# Docify AI 🚀: Intelligent Documentation & Test Generation for Your Code
[](https://pypi.org/project/docify-ai/)
[](https://pypi.org/project/docify-ai/)
[](LICENSE)
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 and tests.
* **💡 Multi-Format Output**: Generate `README.md` files or receive runnable pytest tests.
* **📂 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`.
```bash
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](https://aistudio.google.com/app/apikey) for Gemini, or from the [OpenAI platform](https://platform.openai.com/api-keys) 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):**
```bash
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):**
```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.
```bash
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.md` for docs, `tests/` for tests, `WORKFLOWS.md` for workflows.
* **`--client <openai|gemini>` / `-c <openai|gemini>`**: Choose the AI client to use for generation. Options are `openai` or `gemini` (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`**: Generate `pytest` test files instead of a README.
* **`--ignore-dirs <dir1> <dir2>...`**: A space-separated list of directory names to ignore during scanning. (e.g., `.git __pycache__ node_modules`).
* **`--ignore-exts <ext1> <ext2>...`**: A space-separated list of file extensions to ignore (e.g., `.tmp .pyc .log`).
**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:
```bash
docify --path /path/to/my-other-project --output DOCS.md
```
2. To use the OpenAI client for README generation:
```bash
docify --client openai
```
3. To use the OpenAI client and provide the API key directly (overriding any environment variable):
```bash
docify --client openai --key sk-YOUR_OPENAI_API_KEY
```
4. To generate `pytest` tests for the current project using the Gemini client, ignoring `dist` and `build` directories:
```bash
docify --test --client gemini --ignore-dirs dist build
```
## 1.3.0 - 2025-08-22
- Added `--ignore-dirs` and `--ignore-exts` option, to ignore the irrelevant or unwanted directories and files to generate the docs/readme or tests.
## 1.2.0 - 2025-08-21
- Added `-t` or `--test` option, 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 `--key` argument to provide api key, without setting it as environment variable.
- 🔍 Case-insensitive `--client` option
## 1.0.0 - 2025-08-15
- 🚀 Initial release
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"description": "# Docify AI \ud83d\ude80: Intelligent Documentation & Test Generation for Your Code\r\n\r\n[](https://pypi.org/project/docify-ai/)\r\n[](https://pypi.org/project/docify-ai/)\r\n[](LICENSE)\r\n\r\nA 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.\r\n\r\n\r\n## Key Features \u2728\r\n\r\n* **\ud83e\udd16 AI-Powered Content Generation**: Leverages large language models (Google Gemini and OpenAI GPT) to write human-like, technical documentation and tests.\r\n* **\ud83d\udca1 Multi-Format Output**: Generate `README.md` files or receive runnable pytest tests.\r\n* **\ud83d\udcc2 Intelligent Code Analysis**: Scans your entire project directory, intelligently ignoring irrelevant files and directories, to understand its purpose, technologies, and structure.\r\n* **\u2699\ufe0f Flexible AI Client Selection**: Choose between Google Gemini and OpenAI GPT models for content generation directly from the command line.\r\n* **\ud83d\udd11 API Key Management**: Supports API keys via environment variables or direct command-line arguments for both Gemini and OpenAI.\r\n* **\ud83d\ude80 Fast and Efficient**: Go from a messy project folder to a polished README, tests, or workflows in under a minute.\r\n* **\ud83d\udd27 Customizable Output**: Easily specify the project path to analyze and the desired output file or directory name.\r\n\r\n\r\n## Installation \ud83d\udce6\r\n\r\nDocify-AI is available on PyPI and can be installed on any system with Python 3.8 or newer using `pip`.\r\n\r\n```bash\r\npip install docify-ai\r\n```\r\n\r\n## Usage \ud83d\ude80\r\n\r\nUsing Docify-AI is straightforward, involving a one-time API key setup and a simple command execution.\r\n\r\n### 1. Set Your API Key\r\n\r\nDocify-AI requires an API key for the chosen AI model (Google Gemini or OpenAI). You can obtain a free key from [Google AI Studio](https://aistudio.google.com/app/apikey) for Gemini, or from the [OpenAI platform](https://platform.openai.com/api-keys) for OpenAI.\r\n\r\nOnce you have your key, set it as an environment variable:\r\n\r\n* For **Google Gemini**: `GEMINI_API_KEY`\r\n* For **OpenAI**: `OPENAI_API_KEY`\r\n\r\n**For macOS / Linux (bash/zsh):**\r\n\r\n```bash\r\nexport GEMINI_API_KEY='your-gemini-secret-api-key'\r\n# OR\r\nexport OPENAI_API_KEY='your-openai-secret-api-key'\r\n```\r\n*(To make this permanent across terminal sessions, add the line to your shell's configuration file, e.g., `~/.zshrc` or `~/.bashrc`.)*\r\n\r\n**For Windows (PowerShell):**\r\n\r\n```powershell\r\n$Env:GEMINI_API_KEY=\"your-gemini-secret-api-key\"\r\n# OR\r\n$Env:OPENAI_API_KEY=\"your-openai-secret-api-key\"\r\n```\r\n\r\nAlternatively, you can pass the API key directly via the `--key` argument, which will override the environment variable.\r\n\r\n### 2. Run Docify-AI\r\n\r\nNavigate 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.\r\n\r\n```bash\r\ndocify\r\n```\r\nThe tool will scan the current directory and generate a `README.md` file with AI-powered content.\r\n\r\n### Command-Line Options\r\n\r\nYou can customize the behavior of Docify-AI using the following command-line arguments:\r\n\r\n* **`--path <directory>` / `-p <directory>`**: Specifies the root directory of the project to be documented. Defaults to the current working directory (`.`).\r\n* **`--output <filename>` / `-o <filename>`**: Defines the name of the output file/folder. Defaults: `README.md` for docs, `tests/` for tests, `WORKFLOWS.md` for workflows.\r\n* **`--client <openai|gemini>` / `-c <openai|gemini>`**: Choose the AI client to use for generation. Options are `openai` or `gemini` (default: `gemini`). 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