optiattack-client 0.1.1

A FastAPI decorator to track method calls and manage state.

OptiAttack Client

The OptiAttack Client (optiattack_client) is a FastAPI-based server package designed to facilitate remote integration between the OptiAttack core engine and external models or systems under test (NUT). It provides a simple decorator and API endpoints for seamless communication and adversarial test execution.

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Table of Contents

• Features
• Installation
• Quick Start
• API Endpoints
• Example Usage
• Configuration
• Contributing
• License

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Features

• FastAPI server for remote model or NUT integration
• Decorator-based interface for easy wrapping of prediction functions
• Automatic endpoint creation for running, stopping, and querying the NUT
• Supports image-based adversarial attacks
• Easy integration with OptiAttack core

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Installation

You can install the OptiAttack Client package using pip:

pip install optiattack-client

Alternatively, if you want to install from the local directory (for development or custom modifications), run:

cd client
pip install -e .

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Quick Start

1. Wrap your prediction function with the provided decorator:

from optiattack_client import collect_info

@collect_info(host="localhost", port=38000)
def predict(image_array):
    # Your prediction logic here
    return {"predictions": ...}

2. Start your script. The FastAPI server will automatically run and expose endpoints for OptiAttack to communicate with.

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API Endpoints

The client exposes the following endpoints (default base path: /api/v1):

• GET /api/v1/infoNUT — Get the current state of the NUT
• POST /api/v1/runNUT — Run a prediction on the NUT (expects base64-encoded image)
• POST /api/v1/stopNUT — Stop the NUT
• POST /api/v1/newAction — Apply a new action (mutation) and get prediction

See client/constants.py for all endpoint paths and defaults.

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Example Usage

from optiattack_client import collect_info

@collect_info(host="localhost", port=38000)
def predict(image_array):
    # Example: Use your ML model to predict
    # result = model.predict(image_array)
    return {"predictions": [0.1, 0.9]}  # Example output

# The FastAPI server is now running at http://localhost:38000

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Configuration

• Host and Port: Set via the collect_info decorator arguments.
• Endpoints: Configurable in client/constants.py.
• Python Version: Requires Python 3.9 or higher.

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Contributing

Contributions are welcome! Please open issues or pull requests for bug fixes, new features, or documentation improvements.

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License

This package is part of the OptiAttack project and is licensed under the GNU Lesser General Public License v3 (LGPLv3).