---
layout: page
title: "Zig CLI Guide"
permalink: /zig-cli/
nav_order: 3
---

# Zig CLI Guide

High-performance command-line interface for ML experiment management, written in Zig for maximum speed and efficiency.

## Overview

The Zig CLI (`ml`) is the primary interface for managing ML experiments in your homelab. Built with Zig, it provides exceptional performance for file operations, network communication, and experiment management.

## Installation

### Pre-built Binaries (Recommended)

Download from [GitHub Releases](https://github.com/jfraeys/fetch_ml/releases):

```bash
# Download for your platform
curl -LO https://github.com/jfraeys/fetch_ml/releases/latest/download/ml-<platform>.tar.gz

# Extract
tar -xzf ml-<platform>.tar.gz

# Install
chmod +x ml-<platform>
sudo mv ml-<platform> /usr/local/bin/ml

# Verify
ml --help
```

**Platforms:**
- `ml-linux-x86_64.tar.gz` - Linux (fully static, zero dependencies)
- `ml-macos-x86_64.tar.gz` - macOS Intel  
- `ml-macos-arm64.tar.gz` - macOS Apple Silicon

All release binaries include **embedded static rsync** for complete independence.

### Build from Source

**Development Build** (uses system rsync):
```bash
cd cli
zig build dev
./zig-out/dev/ml-dev --help
```

**Production Build** (embedded rsync):
```bash
cd cli
# For testing: uses rsync wrapper
zig build prod

# For release with static rsync:
# 1. Place static rsync binary at src/assets/rsync_release.bin
# 2. Build
zig build prod
strip zig-out/prod/ml  # Optional: reduce size

# Verify
./zig-out/prod/ml --help
ls -lh zig-out/prod/ml
```

See [cli/src/assets/README.md](https://github.com/jfraeys/fetch_ml/blob/main/cli/src/assets/README.md) for details on obtaining static rsync binaries.

### Verify Installation
```bash
ml --help
ml --version  # Shows build config
```

## Quick Start

1. **Initialize Configuration**
   ```bash
   ./cli/zig-out/bin/ml init
   ```

2. **Sync Your First Project**
   ```bash
   ./cli/zig-out/bin/ml sync ./my-project --queue
   ```

3. **Monitor Progress**
   ```bash
   ./cli/zig-out/bin/ml status
   ```

## Command Reference

### `init` - Configuration Setup

Initialize the CLI configuration file.

```bash
ml init
```

**Creates:** `~/.ml/config.toml`

**Configuration Template:**
```toml
worker_host = "worker.local"
worker_user = "mluser"
worker_base = "/data/ml-experiments"
worker_port = 22
api_key = "your-api-key"
```

### `sync` - Project Synchronization

Sync project files to the worker with intelligent deduplication.

```bash
# Basic sync
ml sync ./project

# Sync with custom name and auto-queue
ml sync ./project --name "experiment-1" --queue

# Sync with priority
ml sync ./project --priority 8
```

**Options:**
- `--name <name>`: Custom experiment name
- `--queue`: Automatically queue after sync
- `--priority N`: Set priority (1-10, default 5)

**Features:**
- **Content-Addressed Storage**: Automatic deduplication
- **SHA256 Commit IDs**: Reliable change detection
- **Incremental Transfer**: Only sync changed files
- **Rsync Backend**: Efficient file transfer

### `queue` - Job Management

Queue experiments for execution on the worker.

```bash
# Queue with commit ID
ml queue my-job --commit abc123def456

# Queue with priority
ml queue my-job --commit abc123 --priority 8
```

**Options:**
- `--commit <id>`: Commit ID from sync output
- `--priority N`: Execution priority (1-10)

**Features:**
- **WebSocket Communication**: Real-time job submission
- **Priority Queuing**: Higher priority jobs run first
- **API Authentication**: Secure job submission

### `watch` - Auto-Sync Monitoring

Monitor directories for changes and auto-sync.

```bash
# Watch for changes
ml watch ./project

# Watch and auto-queue on changes
ml watch ./project --name "dev-exp" --queue
```

**Options:**
- `--name <name>`: Custom experiment name
- `--queue`: Auto-queue on changes
- `--priority N`: Set priority for queued jobs

**Features:**
- **Real-time Monitoring**: 2-second polling interval
- **Change Detection**: File modification time tracking
- **Commit Comparison**: Only sync when content changes
- **Automatic Queuing**: Seamless development workflow

### `status` - System Status

Check system and worker status.

```bash
ml status
```

**Displays:**
- Worker connectivity
- Queue status
- Running jobs
- System health

### `monitor` - Remote Monitoring

Launch TUI interface via SSH for real-time monitoring.

```bash
ml monitor
```

**Features:**
- **Real-time Updates**: Live experiment status
- **Interactive Interface**: Browse and manage experiments
- **SSH Integration**: Secure remote access

### `cancel` - Job Cancellation

Cancel running or queued jobs.

```bash
ml cancel job-id
```

**Options:**
- `job-id`: Job identifier from status output

### `prune` - Cleanup Management

Clean up old experiments to save space.

```bash
# Keep last N experiments
ml prune --keep 20

# Remove experiments older than N days
ml prune --older-than 30
```

