docify-ai 1.1.1

An AI-powered README.md generator for local projects.

Docify AI 🚀

Instantly generate beautiful, comprehensive README.md files for your local projects using the power of AI, supporting both 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.
• 📂 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 in under a minute.
• 🔧 Customizable Output: Easily specify the project path to analyze and the desired output file 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.

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>: Specifies the root directory of the project to be documented. Defaults to the current working directory (.).
• --output <filename>: Defines the name of the output markdown file. Defaults to README.md.
• --client <openai|gemini>: Choose the AI client to use for generation. Options are openai or gemini (default: gemini). Case-insensitive.
• --key <your-api-key>: Provide your API key directly. This will take precedence over environment variables.

Examples:

1. To document a project located at /path/to/my-other-project and save the output to DOCS.md using the default Gemini model:

   docify --path /path/to/my-other-project --output DOCS.md
   

2. To use the OpenAI client for documentation:

   docify --client openai
   

3. To use the OpenAI client and provide the API key directly (overriding any environment variable):

   docify --client openai --key sk-YOUR_OPENAI_API_KEY
   

4. To document a project using the Gemini client and specify the output file:

   docify --client gemini --output project-readme.md
   

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 --key argument to provide api key, without setting it as environment variable.
• 🔍 Case-insensitive --client option

1.0.0 - 2025-08-15

• 🚀 Initial release