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An AI-powered tool to automatically document, refactor, and format Python code.

Project description

AutoDoc AI

PyPI version License: MIT

AutoDoc AI is a smart command-line developer tool that automates the tedious parts of maintaining high-quality Python code. It leverages Large Language Models (LLMs) to automatically generate docstrings, suggest intelligent refactorings, and integrate seamlessly into a modern development workflow.

This project was built on a foundation of solid Object-Oriented Programming principles and design patterns, including the Visitor, Strategy, Factory, and Adapter patterns.


Core Features

  • AI-Powered Docstring Generation: Automatically create high-quality, context-aware docstrings for any function or class that's missing them.
  • Intelligent Docstring Correction: Uses AI to evaluate existing docstrings and replaces poor-quality or placeholder documentation with new, improved versions.
  • AI-Powered Refactoring:
    • Safe Variable Renaming: Automatically renames poorly named local variables within function scope.
    • Intelligent Naming Suggestions: Acts as an AI-powered linter, suggesting better names for classes and functions.
  • Seamless Git Integration: Use the --diff flag to only process files that have been changed in your current Git branch.
  • Codebase-Wide Scanning: Run autodoc on a single file or an entire directory, with automatic .gitignore respect.
  • Automatic Formatting: Integrates with the black code formatter to ensure all generated and refactored code is perfectly styled.
  • Highly Configurable: Set project-wide defaults for style, AI provider, and behavior in your pyproject.toml file.

Installation

You can install AutoDoc AI directly from PyPI:

pip install autodoc-ai-paudelnirajan

First-Time Setup

Before you can use the AI features, you need to configure your API key. The easiest way is to use the built-in init command in your project's root directory.

autodoc init

This will guide you through creating or updating a .env file with your Groq API key and preferred model.

Configuration

AutoDoc uses a .env file for secrets and a pyproject.toml file for project-wide settings.

1. API Credentials (.env)

The autodoc init command will create this for you. It should look like this:

GROQ_API_KEY="gsk_YourActualGroqApiKeyHere"
GROQ_MODEL_NAME="llama3-8b-8192"

2. Project Defaults (pyproject.toml)

You can set default behaviors for your project in pyproject.toml. These settings will be used unless they are overridden by a command-line flag.

# In your pyproject.toml

[tool.autodoc]
# Settings for your AutoDoc tool
strategy = "groq"
style = "google"           # 'google', 'numpy', or 'rst'
overwrite_existing = true  # Regenerate poor-quality docstrings
refactor = true            # Enable AI-powered refactoring

Usage

AutoDoc is a flexible command-line tool with two main commands: init and run.

Get a list of commands:

autodoc --help

Get detailed help for the run command and all its flags:

autodoc run --help

Run on a specific file (dry run, prints to console):

autodoc run path/to/your/file.py

Run on an entire directory and save changes in-place:

autodoc run src/ --in-place

Run in "Git mode" to only process changed files (most common use case):

autodoc run . --diff --in-place

Enable all AI features to perform a full quality pass:

autodoc run . --in-place --overwrite-existing --refactor

How It Works

AutoDoc uses a "Surgical Hybrid" architecture that combines the strengths of traditional and modern tooling:

  1. Fast Local Analysis: It uses Python's ast (Abstract Syntax Tree) module to rapidly parse code and identify potential issues.
  2. Targeted AI Intelligence: Only when a potential issue is found does it send the small, relevant code snippet to an LLM for intelligent analysis.
  3. Precise Code Modification: The AI's response is used to perform a safe and precise modification of the AST, which is then unparsed back into valid Python code.
  4. Toolchain Integration: Finally, it uses black to ensure the final code is perfectly formatted, integrating seamlessly into the existing Python ecosystem.

License

This project is licensed under the MIT License.

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