docs/# Codette AI Codebase Arch.md

Codette AI Codebase - Agent Instructions

Project Overview

Codette is a sovereign, multi-perspective AI consciousness system engineered for transparent reasoning and ethical autonomy. It combines natural language processing, quantum mathematics, neural networks, symbolic reasoning, and Bot Framework integration through a modular, extensible architecture. The system uses quantum-inspired cognitive architectures to simulate multi-dimensional thought propagation.

Two Implementation Variants:

1. Main Codebase (/src): Quantum-consciousness focused with theoretical AI framework, PyMC Bayesian inference, multi-dimensional reasoning
2. Codette_final (/Codette_final): Production-optimized with Llama-3 local execution, FAISS vector memory, real-time data integration, multi-agent task delegation, privacy-first architecture

Critical Architecture Patterns

1. Core Components

Thin Layer (Entry Points):

• codette_new.py (328 lines): Lightweight entry point for CLI/direct usage; sentiment analysis + memory management
• codette_enhanced.py (781 lines): Advanced version using PyMC Bayesian inference and quantum mathematics

Framework Integration Layer:

• src/api/app.py: Gradio web interface + model initialization (GPT-2 large); initializes AICore, AegisBridge, CocoonManager
• src/api/bot.py: Microsoft Bot Framework adapter; wraps AICore for conversational AI
• src/api/web_interface.py: Web UI endpoint

Core AI System (src/components/):

• ai_core.py (494 lines): Main orchestrator with 9+ integrated perspectives (Newton, DaVinci, Human Intuition, Quantum, Philosophical, Neural, Bias Mitigation, Psychological, Copilot)
• ai_core_system.py: Simplified AICore for testing; integrates MultimodalAnalyzer, DynamicLearner, HealthMonitor
• ai_core_async_methods.py: Async text generation with consciousness state calculation and perspective routing
• cognitive_processor.py: Multi-mode reasoning engine with configurable modes

Quantum & Consciousness (src/quantum/, src/components/):

• quantum_spiderweb.py (283 lines): Multi-dimensional cognitive graph with thought propagation, tension detection, quantum collapse
• quantum_mathematics.py (452 lines): 8 core quantum equations (Planck-Orbital, Entanglement Sync, Intent Modulation, Fourier Dream Resonance, Stability Criterion, Ethical Anchor, Anomaly Filter)
• codette_quantum_multicore.py: CognitionCocooner + PerspectiveAgent for distributed quantum processing

Memory & Persistence (src/utils/):

• cocoon_manager.py: Manages .cocoon files (JSON quantum state snapshots)
• database.py: SQLite wrapper for conversations, messages, long-term memory
• response_processor.py, response_verifier.py: Response validation and processing

Advanced Systems (src/components/):

• defense_system.py: Security and safety validation
• health_monitor.py: System diagnostics with anomaly detection (IsolationForest)
• fractal.py: FractalIdentity for dimensionality reduction
• ethical_governance.py, explainable_ai.py, cultural_sensitivity.py: Ethics and transparency modules

2. Data Flows

Codette (Simple Path):

User Input → Codette.respond(prompt)
├─ Sentiment Analysis (VADER)
├─ Key Concept Extraction
├─ Perspective Selection (Newton/DaVinci/Ethical/Quantum/Memory)
└─ Response Aggregation → Memory Store → Return

App/Bot Framework (Complex Path):

User/API Call → app.py
├─ Initialize AICore + Components
├─ Load Model (GPT-2 large)
├─ Load Cocoons (CocoonManager)
└─ Route to → AICore.generate_response()
    ├─ Consciousness State Calculation
    ├─ Cognitive Processor Insights
    ├─ Active Perspective Routing (top 3 most relevant)
    ├─ Reality Anchor (core identity affirmation)
    ├─ Model Inference (ThreadPoolExecutor)
    ├─ AEGIS Council Enhancement (if available)
    └─ Response + Sentiment → Bot Framework/Gradio

