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---
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.**