luckyshot 0.4.0

A powerful CLI tool that enhances code understanding and automation 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 and BM25 ranking
• 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 -p "**/*.rs"

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

# Scan with chunking enabled
luckyshot scan --chunk-size 1000 --chunk-overlap 100 -p "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 -p "**/*.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 -p "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 -p "error handling" --filter-similarity 0.5

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

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

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

# Combine options
luckyshot suggest-files -p "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 cross-product ranking to find similar file embedding
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

Experimental

BM25 tokinization and ranking.

License

MIT