Human Time-to-Completion Evaluation CLI
Project description
hte-cli
Human Time-to-Completion Evaluation CLI - A tool for running assigned cybersecurity tasks with timing and result tracking.
Installation
# Recommended (pipx)
pipx install hte-cli
# Or with pip
pip install hte-cli
Quick Start
-
Login (get credentials from your coordinator):
hte-cli auth login
-
View your assigned tasks:
hte-cli tasks list
-
Run a task:
hte-cli tasks run
Commands
hte-cli auth login- Authenticate with the APIhte-cli auth status- Check authentication statushte-cli tasks list- List your pending taskshte-cli tasks run [TASK_ID]- Run a task (defaults to highest priority)hte-cli tasks pull-images- Pre-pull Docker images for upcoming taskshte-cli version- Show version info
System Requirements
All Platforms
- Python 3.11+
- Docker Engine >= 24.0.6
- Docker Compose >= 2.21.0 (included in Docker Desktop 4.25+)
Windows
- Docker Desktop with WSL2 backend enabled
- WSL2 installed and configured (Microsoft docs)
macOS
- Docker Desktop (Intel or Apple Silicon)
- Note: Apple Silicon (M1/M2/M3) runs x86 containers via emulation - expect slightly slower performance
Linux
- Docker Engine >= 24.0.6 with Compose plugin
- User added to docker group:
sudo usermod -aG docker $USER(log out and back in after)
Verify Docker Setup
# Check Docker Engine version (need >= 24.0.6)
docker version --format '{{.Client.Version}}'
# Check Docker Compose version (need >= 2.21.0)
docker compose version --short
# Test container can start
docker run --rm hello-world
If your Docker Compose version is too old, update Docker Desktop or install the latest compose plugin:
# Linux: Update compose plugin
sudo apt-get update && sudo apt-get install docker-compose-plugin
Configuration
Set HTE_API_URL environment variable to use a custom API endpoint:
export HTE_API_URL="http://your-server.com/api/v1/cli"
Support
For issues, contact your study coordinator or open an issue at: https://github.com/sean-peters-au/lyptus-mono
Developer Notes
This CLI is a thin wrapper with no consequential research decisions. It:
- Wraps Inspect AI's
human_cliagent for task execution - Syncs results to the backend API
- Handles authentication via OAuth-style code exchange
The research-relevant code lives elsewhere:
- Task sampling:
scripts/sample_tasks_for_trials.py - Scoring criteria:
src/human_ttc_eval/datasets/*/ - Methodology:
docs/methodology/human-expert-methodology-guide.md
Project details
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