Command-line interface for LLM Meter - Track and monitor your LLM usage, costs, and performance across multiple providers (OpenAI, Anthropic, Ollama, etc.).

• View usage statistics and costs
• List individual API requests with token details
• Interactive REPL mode for exploring data
• Server management commands
• Model pricing configuration

npm install -g llm-meter-cli

Or install and run with npx:

npx llm-meter-cli

# Show usage statistics
llm-meter stats

# List recent API requests
llm-meter requests

# View details of a specific request
llm-meter request <request-id>

# View model pricing
llm-meter pricing

# Start the LLM Meter server
llm-meter serve

• --help: Show help information for any command
• -p, --project <name>: Filter by project
• --page <number>: Page number for requests (default: 1)
• --limit <number>: Requests per page (default: 20)

Run llm-meter without any arguments to enter the interactive REPL mode:

llm-meter

This launches a shell where you can run commands like:

• stats - Show usage statistics
• requests - List recent requests
• pricing - View model pricing
• help - Show available commands

The CLI connects to the LLM Meter backend server. You can configure the API endpoint using the LLM_METER_API environment variable:

export LLM_METER_API=http://localhost:3001/api

Default endpoint: http://localhost:3001/api

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Commit your changes (git commit -m 'Add amazing feature')
5. Push to the branch (git push origin feature/amazing-feature)
6. Open a Pull Request

MIT