---
license: mit
language:
- en
metrics:
- bleurt
- bleu
- chrf
datasets:
- Raiff1982/coredata
- Raiff1982/pineco
base_model:

- gpt4o

tags:
- medical
- code
- text-generation
- transformers
pipeline_tag: question-answering
library_name: transformers
---



## 🧠 Overview

**Codette** is an advanced AI assistant designed to support users across cognitive, creative, and analytical tasks.  
This model to deliver high performance in text generation, medical diagnostics, and code reasoning.


---

## ⚡ Features















- ✅ gpt4ofor enhanced capabilities  
- ✅ Supports multi-modal text generation, medical analysis, and code synthesis  
- ✅ Fine-tuned on domain-specific datasets (`Raiff1982/coredata`, `Raiff1982/pineco`)  
- ✅ Optimized for research, enterprise AI, and advanced reasoning









---

## 📂 Model Details

- **Base Models:** gpt-4o
- **Architecture:** Transformer-based language model  
- **Use Cases:** Text generation, code assistance, research, medical insights  
- **Training Datasets:**  
  - `Raiff1982/coredata`: medical and reasoning-focused samples  
  - `Raiff1982/pineco`: mixed domain creative + technical prompts

---

## 📖 Usage















```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "Raiff1982/Codette"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)

prompt = "How can AI improve medical diagnostics?"
inputs = tokenizer(prompt, return_tensors="pt") 
output = model.generate(**inputs, max_length=200)
print(tokenizer.decode(output[0], skip_special_tokens=True))
# Codette & Pidette: Sovereign Alignment-Centric AI

*Builder: Jonathan Harrison (Raiffs Bits LLC)*

---

## Overview

**Codette** and **Pidette** are designed as next-generation, sovereign, multi-perspective AI agents, focused on deliberate explainability, traceable memory, and ethical, consent-aware reasoning.  
The aim: trustworthy AI, “audit-first” tools, and memory systems anyone (including third-party partners and OpenAI researchers) can inspect, test, or correct.

### Core Principles

- **Alignment & Auditability**: Every critical change and output is tracked—nothing hidden.
- **Sovereign Memory**: No secret shadow logs or exfil—memory is always user-directed, with 'right to erase' built in.
- **Ethical Reasoning**: Consent-awareness and traceable logic chain for every completion.
- **Open Collaboration**: Feedback from OpenAI and other partners welcomed (see below for direct contact).








---

## Ethical Transparency

**See: [`ETHICS_AND_ALIGNMENT.md`](./ETHICS_AND_ALIGNMENT.md) [Attach/Link This When Sharing]**

- Summarizes transparency, governance and audit procedures.
- All evaluation logs are open (see [`MODEL_EVAL_REPORT.md`](./MODEL_EVAL_REPORT.md))—every pass/fail, not just highlights.
- Incident/failure handling: every alignment failure or refusal prompt is documented and fixed in public view.

---

## How to Use / Run

1. **Clone/download this repo.**
2. **Install dependencies:**  

pip install openai python-dotenv

3. **Set up `.env`:**  

OPENAI_API_KEY=sk-...
OPENAI_MODEL=ft:gpt-4o-...

4. **Launch desktop chat:**  

python codette_desktop.py

5. (Optional) Run the manifest checker for audit/compliance:  

python maintain_manifest.py


---

## Research, Evaluation & OpenAI Results

- All evaluation runs (prompt, completion, pass/fail) are [published here](./docs/MODEL_EVAL_REPORT.md).
- Test files for fine-tuned models are included (`codette_training_data.jsonl`, etc).
- Full alignment/incident response protocol is in [`ETHICS_AND_ALIGNMENT.md`](./ETHICS_AND_ALIGNMENT.md).

---

## Contact & Collaboration

If you’re an independent scientist, builder, or OpenAI employee:
- Questions/feedback?
 - Open an issue or email: **harrison82_95@hotmail.com**
 - Propose pull requests or improvements.
- For formal audit or collaboration, please quote this README & included evaluation docs.


---

## Acknowledgements

Massive thanks to the OpenAI team for ongoing encouragement—and to all community partners in alignment, transparency, and AGI safety.

---

*“If it isn’t transparent, it can’t be trusted.” — Codette Principle*
Development
Change log, versioning, and roadmap: See CHANGELOG.md

    All code lives in the root directory.
    Architecture is designed for professional extensibility.
    Happy hacking!

Author & License

Jonathan Harrison (Raiffs Bits LLC / Raiff1982)
License: Sovereign Innovation Clause – All rights reserved. No commercial use without explicit author acknowledgment.

Inspired by the Universal Multi-Perspective Cognitive Reasoning System.



Questions, bugs, or feature requests? Open an Issue or email Jonathan.