Introduction

AnomalyLLM is a is a LLM enhanced few-shot anomaly detection framework.

• It consists of three key modules: (1)dynamic-aware encoder, (2)modality alignment and (3)in-context learning for detection.

Requirements

• networkx==3.2.1
• numpy==1.26.3
• PyYAML==6.0.1
• scikit-learn==1.4.0
• scipy==1.12.0
• torch==2.0.1
• torch_geometric==2.4.0
• torchaudio==2.0.2
• torchdata==0.7.1
• torchtext==0.17.0
• torchvision==0.15.2
• tqdm==4.66.1
• transformers==4.37.2
• urllib3==1.26.13

To install all dependencies:

pip install -r requirements.txt

Download Backbone

Please download backbone model and place them under ./backbone

Download Data

Due to the file size limit, we put the data on other sites. Please first download the data and put it in data folder. The data can be download at: here

Training & Evaluating

To train AnomalyLLM, run the following command:

python pre_training.py -dataset uci

python alignment.py -dataset uci

You can evaluate on UCI Message datasets by:

python evaluate.py -dataset uci