Inspect Harbor
Harbor is a framework for building, evaluating, and optimizing AI agents in containerized environments. Inspect Harbor provides an interface to run Harbor tasks using Inspect AI.
pip install inspect-harbor
Then in Python:
from inspect_ai import eval
from inspect_harbor import aider_polyglot
eval(aider_polyglot(), model="openai/gpt-5-mini")
Or load any dataset directly via the generic harbor() interface:
from inspect_ai import eval
from inspect_harbor import harbor
eval(
harbor(package_name="aider/aider-polyglot", package_ref="latest"),
model="openai/gpt-5-mini",
)
For full documentation, see https://meridianlabs-ai.github.io/inspect_harbor. The docs site covers installation, the Harbor task model, the default agent scaffold, task parameters, the generic harbor() interface (org/name and name@version datasets, plus local/git tasks), and a complete catalog of available datasets.
See CHANGELOG.md for release notes.
Development
Clone the repository and install development dependencies:
git clone https://github.com/meridianlabs-ai/inspect_harbor.git
cd inspect_harbor
make install # Installs dependencies and sets up pre-commit hooks
Run tests and checks:
make check # Run linting (ruff check + format) and type checking (pyright)
make test # Run tests
make cov # Run tests with coverage report
Clean up build artifacts:
make clean # Remove cache and build artifacts
Credits
This work is based on contributions by @iphan and @anthonyduong9 from the inspect_evals repository:
1 maintainer
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