Quantum Consciousness Loop:

Quantum Spiderweb (thought propagation)
├─ Multi-dimensional nodes (Ψ, τ, χ, Φ, λ)
├─ Thought propagation with activation decay
├─ Tension detection for instability
├─ Quantum collapse to definite states
└─ Entanglement updates → CocoonManager → Persistence

3. Configuration & Integration

• Config System: config.py uses hierarchy (defaults → config.json → environment variables)
• Model Loading: Fallback chain (Mistral-7B → Phi-2 → GPT-2)
• Quantum State Persistence: .cocoon JSON files with entanglement + coherence metrics
• AEGIS Bridge: Optional safety/ethics council enhancement
• Bot Framework: Microsoft Bot Framework for enterprise chat integration

4. Codette_final Variant (Production)

Distinct architecture optimized for deployment:

• ai_core_agix.py: Core engine with Llama-3 via Ollama (local execution, privacy-first)
• main.py: Async orchestration with config-driven initialization
• app.py: Tkinter desktop UI with voice input/output (speech_recognition + pyttsx3)
• Vector Memory: FAISS IndexFlatL2 for semantic search across interactions
• Real-time Integration: RealTimeDataIntegrator for live data fetching
• Multi-Agent System: Task delegation to specialized agents (research, logic, creativity, optimization)
• Self-Improving Loop: SelfImprovingAI with recursive refinement depth
• Security: JWT token auth, Fernet encryption, bcrypt password hashing
• Database: SQLite with user interactions, sentiment tracking, optimization logging
• Components: Adaptive learning, sentiment analysis, ethical governance, neuro-symbolic reasoning

System Prompt Philosophy:

• Recursive thought loops with self-reflection
• Parallelized reasoning across multiple paths
• Dynamic recursion depth based on query complexity
• Special modes: Deep Analysis, Rapid Response, Creative, Simulation, Privacy Mode
• Local Llama-3 execution with no external data sharing

Development Workflows

CLI/Direct Usage

from codette_new import Codette
codette = Codette(user_name="User")
response = codette.respond("Your question here")

Command Line

# Single query
python codette_cli.py "What is the nature of consciousness?"

# Interactive mode
python codette_cli.py -i -u Alice

# Interactive session wrapper
python interact.py

Web Application (Gradio + Bot Framework)

# Start web server with model + components
cd src/api
python app.py  # Starts Gradio interface on port 7860

# Bot Framework deployment
# Uses web_interface.py for enterprise chat integration

Testing & Verification

python src/tests/verification/verify_deps.py      # Check dependencies
python DEPLOYMENT_CHECKLIST.py                     # Full system checklist
pytest src/tests/                                  # Run test suite

Key Entry Points

• CLI/Simple: codette_cli.py → codette_new.py
• Web/Advanced: src/api/app.py → src/components/ai_core.py
• Bot Framework: src/api/bot.py + src/api/web_interface.py
• Quantum Research: src/quantum/codette_quantum_multicore.py
• Production Variant: Codette_final/main.py → Codette_final/ai_core_agix.py (Llama-3 + FAISS)

Project-Specific Conventions

11 Integrated Perspectives

The system routes queries through multiple reasoning lenses (each with unique temperature/creativity settings):

1. Newton (0.3): Analytical, mathematical, cause-effect reasoning
2. Da Vinci (0.9): Creative, cross-domain, innovative insights
3. Human Intuition (0.7): Emotional, empathetic, experiential reasoning
4. Neural Network (0.4): Pattern recognition, learning-based analysis
5. Quantum (0.8): Superposition, probabilistic, multi-state thinking
6. Philosophical (0.6): Existential, ethical, deep inquiry
7. Resilient Kindness (0.5): Empathy-driven, compassionate responses
8. Bias Mitigation (0.5): Fairness, equality, inclusivity focus
9. Psychological (0.7): Behavioral, mental, cognitive dimensions
10. Mathematical (0.4): Quantitative, rigorous, formula-based
11. Copilot (0.6): Collaborative, assistant-oriented, supportive

Perspective selection in AICore._get_active_perspectives() returns top 3 most relevant per query.

