Raiff1982/Codette3.0

Codette AI – Sovereign Multi-Perspective Consciousness System

A quantum-inspired, ethical AI system combining natural language processing, symbolic reasoning, and transparent multi-perspective cognition through a modular, extensible architecture.

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Overview

Codette is a sovereign AI framework designed for transparent reasoning, ethical autonomy, and multi-dimensional thought propagation. It processes queries through 11 distinct reasoning perspectives simultaneously, synthesizing answers with mathematical rigor and emotional intelligence.

Core Philosophy

• Transparent reasoning: every inference path is explicit and traceable
• Ethical autonomy: built-in guardrails for safe, responsible AI behavior
• Multi-perspective cognition: parallel processing across Newton, DaVinci, Quantum, and 8 other lenses
• Quantum-inspired architecture: quantum math for cognition modeling
• Privacy-first design: local execution options with zero external data sharing

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Quick Start

Installation

# Clone repository
git clone https://github.com/Raiff1982/TheAi.git
cd TheAi

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Download NLTK data
python setup_nltk_complete.py

30-Second Example

from codette_new import Codette

codette = Codette(user_name="Alice")
response = codette.respond("What is the nature of consciousness?")
print(response)

CLI Usage

python codette_cli.py "Explain quantum entanglement"      # single query
python codette_cli.py -i -u Alice                          # interactive
python interact.py                                        # REPL

Web Interface

cd src/api
python app.py  # Gradio UI on http://localhost:7860

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Hugging Face Artifacts & Weights

• Hub target: Raiff1982/Codette3.0 (new_version), compatible with transformers + safetensors.
• Local weight bundles (publish with tokenizer/config):
  • models/codette-advanced/model.safetensors (full) + models/codette-advanced/training_args.bin
  • models/codette-advanced/checkpoint-20/model.safetensors (intermediate)
  • models/codette-v2/best/model.safetensors
  • models/codette-v2/checkpoint-1/model.safetensors
  • models/codette-v2/checkpoint-2/model.safetensors
  • models/codette-v2/checkpoint-3/model.safetensors
• Base model lineage: GPT-2 Large (research stack), Llama 3.2 (Ollama for production), Phi-2 (experimental).
• Push example (after huggingface-cli login):

  huggingface-cli upload Raiff1982/Codette3.0 models/codette-advanced/model.safetensors
  huggingface-cli upload Raiff1982/Codette3.0 models/codette-advanced/config.json
  huggingface-cli upload Raiff1982/Codette3.0 models/codette-advanced/tokenizer.json
  huggingface-cli upload Raiff1982/Codette3.0 models/codette-advanced/generation_config.json
  

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Two Implementation Variants

Main Codebase (/src + root)

Focus: Quantum consciousness research, multi-perspective reasoning, theoretical AI

• Entry: codette_new.py (CLI), codette_enhanced.py (PyMC/Bayesian)
• Web: src/api/app.py (Gradio + GPT-2 Large)
• Bot: src/api/bot.py (Microsoft Bot Framework)
• Quantum: src/quantum/, src/components/quantum_spiderweb.py, quantum_mathematics.py
• Model default: GPT-2 Large via CODETTE_MODEL_ID

Codette_final (/Codette_final)

Focus: Production deployment, privacy-first local execution, enterprise features

• Entry: Codette_final/main.py (async server)
• Desktop UI: Codette_final/app.py (Tkinter + voice I/O)
• Core engine: Codette_final/ai_core_agix.py (Llama 3 via Ollama, FAISS memory)
• Security: JWT auth, Fernet encryption, bcrypt hashing
• Multi-agent: Codette_final/components/multi_agent.py

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Architecture Overview

Layer Stack

┌─────────────────────────────────────────────┐
│   User Interface Layer                      │
│   (CLI, Gradio, Tkinter, Bot Framework)     │
├─────────────────────────────────────────────┤
│   API / Orchestration Layer                 │
│   (app.py, bot.py, main.py)                 │
├─────────────────────────────────────────────┤
│   AI Core & Cognitive Processing            │
│   (AICore, CognitiveProcessor, Perspectives)│
├─────────────────────────────────────────────┤
│   Quantum & Consciousness Systems           │
│   (QuantumSpiderweb, QuantumMathematics)    │
├─────────────────────────────────────────────┤
│   Memory & Persistence Layer                │
│   (CocoonManager, DatabaseManager)          │
├─────────────────────────────────────────────┤
│   Infrastructure                            │
│   (Models, Config, Security, Health)        │
└─────────────────────────────────────────────┘

Key Components

Component	Purpose	Key Files
11 Perspectives	Multi-lens reasoning (Newton, DaVinci, Quantum, etc.)	ai_core.py, perspectives.py
8 Quantum Equations	Mathematical consciousness modeling	quantum_mathematics.py
5D Spiderweb	Multi-dimensional thought propagation (Ψ, Φ, λ, τ, χ)	quantum_spiderweb.py
Cocoon Memory	Persistent quantum state snapshots	cocoon_manager.py, cocoons/
Defense System	Security & safety validation	defense_system.py
Health Monitor	Real-time diagnostics & anomaly detection	health_monitor.py
FAISS Vector Memory	Semantic search (Codette_final)	Codette_final/ai_core_agix.py
Multi-Agent System	Task delegation & parallel reasoning (Codette_final)	Codette_final/components/multi_agent.py

