semvec/pypi-packages huggingface dataset:
aegis-detect 0.1.6
AI Code Classifier Tool
Requires Python: >=3.10

# Aegis: AI vs. Human Python Code Classifier

## Overview
Aegis is a fine-tuned CodeBERT model designed to classify AI-generated and human Python code. While CodeBERT contains 125 million parameters, Aegis was efficiently trained locally using LoRA (Low-Rank Adaptation), updating only a subset of the original parameters.

This project investigates classifying code based on semantic differences. Consequently, the dataset (20K Python samples: 10K AI + 10K Human) was aggressively cleaned to ensure standard formatting and the removal of comments and docstrings. A confidence threshold of 0.7 was established to flag samples as AI-generated only when strong evidence exists. Aegis is not a definitive judge; predictions can be imperfect, particularly in tasks where semantic convergence between humans and AI is observed (e.g., LeetCode solutions).

## Installation

```bash
pip install aegis-detect
```

### CLI Usage

**Supported commands**:
```bash
# Predicting using a file
aegis --file path/to/code.py

# Predicting using text
aegis --text "def add(a, b):\n    return a + b"

# JSON output
aegis --file path/to/code.py --json > result.json

# Setting a threshold for AI classification 
aegis --file path/to/code.py --threshold 0.7

# Help
aegis --help

# Uninstall
aegis-cleanup 
pip uninstall aegis-detect
```

**Notes**:
- On first run, the model adapter is downloaded from the Hugging Face repo [anthonyq7/aegis](https://huggingface.co/anthonyq7/aegis) and cached under `~/.aegis/models`.
- Internet access is required on the first run; subsequent runs use local cache. 
- The CLI prints the predicted label and probabilities for human and AI.

## Contact
**Email**: a.j.qin@wustl.edu

**Email**: ethanqin@bu.edu

## License
This project is licensed under the [MIT License](LICENSE).
hexdoc-hexxyplanes 0.2.1.1.20.1.1.0
A small personal dimension, perfect for all your secret keeping needs
Requires Python: >=3.12
Keywords: hexdoc

# hexdoc-hexxyplanes

Python web book docgen and [hexdoc](https://pypi.org/project/hexdoc) plugin for Hexxyplanes.

A small personal dimension, perfect for all your secret keeping needs

## Version scheme

We use [hatch-gradle-version](https://pypi.org/project/hatch-gradle-version) to generate the version number based on whichever mod version the docgen was built with.

The version is in this format: `mod-version.python-version.mod-pre.python-dev.python-post`

For example:
* Mod version: `0.11.1-7`
* Python package version: `1.0.dev0`
* Full version: `0.11.1.1.0rc7.dev0`

## Setup

Install [uv](https://docs.astral.sh/uv/getting-started/installation/), then:

```sh
uv sync

.\.venv\Scripts\activate   # Windows
. .venv/bin/activate.fish  # fish
source .venv/bin/activate  # everything else
```

## Usage

For local testing, create a file called `.env` in the repo root following this template:

```sh
GITHUB_REPOSITORY=Real-Septicake/HexxyPlanes
GITHUB_SHA=main
GITHUB_PAGES_URL=https://real-septicake.github.io/HexxyPlanes
```

Useful commands:

```sh
# update your Python environment and lockfile if you added new dependencies
uv sync

# show help
hexdoc -h

# render and serve the web book in watch mode
nodemon --config doc/nodemon.json

# render and serve the web book
hexdoc serve

# build and merge the web book
hexdoc build
hexdoc merge

# start the Python interpreter with some extra local variables
hexdoc repl
```