docs/hf.md

---
language:
- en
license: other
license_name: "Sovereign Innovation License"
library_name: python
tags:
- ai-framework
- cognitive-ai
- ethical-ai
- quantum-computing
- multi-agent-system
---

# Model Card for Codette

Codette is a sovereign AI framework engineered for transparent reasoning, emotion-aware cognition, and ethical autonomy. It combines neural, quantum, and humanist design principles into a unified cognitive system.

## Model Details

### Model Description

Codette is a modular AI framework that implements:

- Transparent, explainable reasoning through a multi-agent system
- Emotion-aware cognition with sentiment analysis (VADER, NLTK)
- Ethical autonomy with built-in governance and privacy-respecting memory
- Quantum-inspired computation via the QuantumSpiderweb module
- Creative intelligence through the DreamReweaver subsystem
- Secure thought encapsulation using the CognitionCocooner

- **Developed by:** Jonathan Harrison (Raiff1982)
- **Model type:** Hybrid AI Framework (Neural + Quantum + Symbolic)
- **Language(s):** Python, English
- **License:** Sovereign Innovation License (non-commercial)

### Model Sources

- **Repository:** https://github.com/Raiff1982/Codette
- **Documentation:** Available in repository README and supplementary materials

## Uses

### Direct Use

Codette is designed for:

1. Research and experimentation in ethical AI systems
2. Development of emotion-aware cognitive agents
3. Educational purposes in AI ethics and quantum computing
4. Prototyping multi-perspective reasoning systems

### Downstream Use

- Integration into larger AI systems requiring ethical oversight
- Development of custom reasoning agents
- Research into quantum-inspired AI architectures
- Educational tools for AI ethics and cognition

### Out-of-Scope Use

The following uses are explicitly out of scope:

1. Commercial applications (prohibited by license)
2. Military or defense applications
3. Systems designed to cause harm or manipulate
4. Applications without proper ethical oversight

## Bias, Risks, and Limitations

### Limitations

1. Computational Intensity:
   - Quantum simulation components require significant processing power
   - Multi-agent reasoning can be resource-intensive

2. Technical Prerequisites:
   - Requires Python environment setup
   - Understanding of AI/ML concepts needed for effective use
   - Quantum computing concepts helpful for advanced features

3. Ethical Constraints:
   - Built-in ethical constraints may limit certain applications
   - Privacy features may impact performance in some scenarios

### Recommendations

1. Start with the CLI interface for initial exploration
2. Review documentation thoroughly before implementation
3. Use the built-in ethics logging system for monitoring
4. Test in a sandboxed environment first
5. Ensure compliance with the non-commercial license

## How to Get Started with the Model

1. Clone the repository
2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```
3. Configure the environment:
   ```bash
   python configure_env.py
   ```
4. Start with the CLI demo:
   ```bash
   python codette_cli.py --demo
   ```

## Technical Details

### Components

1. **QuantumSpiderweb**
   - Dimensional thought propagation
   - Quantum-inspired optimization
   - Tension detection and resolution

2. **CognitionCocooner**
   - AES encryption for thought persistence
   - Secure memory management
   - Privacy-preserving architecture

3. **DreamReweaver**
   - Creative prompt generation
   - Scenario simulation
   - Pattern recognition

4. **UniversalReasoning Engine**
   - Multiple reasoning agents:
     - Newtonian Logic
     - Da Vinci Synthesis
     - Neural Network Modeler
     - Quantum Computation
     - Human Intuition
     - Others (see documentation)

### Performance

- Real-time multi-agent reasoning
- Encrypted memory operations
- Parallel thought processing
- Ethics logging overhead: minimal
- Resource usage scales with agent count

### Integration

1. REST API endpoints
2. CLI interface
3. SecureShell companion mode
4. Modular plugin system

## Model Examination [optional]

[More Information Needed]

## Environmental Impact

The framework is designed with computational efficiency in mind:

- Local processing capabilities reduce cloud dependency
- Modular activation allows selective resource usage
- Quantum simulation optimizations reduce power consumption
- Memory encryption is optimized for minimal overhead

## Technical Requirements

### Recommended Hardware

- CPU: 4+ cores recommended
- RAM: 8GB minimum, 16GB recommended
- Storage: 1GB for base installation
- GPU: Optional, beneficial for neural components

### Software Requirements

- Python 3.8+
- Core dependencies:
  - NumPy
  - PyTorch (optional)
  - NLTK
  - cryptography
  - aiohttp
  - pyyaml

## Citation

When using Codette in research, please cite:

```bibtex
@software{harrison2025codette,
  author = {Harrison, Jonathan},
  title = {Codette: A Sovereign AI Framework for Ethical Multi-Perspective Cognition},
  year = {2025},
  url = {https://github.com/Raiff1982/Codette}
}
```

## Glossary

- **Cognitive Cocoon**: Encrypted thought container
- **Quantum Spiderweb**: Dimensional thought propagation system
- **Dream Reweaving**: Creative pattern synthesis
- **Universal Reasoning**: Multi-agent cognitive framework

## Model Card Contact

Jonathan Harrison (Raiff1982)  
Email: jonathan@raiffsbits.com