Documentation

# Download from your purchase email
# Extract and move to PATH

# macOS/Linux
chmod +x logtorque
sudo mv logtorque /usr/local/bin/

# Windows (PowerShell as Admin)
Move-Item logtorque.exe C:\Windows\System32\

# Verify installation
logtorque --version

The Demo tier uses Ollama for local AI processing. Your logs never leave your machine. Paid tiers also support cloud LLMs.

Install / Update Ollama

Always use the latest version. Older versions may cause model errors.

# macOS
brew install ollama

# Linux
curl -fsSL https://ollama.com/install.sh | sh

# Windows
# Download from https://ollama.com/download

Recommended Models

Note: tinyllama is useful for quickly testing that the app works, but output quality is poor. Use llama3.2 or larger for real analysis.

Pull a Model

# Recommended for most users
ollama pull llama3.2

# Start Ollama server (runs in background)
ollama serve

Hardware Requirements

• Minimum: 8 GB RAM, any modern CPU
• Recommended: 16 GB RAM, Apple Silicon or NVIDIA GPU
• GPU acceleration: NVIDIA (CUDA), Apple Silicon (Metal), AMD (ROCm on Linux)

# Analyze a log file
logtorque analyze /var/log/nginx/error.log

# Pipe from another command
docker logs my-container | logtorque analyze -

# From kubectl
kubectl logs pod-name | logtorque analyze -

# Set default LLM provider
logtorque config set provider ollama

# Set API key (for cloud providers)
logtorque config set openai-key sk-xxx

# View current config
logtorque config list

# Plain text (default)
logtorque analyze error.log

# JSON
logtorque analyze error.log --format json

# Markdown
logtorque analyze error.log --format markdown

Available in Pro and Team tiers.

# Monitor a log file in real-time
logtorque watch /var/log/app.log

# With alerts
logtorque watch /var/log/app.log --alert-level error