doc-comments-ai 0.1.9

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Generate your code documentation with doc-comments.ai

Focus on writing your code, let AI write the documentation for you.

With just a few keystrokes in your terminal by using the OpenAI API or 100% local LLMs without any data leaks.

Powered by langchain, lama.cpp and treesitter.

✨ Features

• 📝 Create documentation comment blocks for all methods in a file
  • e.g. Javadoc, JSDoc, Docstring, Rustdoc
• ✍️ Create inline documentation comments in method bodies
• 🌳 Treesitter integration
• 💻 Local LLM support

[!NOTE] Documentations will only be added to files without unstaged changes, so that nothing is overwritten.

🚀 Usage

Create documentations for any method in the file with GPT-3.5 Turbo model:

aicomments <RELATIVE_FILE_PATH>

Create also documentation comments in the method body:

aicomments <RELATIVE_FILE_PATH> --inline

Use GPT-4 model (Default is GPT-3.5):

aicomments <RELATIVE_FILE_PATH> --gpt4

Guided mode, confirm documentation generation for each method:

aicomments <RELATIVE_FILE_PATH> --guided

Use a local LLM on your machine:

aicomments <RELATIVE_FILE_PATH> --local --model_path <RELATIVE_MODEL_PATH>

⚙️ Supported Languages

• Python
• Typescript
• Javascript
• Java
• Rust
• Kotlin
• Go
• C++
• C
• Scala

📋 Requirements

• Python >= 3.9

🔧 Installation

1. OpenAI API usage

Create your personal OpenAI API key and add it as $OPENAI_API_KEY to your environment with:

export OPENAI_API_KEY=<YOUR_API_KEY>

Install with pipx:

pipx install doc-comments-ai

It is recommended to use pipx for installation, nonetheless it is also possible to use pip.

2. Local LLM usage

By using a local LLM no API key is required. The recommended way for the installation is pip since CMake arguments needs to be passed to the llama.cpp build for better performance which is not possible with pipx. You can also use the OpenAI API with this installation.

[!WARNING]
If your are sensitive to your global pip packages you may consider to checkout the repo and install and run it manually with poetry or conda.

See the following instructions for your machine with CMake: installation-with-hardware-acceleration and install llama-cpp-python with your desired hardware acceleration, e.g. for Metal on Mac run:

CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python

To install doc-comments.ai which should use your previously installed llama.cpp build run:

pip install doc-comments-ai

[!IMPORTANT]
The results by using a local LLM will highly be affected by your selected model. To get similar results compared to GPT-3.5/4 you need to select very large models which require a powerful hardware.