Neural Mesh Pipeline

Production-ready self-healing neural mesh pipeline with AI-powered code repair, retry logic, and state persistence for Termux

Features

✅ Exponential Backoff Retry Logic - Handles transient failures gracefully
✅ Persistent State Management - Survives interruptions and device resets
✅ AI-Powered Code Repair - LangChain agents automatically fix failing tests
✅ Structured Logging - File and console output with timestamps
✅ Advanced Test Execution - Timeout protection and metrics collection
✅ Zero-Trust Networking - OpenZiti deployment integration
✅ Termux Optimized - Designed for Android mobile development

Quick Start (5 Minutes)

Automated Deployment (Recommended)

# Clone repository
git clone https://github.com/Garrettc123/neural-mesh-pipeline.git
cd neural-mesh-pipeline

# Run deployment script
./deploy.sh

# Or use Docker
./deploy-docker.sh

Manual Setup (Termux)

# 1. Install prerequisites
pkg update && pkg upgrade -y
pkg install python python-pip -y
termux-setup-storage

# 2. Create directory structure
mkdir -p ~/neural-mesh/{src/tests,logs,storage}
cd ~/neural-mesh

# 3. Clone or download files
# Copy pipeline_enhanced.py and requirements-termux.txt to ~/neural-mesh

# 4. Install dependencies
pip install -r requirements-termux.txt

# 5. Configure
export OPENAI_API_KEY="sk-your-key"

# 6. Run!
python pipeline_enhanced.py

For detailed deployment options (Docker, Cloud, CI/CD), see DEPLOYMENT.md

Documentation

• Deployment Guide - Complete deployment instructions
• Quick Reference - Commands and common tasks
• Implementation Guide - Full technical documentation
• Troubleshooting - Common issues and solutions

Architecture

NeuralMeshPipeline
├── State Persistence (JSON)
├── Retry Logic (Exponential Backoff + Jitter)
├── Test Execution (Subprocess + Timeout)
├── AI Code Repair (LangChain ReAct Agent)
│   ├── ReadSourceCode Tool
│   ├── AnalyzeError Tool
│   └── WriteFixedCode Tool
└── Continuous Orchestration

Usage Examples

# Single cycle
python pipeline_enhanced.py --mode single

# Continuous with 30-min interval
python pipeline_enhanced.py --interval 1800

# View current state
python pipeline_enhanced.py --show-state

# Watch logs
tail -f logs/pipeline_*.log

Configuration

Create .env file:

OPENAI_API_KEY=sk-your-key-here
AI_MODEL=gpt-4
MAX_RETRIES=3
TEST_TIMEOUT=300

Key Features Explained

Retry Logic

Uses exponential backoff with jitter to prevent thundering herd:

• Attempt 1: immediate
• Attempt 2: ~1s delay
• Attempt 3: ~2s delay
• Attempt 4: ~4s delay

State Persistence

Automatically saves:

• Cycle count and timestamps
• Test metrics (passes/failures)
• Repair success rates
• Code checksums
• Backup locations

AI Repair

LangChain agent with specialized tools:

1. Reads failing source code
2. Analyzes test error output
3. Generates corrected code
4. Verifies fix with re-test

Requirements

• Python 3.8+
• Termux (Android) or Linux
• OpenAI API key
• ~50MB storage

Project Structure

~/neural-mesh/
├── pipeline_enhanced.py      # Main orchestrator (500+ lines)
├── requirements-termux.txt   # Dependencies
├── .env                      # API keys (create this)
├── src/
│   ├── tests/               # Test files (test_*.py)
│   └── *.py                 # Your source code
├── logs/                    # Rotating logs
└── storage/                 # State persistence
    └── pipeline_state.json

License

MIT License - See LICENSE file for details

Contributing

Pull requests welcome! See IMPLEMENTATION_GUIDE.md for architecture details.

Support

For issues, see TROUBLESHOOTING.md or open a GitHub issue.

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Built for production use on Termux with love ❤️