**Options:**
- `--keep N`: Keep N most recent experiments
- `--older-than N`: Remove experiments older than N days

## Architecture

### Core Components

```
cli/src/
├── commands/        # Command implementations
│   ├── init.zig     # Configuration setup
│   ├── sync.zig     # Project synchronization
│   ├── queue.zig    # Job management
│   ├── watch.zig    # Auto-sync monitoring
│   ├── status.zig   # System status
│   ├── monitor.zig  # Remote monitoring
│   ├── cancel.zig   # Job cancellation
│   └── prune.zig    # Cleanup operations
├── config.zig       # Configuration management
├── errors.zig       # Error handling
├── net/            # Network utilities
│   └── ws.zig       # WebSocket client
└── utils/          # Utility functions
    ├── crypto.zig   # Hashing and encryption
    ├── storage.zig  # Content-addressed storage
    └── rsync.zig    # File synchronization
```

### Performance Features

#### Content-Addressed Storage
- **Deduplication**: Identical files shared across experiments
- **Hash-based Storage**: Files stored by SHA256 hash
- **Space Efficiency**: Reduces storage by up to 90%

#### SHA256 Commit IDs
- **Reliable Detection**: Cryptographic change detection
- **Collision Resistance**: Guaranteed unique identifiers
- **Fast Computation**: Optimized for large directories

#### WebSocket Protocol
- **Low Latency**: Real-time communication
- **Binary Protocol**: Efficient message format
- **Connection Pooling**: Reused connections

#### Memory Management
- **Arena Allocators**: Efficient memory allocation
- **Zero-copy Operations**: Minimized memory usage
- **Resource Cleanup**: Automatic resource management

### Security Features

#### Authentication
- **API Key Hashing**: Secure token storage
- **SHA256 Hashes**: Irreversible token protection
- **Config Validation**: Input sanitization

#### Secure Communication
- **SSH Integration**: Encrypted file transfers
- **WebSocket Security**: TLS-protected communication
- **Input Validation**: Comprehensive argument checking

#### Error Handling
- **Secure Reporting**: No sensitive information leakage
- **Graceful Degradation**: Safe error recovery
- **Audit Logging**: Operation tracking

## Advanced Usage

### Workflow Integration

#### Development Workflow
```bash
# 1. Initialize project
ml sync ./project --name "dev" --queue

# 2. Auto-sync during development
ml watch ./project --name "dev" --queue

# 3. Monitor progress
ml status
```

#### Batch Processing
```bash
# Process multiple experiments
for dir in experiments/*/; do
    ml sync "$dir" --queue
done
```

#### Priority Management
```bash
# High priority experiment
ml sync ./urgent --priority 10 --queue

# Background processing
ml sync ./background --priority 1 --queue
```

### Configuration Management

#### Multiple Workers
```toml
# ~/.ml/config.toml
worker_host = "worker.local"
worker_user = "mluser"
worker_base = "/data/ml-experiments"
worker_port = 22
api_key = "your-api-key"
```

#### Security Settings
```bash
# Set restrictive permissions
chmod 600 ~/.ml/config.toml

# Verify configuration
ml status
```

## Troubleshooting

### Common Issues

#### Build Problems
```bash
# Check Zig installation
zig version

# Clean build
cd cli && make clean && make build
```

#### Connection Issues
```bash
# Test SSH connectivity
ssh -p $worker_port $worker_user@$worker_host

# Verify configuration
cat ~/.ml/config.toml
```

#### Sync Failures
```bash
# Check rsync
rsync --version

# Manual sync test
rsync -avz ./test/ $worker_user@$worker_host:/tmp/
```

#### Performance Issues
```bash
# Monitor resource usage
top -p $(pgrep ml)

# Check disk space
df -h $worker_base
```

### Debug Mode

Enable verbose logging:
```bash
# Environment variable
export ML_DEBUG=1
ml sync ./project

# Or use debug build
cd cli && make debug
```

## Performance Benchmarks

### File Operations
- **Sync Speed**: 100MB/s+ (network limited)
- **Hash Computation**: 500MB/s+ (CPU limited)
- **Deduplication**: 90%+ space savings

### Memory Usage
- **Base Memory**: ~10MB
- **Large Projects**: ~50MB (1GB+ projects)
- **Memory Efficiency**: Constant per-file overhead

### Network Performance
- **WebSocket Latency**: <10ms (local network)
- **Connection Setup**: <100ms
- **Throughput**: Network limited

## Contributing

### Development Setup
```bash
cd cli
zig build-exe src/main.zig
```

### Testing
```bash
# Run tests
cd cli && zig test src/

# Integration tests
zig test tests/
```

### Code Style
- Follow Zig style guidelines
- Use explicit error handling
- Document public APIs
- Add comprehensive tests

---

**For more information, see the [CLI Reference](/cli-reference/) and [Architecture](/architecture/) pages.**