CodeSage 🔮

Wisdom for your code - AI-powered code review tool for Ruby projects.

CodeSage leverages the power of Large Language Models (LLM) through the llm_chain library to provide intelligent, context-aware code reviews for your Ruby projects. Get expert-level feedback on code quality, security, performance, and best practices.

• 🤖 AI-Powered Reviews: Intelligent code analysis using advanced language models
• 🔍 Git Integration: Seamless integration with Git workflows
• 📊 Multiple Output Formats: Console, JSON, and Markdown reports
• ⚙️ Configurable: Customizable review criteria and output preferences
• 🎯 Ruby-Focused: Specialized knowledge of Ruby best practices and idioms
• 🚀 CLI Interface: Easy-to-use command-line interface
• 🌐 Multiple LLM Providers: OpenAI, Ollama, Qwen, and more via llm_chain
• 🏠 Local Models: Support for local models through Ollama
• 🔧 System Diagnostics: Built-in health checks and configuration validation

Add this line to your application's Gemfile:

gem 'code_sage'

And then execute:

$ bundle install

Or install it yourself as:

$ gem install code_sage

Before starting, run diagnostics to ensure your system is properly configured:

$ code_sage diagnose

Review changes between your current branch and main:

$ code_sage review

# Review against a specific branch
$ code_sage review -b develop

# Review specific files
$ code_sage review -f lib/my_class.rb app/controllers/my_controller.rb

# Output in JSON format
$ code_sage review --format json

# Output in Markdown format  
$ code_sage review --format markdown

# Verbose output
$ code_sage review -v

# Review with custom configuration
$ code_sage review -c ~/.my_code_sage_config.yml

CodeSage can be configured using a YAML file. By default, it looks for ~/.code_sage.yml:

llm:
  provider: openai  # openai, ollama, qwen
  model: gpt-4
  temperature: 0.1
  max_tokens: 2000
  api_key: null  # Will use ENV variables

git:
  default_branch: main
  include_patterns:
    - "*.rb"
    - "*.rake"
    - "Gemfile"
    - "Rakefile"
  exclude_patterns:
    - "spec/**/*"
    - "test/**/*"

review:
  focus_areas:
    - security
    - performance
    - maintainability
    - best_practices
  severity_levels:
    - low
    - medium
    - high
    - critical

output:
  format: console
  verbose: false
  colors: true

Using OpenAI GPT-4:

llm:
  provider: openai
  model: gpt-4
  temperature: 0.1
  max_tokens: 2000

Using Local Ollama with Qwen:

llm:
  provider: qwen
  model: qwen2:7b
  temperature: 0.2

Using Local Ollama with LLaMA:

llm:
  provider: ollama
  model: llama2:7b
  temperature: 0.1

# Show current configuration
$ code_sage config --show

# Set LLM provider
$ code_sage config --key llm.provider --value ollama

# Set model
$ code_sage config --key llm.model --value qwen2:7b

# Reset to defaults
$ code_sage config --reset

You can also use CodeSage programmatically in your Ruby code:

require 'code_sage'

# Basic review
result = CodeSage.review

# With options
result = CodeSage.review(
  branch: 'develop',
  files: ['lib/my_file.rb'],
  format: 'json',
  verbose: true
)

puts result[:report] if result[:success]

Perform a code review on your repository.

Options:

• -b, --branch BRANCH - Branch to compare against (default: main)
• -f, --files FILES - Specific files to review
• --format FORMAT - Output format: console, json, markdown (default: console)
• -c, --config PATH - Path to configuration file
• -v, --verbose - Verbose output
• --rag - Enable RAG (Retrieval Augmented Generation) functionality

Manage configuration settings.

Options:

• --show - Show current configuration
• --key KEY --value VALUE - Set configuration values
• --reset - Reset configuration to defaults

Run comprehensive system diagnostics to check your setup.

Features:

• Check Ruby, Git, and llm_chain availability
• Validate API key configuration
• Display current LLM provider and model
• Provide setup recommendations

Show the current version of CodeSage.

• Ruby >= 2.7.0
• Git repository
• llm_chain gem configured with your preferred LLM provider

CodeSage supports multiple LLM providers through llm_chain:

export OPENAI_API_KEY="your-openai-api-key"

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Download models
ollama pull qwen2:7b
ollama pull llama2:7b

# Start Ollama server
ollama serve

• Anthropic: Set ANTHROPIC_API_KEY
• Google: Set GOOGLE_API_KEY
• Qwen: Available through Ollama

• llm_chain - For LLM integration
• thor - CLI framework
• colorize - Terminal colors
• rugged - Git integration

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org.

Bug reports and pull requests are welcome on GitHub at https://github.com/FuryCow/code_sage.

The gem is available as open source under the terms of the MIT License.

See CHANGELOG.md for version history and changes.