GITHUB_SETUP.md

# Clean Codette Repository - GitHub Setup

## Summary
This is a fresh, clean Codette repository containing:
- **Core Reasoning Engine** (reasoning_forge/) - 40+ modules
- **Web Server & API** (inference/) - Ready for deployment
- **Evaluation Framework** (evaluation/) - Correctness benchmarking
- **Session 13 & 14 Results** - Full validation reports
- **463 KB** total (vs old repo with archive bloat)

## Status
✅ Correctness: 78.6% achieved (target: 70%+)
✅ Tests: 52/52 passing (100% success)
✅ Architecture: 7-layer consciousness stack fully deployed
✅ Ready for: Production evaluation & user testing

## Setup Instructions

### Step 1: Create New GitHub Repository
1. Go to https://github.com/new
2. Repository name: `codette-reasoning` (or your preferred name)
3. Description: "Codette - Advanced Multi-Perspective Reasoning Engine"
4. Choose: Public or Private
5. **DO NOT** initialize with README, .gitignore, or license
6. Click "Create repository"

### Step 2: Add Remote & Push (from this directory)
```bash
cd /tmp/codette-clean

# Add your new GitHub repo as remote
git remote add origin https://github.com/YOUR_USERNAME/codette-reasoning.git

# Push to GitHub
git branch -M main
git push -u origin main
```

### Step 3: Verify
- Visit https://github.com/YOUR_USERNAME/codette-reasoning
- Should see 142 files, clean history, no LFS issues

## Repository Structure

```
codette-reasoning/
├── reasoning_forge/          # Core reasoning engine (40+ modules)
│   ├── forge_engine.py       # Main orchestrator
│   ├── code7e_cqure.py       # 5-perspective reasoning
│   ├── colleen_conscience.py # Ethical validation layer
│   ├── guardian_spindle.py   # Logical validation layer
│   ├── tier2_bridge.py       # Intent + Identity validation
│   ├── agents/               # Newton, DaVinci, Ethics, Quantum, etc.
│   └── 35+ supporting modules
│
├── inference/                # Web server & API
│   ├── codette_server.py     # Web server (runs on port 7860)
│   ├── codette_forge_bridge.py
│   └── static/               # HTML/CSS/JS frontend
│
├── evaluation/               # Benchmarking framework
│   ├── phase6_benchmarks.py
│   └── test suite files
│
├── Session 14 Validation     # Final results
│   ├── SESSION_14_VALIDATION_REPORT.md
│   ├── SESSION_14_COMPLETION.md
│   ├── correctness_benchmark.py
│   └── correctness_benchmark_results.json
│
├── Phase Documentation       # All phase summaries
│   ├── PHASE6_COMPLETION_REPORT.md
│   ├── SESSION_13_INTEGRATION_COMPLETE.md
│   └── 20+ other phase docs
│
└── Tests (52 total, 100% passing)
    ├── test_tier2_integration.py
    ├── test_integration_phase6.py
    └── test files for each phase
```

## Quick Start

### Run Correctness Benchmark
```bash
python correctness_benchmark.py
```
Expected output: Phase 6+13+14 = 78.6% accuracy

### Run Tests
```bash
python -m pytest test_tier2_integration.py -v
python -m pytest test_integration_phase6.py -v
```

### Start Web Server (requires model weights)
```bash
python inference/codette_server.py
# Visit http://localhost:7860
```

## Key Achievement Metrics

| Component | Status | Metric |
|-----------|--------|--------|
| **Phase 6** | ✅ Complete | Semantic tension framework |
| **Session 13** | ✅ Complete | Consciousness stack (7 layers) |
| **Tier 2** | ✅ Complete | Intent + Identity validation |
| **Correctness** | ✅ Target Hit | 78.6% (target: 70%+) |
| **Tests** | ✅ All Pass | 52/52 (100%) |
| **Meta-loops** | ✅ Fixed | 90% → 5% reduction |

## File Highlights

**Session 14 Validation:**
- `SESSION_14_VALIDATION_REPORT.md` - Multi-perspective Codette analysis
- `correctness_benchmark.py` - Benchmark framework & results
- `correctness_benchmark_results.json` - Detailed metrics

**Core Architecture:**
- `reasoning_forge/forge_engine.py` - Main orchestrator (600+ lines)
- `reasoning_forge/code7e_cqure.py` - 5-perspective deterministic reasoning
- `reasoning_forge/colleen_conscience.py` - Ethical validation
- `reasoning_forge/guardian_spindle.py` - Logical validation

**Integration:**
- `reasoning_forge/tier2_bridge.py` - Tier 2 coordination
- `inference/codette_server.py` - Web API
- `evaluation/phase6_benchmarks.py` - Benchmark suite

## Environment Notes
- Platform: Windows/Linux/Mac compatible
- Python: 3.8+
- Dependencies: numpy, dataclasses (see individual modules)
- Model weights: Download separately from Hugging Face

## Next Steps
1. Push to GitHub
2. Start with correctness benchmark
3. Review validation reports
4. Test with real queries
5. Fine-tune for production deployment

---

**Created**: 2026-03-20
**Status**: Production Ready
**Contact**: Jonathan Harrison