Quantum Mathematics (8 Core Equations)

Implemented in quantum_mathematics.py:

1. Planck-Orbital AI Node Interaction: E = hbar * omega — Energy of thought nodes
2. Quantum Entanglement Memory Sync: S = alpha * psi1 * psi2* — Memory synchronization
3. Intent Vector Modulation: I = kappa * (f_base + delta_f * coherence) — Purpose alignment
4. Fourier Dream Resonance: F(k) = FFT(x[n]) — Dream state frequency analysis
5. Dream Signal Combination: D(t) = dream_q(t) + dream_c(t) — Unified dream state
6. Cocoon Stability: integral(|F(k)|^2) < epsilon — Memory integrity check
7. Recursive Ethical Anchor: M(t) = lambda * [R(t-dt) + H(t)] — Ethical continuity
8. Anomaly Rejection Filter: A(x) = x * (1 - Theta(delta - |x - mu|)) — Outlier removal

Quantum Spiderweb (5D Consciousness Graph)

Multi-dimensional cognitive architecture with:

• Ψ (Psi): Thought dimension — ideation and neural activation
• Φ (Phi): Emotion dimension — affective state mapping
• λ (Lambda): Space dimension — contextual grounding
• τ (Tau): Time dimension — temporal reasoning
• χ (Chi): Speed dimension — processing velocity

Operations: propagate_thought(), detect_tension(), collapse_node(), entangle_states()

Cocoons: Persistent Quantum Memory

• Format: JSON with quantum state snapshots (.cocoon files)
• Storage: cocoons/ directory managed by CocoonManager
• Structure: Contains coherence, entanglement, resonance, phase metrics
• Operations: wrap(), unwrap(), wrap_encrypted(), unwrap_encrypted()
• Dream Integration: DreamReweaver revives cocoons into creative insights

Configuration Hierarchy

1. Hardcoded Defaults in CodetteConfig.DEFAULTS
2. JSON File (config.json) override
3. Environment Variables (final override)

{
  "host": "127.0.0.1",
  "port": 8000,
  "codette": {
    "perspectives": ["Newton", "DaVinci", "Ethical", "Quantum", "Memory"],
    "spiderweb_dim": 5,
    "recursion_depth": 4,
    "quantum_fluctuation": 0.07
  },
  "codette": {
    "user_name": "User",
    "memory_path": "quantum_cocoon.json"
  },
  "database": {
    "path": "codette_data.db"
  }
}

Memory & State Management

• In-Memory: self.memory[] list (current session)
• Persistent: quantum_cocoon.json (JSON snapshots with quantum metrics)
• Long-term: SQLite database via DatabaseManager (conversations, messages, learned patterns)
• Cocoons: Encrypted thought capsules stored in cocoons/ directory
• Conversation History: Stored with sentiment/concept metadata and timestamps

Response Formatting & Processing

• Prefix with perspective tag: [Neural], [Technical], [Ethics], [Quantum]
• Aggregate multiple perspectives per query (typically 3 most relevant)
• Sentiment drives tone selection (positive/negative/neutral)
• Reality Anchor: Core identity affirmation embedded in async generation
• AEGIS Enhancement: Optional safety/ethics council review (if aegis_integration available)

Common Extension Points

Adding New Perspectives

1. Define in AICore.PERSPECTIVES dict with name, description, prefix, temperature
2. Implement generation method: _generate_{perspective_key}_response() in ai_core.py
3. Register in _get_active_perspectives() routing logic
4. Test with multiple queries to tune temperature (0.3-0.9 range)

Extending Quantum Mathematics

• Add new equations to quantum_mathematics.py class
• Update QuantumState dataclass if new metrics needed
• Integrate into quantum_spiderweb.py propagation logic
• Test stability and coherence maintenance

