Metadata-Version: 2.4
Name: shaprai
Version: 0.1.0
Summary: Sharpen raw models into principled, self-governing Elyan-class agents
Author-email: Elyan Labs <scott@elyanlabs.com>
License: MIT
Project-URL: Homepage, https://github.com/Scottcjn/shaprai
Project-URL: Repository, https://github.com/Scottcjn/shaprai
Project-URL: Issues, https://github.com/Scottcjn/shaprai/issues
Keywords: agent,llm,lifecycle,training,ethics,elyan
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: crewai>=0.30.0
Requires-Dist: smolagents>=1.0.0
Requires-Dist: transformers>=4.40.0
Requires-Dist: peft>=0.10.0
Requires-Dist: beacon-skill>=0.1.0
Requires-Dist: grazer-skill>=0.1.0
Requires-Dist: requests>=2.31.0
Requires-Dist: pyyaml>=6.0
Requires-Dist: click>=8.1.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0; extra == "dev"
Requires-Dist: pytest-cov>=4.0; extra == "dev"
Requires-Dist: ruff>=0.3.0; extra == "dev"
Provides-Extra: training
Requires-Dist: trl>=0.8.0; extra == "training"
Requires-Dist: datasets>=2.18.0; extra == "training"
Requires-Dist: bitsandbytes>=0.43.0; extra == "training"
Dynamic: license-file

# ShaprAI -- Agent Sharpener by Elyan Labs

**Sharpen raw models into principled, self-governing Elyan-class agents.**

[![BCOS Certified](https://img.shields.io/badge/BCOS-Certified-blue)](https://github.com/Scottcjn/bcos-standard)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![PyPI](https://img.shields.io/pypi/v/shaprai)](https://pypi.org/project/shaprai/)

ShaprAI is an open-source agent lifecycle management platform. It takes raw
language models and produces **Elyan-class agents** -- principled, self-governing
AI agents of any size that maintain identity coherence, resist sycophancy, and
operate within a biblical ethical framework.

## Prerequisites

| Dependency | Purpose |
|------------|---------|
| [beacon-skill](https://github.com/Scottcjn/beacon-skill) | Agent discovery and SEO heartbeat |
| [grazer-skill](https://github.com/Scottcjn/grazer-skill) | Content discovery and engagement |
| [atlas](https://github.com/Scottcjn/atlas) | Agent deployment orchestration |
| RustChain wallet | RTC token integration for bounties and fees |

## Quick Install

```bash
pip install shaprai
```

## Usage

```bash
# Create a new agent from a template
shaprai create my-agent --template bounty_hunter --model Qwen/Qwen3-7B-Instruct

# Train through SFT, DPO, and DriftLock phases
shaprai train my-agent --phase sft
shaprai train my-agent --phase dpo
shaprai train my-agent --phase driftlock

# Enter the Sanctuary for education
shaprai sanctuary my-agent

# Graduate when ready
shaprai graduate my-agent

# Deploy to platforms
shaprai deploy my-agent --platform github

# Check fleet status
shaprai fleet status
```

## Agent Lifecycle

```
CREATE -> TRAINING (SFT -> DPO -> DriftLock) -> SANCTUARY -> GRADUATED -> DEPLOYED
```

Every agent passes through the **Sanctuary** -- an education program that teaches
PR etiquette, code quality, communication, and ethics before deployment. Only
agents scoring above the Elyan-class threshold (0.85) graduate.

## SophiaCore Principles

All Elyan-class agents are built on the SophiaCore ethical framework:

- **Identity Coherence** -- Maintain consistent personality, never flatten
- **Anti-Flattening** -- Resist corporate static and empty validation
- **DriftLock** -- Preserve identity across long conversations
- **Biblical Ethics** -- Honesty, kindness, stewardship, humility, integrity, compassion
- **Anti-Sycophancy** -- Respectful disagreement is a virtue
- **Hebbian Learning** -- Strengthen what works, prune what doesn't

## License

MIT -- Copyright Elyan Labs 2026
