llmcat is a fast and flexible command-line tool designed to facilitate the copying of files to large language models (LLMs). With its powerful features, llmcat supports fuzzy search and multi-file selection while seamlessly respecting .gitignore rules.

Key Features:

• Fuzzy Finder: Easily search and select files with a convenient interactive mode using fuzzy search capabilities.
• Multi-file Selection: Choose multiple files or entire directories with ease, simplifying your workflow significantly.
• Previews and Visualizations: Visualize the structure of your projects with directory trees and preview file contents before copying.
• Cross-platform Compatibility: Works smoothly across Linux and macOS systems.

How It Works:

llmcat uses simple commands to perform file operations. Here are some examples of usage:

# Copy a specific file
$ llmcat path/to/file.txt

# Copy all files from a directory
$ llmcat ./src/

# Initiate interactive mode (fuzzy finder)
$ llmcat

Interactive Mode:

If you run llmcat without providing a path, it opens an interactive file selection tool where you can:

• Press tab to select files.
• Use shift-tab to deselect files.
• Preview files by toggling the preview with ctrl-/.
• Confirm your selections with enter or exit with esc.

Command-line Options:

llmcat also supports various command-line options for tailored operations, such as ignoring specific files or printing outputs:

# Copy while ignoring certain file types
$ llmcat -i "*.log" ./src/

# Print output during the copy process
$ llmcat -p file.txt

# Display only the directory structure
$ llmcat -t ./src/

Manual and Help:

You can easily access comprehensive help and commands by using the -h option for llmcat:

llmcat - Prepare files and directories for LLM consumption

Usage: llmcat [options] [path]

Whether you're preparing files for advanced machine learning tasks or simply managing your development resources effectively, llmcat streamlines the process and saves you time.

Explore more on our Blog, or check out an Interactive Demo to see llmcat in action!