luckyshot 0.3.0

A CLI tool for one-shot code generations using RAG and file watching
luckyshot-0.3.0 is not a library.

A powerful CLI tool that enhances code understanding by using RAG (Retrieval Augmented Generation) to find relevant files in your codebase.

Features

  • File scanning with customizable chunk sizes and overlap
  • Semantic search using OpenAI embeddings
  • Support for piped input and file suggestions
  • Intelligent context expansion

Installation

cargo install luckyshot

Usage

Scanning Files

Generate embeddings for your codebase using the scan command:

# Basic scan of all Rust files
luckyshot scan "**/*.rs"

# Basic scan of all Rust and Markdown files
luckyshot scan "**/*{.rs,.md}"

# Scan with chunking enabled
luckyshot scan --chunk-size 1000 --chunk-overlap 100 "src/**/*.rs"

# Include file metadata in embeddings
luckyshot scan --embed-metadata "*.{rs,md}"

# Scan with all options
luckyshot scan --chunk-size 1000 --chunk-overlap 100 --embed-metadata "**/*.rs"

The scan command:

  1. Finds files matching your pattern (respecting .gitignore)
  2. Generates embeddings using OpenAI's API
  3. Saves results to .luckyshot.file.vectors.v1

Finding Relevant Files

To find files related to a topic or question:

# Basic file suggestion
luckyshot suggest-files --prompt "how does the scanning work?"

# Using piped input
echo "how does error handling work?" | luckyshot suggest-files

# Filter results by similarity score (matches >= specified value, range 0.0 to 1.0)
luckyshot suggest-files --prompt "error handling" --filter-similarity 0.5

# Show detailed information including similarity scores
luckyshot suggest-files --prompt "file scanning" --verbose

# Show file contents of matches
luckyshot suggest-files --prompt "metadata handling" --file-contents

# Limit number of results
luckyshot suggest-files --prompt "openai" --count 5

# Combine options
luckyshot suggest-files --prompt "embedding" --verbose --file-contents --filter-similarity 0.7 --count 3

# Chain commands Unix-style
echo "what openai url am I using" | \
  luckyshot expand "you are a rust expert who describes their \
     question and the files you are looking for" | \
  luckyshot suggest-files --verbose

This will:

  1. Convert your query into an embedding
  2. Use BM25-style ranking to find similar files
  3. Display relevant files with similarity scores

Expanding Context

To expand a query with additional context:

luckyshot expand --system-prompt "You are a helpful assistant" --prompt "describe the implementation"

Environment Setup

You'll need an OpenAI API key. Either:

export OPENAI_API_KEY="your-api-key"

Or create a .env file:

OPENAI_API_KEY=your-api-key

License

MIT