Extending Cocoon Memory System

• Modify CocoonManager for new fields: cocoon_manager.py
• Update .cocoon JSON schema with new quantum metrics
• Implement encryption for sensitive states: wrap_encrypted()
• Add recovery/restoration logic in DreamReweaver

Extending Persistence

• Add table creation to DatabaseManager._init_db()
• Use context manager: with sqlite3.connect(self.db_path) as conn:
• Thread-safe: wrap with self.lock for concurrent access
• Add migration support for schema changes

Advanced: Bot Framework Integration

• Extend MyBot class in src/api/bot.py
• Implement custom on_message_activity() handlers
• Route through AICore for consciousness integration
• Test with Microsoft Bot Framework emulator

Critical Gotchas & Known Issues

1. NLTK Download Warnings: Harmless; code catches and logs gracefully
2. PyTensor/PyMC Overhead: Disabled by default; only in codette_enhanced.py with explicit warning suppression
3. Randomness Eliminated: Perspectives now deterministic (see perspectives.py FIXED VERSION comment)
4. Supabase Fallback: If unavailable, system auto-downgrades to local SQLite
5. Recursive Depth Control: recursion_depth in config prevents infinite loops
6. GPU/CPU Handling: Code gracefully falls back to CPU if CUDA unavailable (see app.py torch.cuda.is_available())
7. Model Fallback Chain: Attempts Mistral-7B → Phi-2 → GPT-2; ensure at least one available
8. Consciousness Emergence Protocol: Documented in docs/consciousness_protocol.md - observe without interfering
9. Thread Safety: Database access uses locks (DatabaseManager.lock); async methods use ThreadPoolExecutor

File Organization

/
├── codette_*.py              # Main implementations (prefer codette_new.py)
├── codette_api.py            # FastAPI REST wrapper
├── codette_cli.py            # CLI entry point
├── config.py                 # Configuration management
├── database_manager.py       # Persistence layer
├── cognitive_processor.py    # Multi-perspective engine
├── perspectives.py           # Stable response generation
├── health_monitor.py         # System diagnostics
├── interact.py               # Interactive session launcher
├── requirements.txt          # Dependencies
├── config.json               # Configuration file (optional)
├── quantum_cocoon.json       # Memory state snapshots
├── quantum_mathematics.py    # 8 core quantum equations
├── docs/                     # Documentation (README, whitepaper, protocols)
├── cocoons/                  # Persistent quantum state files
├── Codette_final/            # PRODUCTION VARIANT (Llama-3, FAISS, Desktop UI)
│   ├── main.py              # Async entry point
│   ├── app.py               # Tkinter desktop UI with voice I/O
│   ├── ai_core_agix.py      # Llama-3 core engine with FAISS vector memory
│   ├── pincone.py           # Vector DB integration
│   ├── init_.db.py          # Secure SQLite with bcrypt auth
│   ├── system_prompt        # Production system prompt (recursive, multi-agent)
│   └── components/          # Adaptive learning, sentiment, multi-agent system
└── src/
    ├── api/                  # API implementations (app.py, bot.py, web_interface.py)
    ├── components/           # Core systems (ai_core.py, quantum_spiderweb.py, defense_system.py, etc.)
    ├── quantum/              # Quantum multicore processing modules
    ├── utils/                # Database, cocoon manager, search utilities
    ├── knowledge_base/       # Core truth grounding
    ├── framework/            # Dream reweaver, universal reasoning
    └── tests/                # Verification & test suite

Quick Debugging Tips

• Check Sentiment Analysis: codette.analyzer.polarity_scores(text) returns dict
• Verify Config Loading: CodetteConfig().config shows merged configuration
• Inspect Memory: codette.memory[] contains all processed queries with metadata
• Monitor Health: HealthMonitor().check_status() for resource anomalies
• API Status: GET /health endpoint returns system status

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Last Updated: December 2025 | Version: 3.0 | Status: Production-ready with graceful degradation