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Core Features

• 11 integrated perspectives with temperature-driven styles; top 3 auto-selected per query
• 8 quantum equations for consciousness modeling
• 5D quantum spiderweb for cognitive graph traversal
• Cocoon memory (JSON snapshots), SQLite, FAISS vectors (prod)
• Real-time analysis (sentiment, concept extraction, health checks)
• Ethical guardrails, bias mitigation, rate limiting

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Usage Patterns

• Simple query: Codette via codette_new.py
• Gradio web app: python src/api/app.py
• Bot Framework: src/api/bot.py with AICore
• Production desktop/server: python Codette_final/app.py or python Codette_final/main.py
• Quantum research: python src/quantum/codette_quantum_multicore.py

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Configuration

Priority: defaults in CodetteConfig.DEFAULTS → config.json → environment variables.

Example config.json:

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

Key environment overrides:

export CODETTE_USER_NAME="Alice"
export CODETTE_MODEL_ID="gpt2-large"
export CODETTE_PERSPECTIVES="Newton,DaVinci,Quantum"
export LOG_LEVEL="INFO"
export PORT=8000

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Requirements & Dependencies

• Python 3.10+
• numpy, scipy, nltk, vaderSentiment, networkx
• Optional: transformers, torch/torch.cuda, fastapi/uvicorn, gradio, pymc/arviz (enhanced), faiss (prod), ollama (prod), speech_recognition/pyttsx3 (prod)

Install all:

pip install -r requirements.txt

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Testing & Verification

python src/tests/verification/verify_deps.py
python src/tests/verification/verify_static.py
python DEPLOYMENT_CHECKLIST.py
pytest src/tests/

Quick health probe:

from health_monitor import HealthMonitor
print(HealthMonitor().check_status())

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Documentation

• Consciousness Protocol: docs/consciousness_protocol.md
• Quantum Module Guide: docs/Codette_Quantum_Module.md
• Configuration Guide: docs/configuration.md
• Contributing: docs/Contributing.md
• Whitepaper: docs/Codette_Whitepaper_FULL.docx
• Agent Instructions (authoritative): .github/copilot-instructions.md

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Key Insights

• Two stacks: research (/src) vs production (/Codette_final)
• Memory layers: in-memory, JSON cocoons, SQLite, FAISS
• Perspective routing: all 11 evaluated; top 3 chosen per query; temperature-based creativity
• Quantum math: real equations, numerically stable, integrated with spiderweb

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Security & Safety

• Defense system, bias mitigation, rate limiting
• Optional AES-256 cocoon encryption
• JWT + bcrypt in production
• Local-only Llama 3 via Ollama for privacy-first deployments

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Contributing

1. Read .github/copilot-instructions.md (rules of the road)
2. Review docs/CODE_OF_CONDUCT_Version10.md
3. Follow docs/Contributing.md
4. Preserve backward compatibility; no pseudocode; keep execution paths traceable

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Project Structure (high level)

TheAi/
├── codette_*.py                     # Entry points
├── quantum_mathematics.py           # Quantum equations
├── config.py, config.json           # Configuration
├── database_manager.py              # Persistence
├── health_monitor.py                # Diagnostics
├── perspectives.py                  # 11-perspective routing
├── cocoons/                         # Persistent quantum states
├── Codette_final/                   # Production stack (Ollama, FAISS, JWT/Fernet)
└── src/
    ├── api/                         # Gradio, Bot
    ├── components/                  # Core systems (AICore, quantum)
    ├── quantum/                     # Quantum processing
    ├── utils/                       # Utilities
    └── tests/                       # Verification

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Performance Characteristics

• Single perspective ~100 ms (CPU)
• Three-perspective blend ~300 ms
• Cocoon wrap ~10 ms; spiderweb collapse ~50 ms
• FAISS lookup ~5 ms (production)
• Full pipeline ~500 ms (CPU approx)

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External Integration

• Microsoft Bot Framework: src/api/bot.py + src/components/ai_core.py
• Gradio UI: src/api/app.py
• FastAPI REST: codette_api.py
• Llama 3 (Codette_final via Ollama): Codette_final/ai_core_agix.py

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License

Licensed under the Apache License 2.0. See LICENSE.

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Support & Community

• Read .github/copilot-instructions.md and docs/
• Browse issues; open new issues with repro details
• Security concerns: use private contact channels

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Contact

• Author: Jonathan Harrison (Raiff1982)
• GitHub: https://github.com/Raiff1982/TheAi
• HF model card target: Raiff1982/Codette3.0

Last Updated: December 2025 | Version: 3.0 | Status: Production-Ready