@bxav/code-artisan
v0.0.30
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An AI-driven CLI tool for code refactoring across various programming languages.
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CodeArtisan
CodeArtisan is a cutting-edge Command Line Interface (CLI) tool designed to leverage Large Language Models (LLMs) for enhancing code quality across various programming languages. It offers intelligent, context-aware auto-fixing of linting issues and refactoring suggestions, ensuring your codebase adheres to the latest best practices and standards.
Installation
Install CodeArtisan globally using npm to start improving your codebase:
npm install -g @bxav/code-artisan
Initialization
Run the init
command to set up CodeArtisan in your project. This creates a .codeartisan
directory in your project root, containing a config.yml
for configuration and an examples
directory for custom setups:
code-artisan init
Your project structure will then include:
ProjectRoot/
└── .codeartisan/
├── config.yml
└── examples/
Configuring CodeArtisan
The config.yml
file within the .codeartisan
directory has been enhanced to suit your project's needs. You can specify the model type, name, and options such as temperature for the model's responses. This allows for a more tailored and precise code refactoring and linting experience.
# OpenAI API
model:
type: OpenAI
name: gpt-4-1106-preview # Example: gpt-4-1106-preview, ...
options:
temperature: 0.5
# Uncomment to use Mistral API
# model:
# type: Mistral
# name: mistral-small
# Uncomment to use a Local LLM
# model:
# type: Ollama
# name: codellama # Example: codellama:13b, ...
experts:
react:
pattern: .tsx, .jsx
role: Senior React Developer
codingStyles:
- path: ./.codeartisan/react-coding-styles.md
examples:
- path: ./.codeartisan/examples/reactExample1.tsx
- path: ./.codeartisan/examples/reactExample2.tsx
nestjs:
pattern: .service.ts, .module.ts, .controller.ts
role: Senior Nodejs Developer, expert in NestJS
codingStyles:
- path: ./.codeartisan/nestjs-coding-styles.md
- path: ./.codeartisan/nodejs-coding-styles.md
examples:
- path: ./.codeartisan/examples/example1.controller.ts
- path: ./.codeartisan/examples/example1.service.ts
- path: ./.codeartisan/examples/example1.module.ts
Usage
Smart Corrector (Auto-Fixing Linter)
smart-corrector
is a command within CodeArtisan aimed at automatically resolving linting issues in your code. It uses the expert roles, coding styles, and examples you've defined to tailor its fixes to your project's specifications.
Basic Command
Automatically fix linting issues throughout your project with:
code-artisan smart-corrector
This scans all relevant files in the current directory, defaulting to Git to identify changed files if no commit diff is specified.
Targeting Specific Files or Folders
Specify files or folders for linting fixes:
For individual files:
code-artisan smart-corrector path/to/your/file.tsx another/path/to/file.tsx
For folders:
code-artisan smart-corrector path/to/your/folder/
Command Options
The smart-corrector
supports several options to customize its operation, including --commit-diff
for Git commit diffs, --expert
for expert-specific suggestions, and --config
to specify an alternative configuration file:
code-artisan smart-corrector --commit-diff HEAD~1..HEAD
code-artisan smart-corrector --expert react
code-artisan smart-corrector --config path/to/your/config.yml
Advanced Usage
Combine multiple options for a comprehensive linting process, including the --config
parameter to use a custom configuration file:
code-artisan smart-corrector path/to/your/file.tsx --expert react --config path/to/your/config.yml
Environment Variables
To fully enable CodeArtisan's functionality with Large Language Models, you need to set specific environment variables:
- For using OpenAI models, set the
OPENAI_API_KEY
environment variable with your OpenAI API key. - For using Ollama models, set the
OLLAMA_BASE_URL
environment variable to specify the base URL of your Ollama service. This is crucial for the CLI to communicate with your local or hosted Ollama instance.
Example of setting environment variables:
export OPENAI_API_KEY='your_openai_api_key_here'
export OLLAMA_BASE_URL='http://localhost:11434' # Or the URL of your hosted Ollama service
Ensure these variables are correctly set in your environment to leverage the respective models' capabilities within CodeArtisan for code refactoring and linting.