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lrag

v0.1.5

Published

CLI tool for searching indexed documents in LocalRAG VS Code extension

Readme

lrag - LocalRAG CLI Tool

A lightweight command-line interface for searching indexed documents in the LocalRAG VS Code extension.

Prerequisites

The LocalRAG VS Code extension must be installed and running for this CLI to work. The CLI communicates with the extension via REST API.

Install the VS Code extension:

code --install-extension borgius.localrag

Installation

# Install globally
npm install -g lrag

# Or use directly with npx
npx lrag --help

Usage

# Search for documents (default command)
lrag "how to configure webpack"

# Search with explicit --search flag
lrag --search "authentication flow"

# List all topics
lrag --list

# Show details for a specific topic
lrag --topic Default

# Show extension status
lrag --status

# Output results in JSON format
lrag --json "error handling"

# Compact JSON output
lrag --compact "error handling"

# Limit number of results
lrag -n 5 "configuration"

Options

  • --search, -s <query> - Search indexed documents (default)
  • --list, -l - List all topics
  • --topic, -t <name> - Show details for a specific topic
  • --status - Show extension status
  • -j, --json - Output results in JSON format
  • -c, --compact - Output compact JSON (implies --json)
  • -n, --limit <number> - Maximum results to return (default: 10)
  • -h, --help - Show help message
  • -v, --version - Show version

How It Works

The CLI tool communicates with the LocalRAG VS Code extension via a REST API running on localhost:3875. The extension must be running in VS Code for the CLI to function.

Troubleshooting

"Could not connect to LocalRAG extension"

Make sure:

  1. VS Code is running
  2. The LocalRAG extension is installed
  3. The extension has activated (open the Command Palette and run "LocalRAG: Search Documents" to ensure it's loaded)

Check if extension is installed

code --list-extensions | grep localrag

Install the extension

code --install-extension borgius.localrag

Related

License

MIT