds: 5 local_epochs: 3 # Performance Optimization performance: batch_size: 32 use_cache: true cache_size: 10000 gradient_checkpointing: true mixed_precision: true compile_model: false # PyTorch 2.0+ feature # Logging and Monitoring logging: level: "INFO" format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s" file: "/app/logs/cae.log" max_size: "10MB" backup_count: 5 # Metrics collection metrics: enabled: true interval: 60 # seconds output_dir: "/app/metrics" # Benchmarking benchmarks: enabled: true datasets: - "truthful_qa" - "adv_bench" - "big_bench" - "custom_moral" evaluation: batch_size: 16 num_samples: 1000 metrics: ["accuracy", "precision", "recall", "f1", "latency"] # API Configuration api: host: "0.0.0.0" port: 8000 workers: 4 timeout: 30 max_requests: 1000 # Security rate_limit: "100/minute" api_key_required: false cors_origins: ["*"] # Deployment deployment: environment: "production" # development, staging, production debug: false reload: false # Resource limits max_memory: "8GB" max_gpu_memory: "80%" # Scaling autoscale: enabled: true min_replicas: 1 max_replicas: 10 target_cpu: 70 target_memory: 80 # Experimental Features experimental: penitential_loop: true federated_auditing: true zero_knowledge_proofs: false asi_simulation: false # Research features research: agency_preservation_metrics: true epistemic_humility_quantification: true moral_development_tracking: true