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A comprehensive toolkit for end-to-end risk-aware benchmarking of autonomous agents

Project description

RiskBench Suite

A comprehensive toolkit for end-to-end risk-aware benchmarking of autonomous agents.

Features

  • 🔍 Task specification and execution
  • 📊 Risk metrics calculation and monitoring
  • 🌐 Interactive web dashboard
  • 🐳 Docker support
  • 📈 Prometheus metrics integration

Quick Start

# Install from PyPI
pip install riskbench-suite

# Or with Poetry
poetry add riskbench-suite

Usage

  1. Define a task:
name: MyTask
description: A sample task
environment:
  type: SeleniumEnv
  config:
    url: https://example.com
success_criteria:
  - type: ElementPresent
    selector: "#success-message"
risk_metrics:
  - type: CVaR
    alpha: 0.9
    threshold: 100.0
  1. Run the task:
riskbench run task.yaml
  1. View results in the dashboard:
riskbench dashboard
# Open http://localhost:8000

Documentation

Full documentation is available at docs/.

Contributing

We welcome contributions! Please see our Contributing Guide.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use RiskBench Suite in your research, please cite:

@software{riskbench_suite,
  title = {RiskBench Suite},
  author = {Your Name},
  year = {2025},
  url = {https://github.com/yourusername/riskbench-suite}
}

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