Observed since 20 Oct, 20:16 UTC
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aegis-detect
AI Code Classifier Tool
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).
pip install aegis-detect
Supported commands:
# 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:
~/.aegis/models.Email: a.j.qin@wustl.edu
Email: ethanqin@bu.edu
This project is licensed under the MIT License.
Download counts and popularity will appear here as the collector receives them.
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bdist_wheel · 6.21 KB · Python py3
sdist · 5.57 KB · Python source
Observed since 20 Oct, 20:16 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
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