An AI-powered README.md generator for local projects.
Project description
Docify AI 🚀: Intelligent Documentation for Your Code
A versatile AI-powered command-line tool for instantly generating comprehensive README.md files, pytest tests, and Mermaid workflow diagrams for your local projects, powered by Google Gemini and OpenAI GPT models.
Key Features ✨
- 🤖 AI-Powered Content Generation: Leverages large language models (Google Gemini and OpenAI GPT) to write human-like, technical documentation.
- 💡 Multi-Format Output: Generate
README.mdfiles, receive runnable pytest tests, or visualize project workflows with Mermaid diagrams. - 📂 Intelligent Code Analysis: Scans your entire project directory, intelligently ignoring irrelevant files and directories, to understand its purpose, technologies, and structure.
- ⚙️ Flexible AI Client Selection: Choose between Google Gemini and OpenAI GPT models for content generation directly from the command line.
- 🔑 API Key Management: Supports API keys via environment variables or direct command-line arguments for both Gemini and OpenAI.
- 🚀 Fast and Efficient: Go from a messy project folder to a polished README, tests, or workflows in under a minute.
- 🔧 Customizable Output: Easily specify the project path to analyze and the desired output file or directory name.
Installation 📦
Docify-AI is available on PyPI and can be installed on any system with Python 3.8 or newer using pip.
pip install docify-ai
Usage 🚀
Using Docify-AI is straightforward, involving a one-time API key setup and a simple command execution.
1. Set Your API Key
Docify-AI requires an API key for the chosen AI model (Google Gemini or OpenAI). You can obtain a free key from Google AI Studio for Gemini, or from the OpenAI platform for OpenAI.
Once you have your key, set it as an environment variable:
- For Google Gemini:
GEMINI_API_KEY - For OpenAI:
OPENAI_API_KEY
For macOS / Linux (bash/zsh):
export GEMINI_API_KEY='your-gemini-secret-api-key'
# OR
export OPENAI_API_KEY='your-openai-secret-api-key'
(To make this permanent across terminal sessions, add the line to your shell's configuration file, e.g., ~/.zshrc or ~/.bashrc.)
For Windows (PowerShell):
$Env:GEMINI_API_KEY="your-gemini-secret-api-key"
# OR
$Env:OPENAI_API_KEY="your-openai-secret-api-key"
Alternatively, you can pass the API key directly via the --key argument, which will override the environment variable.
2. Run Docify-AI
Navigate to the root directory of the project you wish to document and simply run the docify command. By default, it uses the Gemini model to generate a README.
docify
The tool will scan the current directory and generate a README.md file with AI-powered content.
Command-Line Options
You can customize the behavior of Docify-AI using the following command-line arguments:
--path <directory>/-p <directory>: Specifies the root directory of the project to be documented. Defaults to the current working directory (.).--output <filename>/-o <filename>: Defines the name of the output file/folder. Defaults:README.mdfor docs,tests/for tests,WORKFLOWS.mdfor workflows.--client <openai|gemini>/-c <openai|gemini>: Choose the AI client to use for generation. Options areopenaiorgemini(default:gemini). Case-insensitive.--key <your-api-key>/-k <your-api-key>: Provide your API key directly. This will take precedence over environment variables.--test/-t: Generatepytesttest files instead of a README.--workflow/-w: Generate Mermaid workflow diagrams instead of a README.
Examples:
-
To document a project located at
/path/to/my-other-projectand save the output toDOCS.mdusing the default Gemini model:docify --path /path/to/my-other-project --output DOCS.md
-
To use the OpenAI client for README generation:
docify --client openai
-
To use the OpenAI client and provide the API key directly (overriding any environment variable):
docify --client openai --key sk-YOUR_OPENAI_API_KEY
-
To generate
pytesttests for the current project using the Gemini client:docify --test --client gemini
-
To generate Mermaid workflow diagrams and save them to
project-workflows.md:docify --workflow --output project-workflows.md
License 📄
This project is licensed under the MIT License - see the LICENSE file for details.
Changelog 📜
See the CHANGELOG.md file for a history of changes and release notes.
1.2.0 - 2025-08-21
- Added
-tor--testoption, to generate pytest supported test directory including test modules for all the features of your project.
1.1.1 - 2025-08-20
- fixed project description not visible issue
1.1.0 - 2025-08-20
- ✨ Added support for OpenAI + Gemini clients
- 🛠 Added
--keyargument to provide api key, without setting it as environment variable. - 🔍 Case-insensitive
--clientoption
1.0.0 - 2025-08-15
- 🚀 Initial release
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