AgentCompass currently needs to be installed from source. This page explains how to prepare the host environment,
install AgentCompass, configure optional dependencies, and verify local or remote execution environments.
For other Linux distributions, use the appropriate package manager to install these tools. See the
official Git installation page for Git-specific instructions.
macOS includes curl, unzip, and CA certificates. Use the Xcode Command Line Tools for native builds and
Homebrew for Git and wget:
xcode-select --installbrew install git wget
Windows includes curl.exe, and PowerShell provides archive extraction through Expand-Archive. Install Git with
WinGet:
Alternatively, install Scoop using its official instructions, then manage Git and wget with:
scoop install git wget
Use WSL 2 for workloads that require /bin/sh, POSIX paths, or Unix build tools.
Before running an evaluation, you also need model endpoint credentials and a supported execution environment. See
Supported Operating Systems for details.After completing these steps, verify that Git and curl are available:
Install AgentCompass in an isolated virtual environment. Do not mix uv, pip, and conda in the same environment
unless you understand how each tool resolves dependencies.First, clone the repository and enter the project directory:
If the host does not already have Python 3.12, the commands above install and manage a Python 3.12 runtime through
uv. See the uv Python installation guide.
Verify the installation: With the environment activated, confirm that the Python version is correct and the
AgentCompass CLI is available:
python --versionagentcompass --version
To browse results with agentcompass view from a source install, also install Node.js 20.19+ or 22.12+; the viewer frontend is built automatically on the first run.
The base installation includes only AgentCompass’s core dependencies; you do not need to preinstall every component
dependency. When an evaluation starts, AgentCompass checks dependencies as needed for the selected benchmark and
harness.If you plan to run SWE-bench or use mini-swe-agent locally on the host, you can preinstall both sets of optional
dependencies:
uv pip install -e ".[swebench,mini-swe-agent]"
If a dependency is missing, AgentCompass stops and displays the appropriate installation command. Install the
dependency, then rerun the original command. You can also enable automatic installation for trusted built-in
components:
agentcompass run <benchmark> <harness> <model> --auto-install-dependencies
--auto-install-dependencies installs dependencies only in the host Python environment that runs AgentCompass. It
does not modify Docker, Daytona, or Modal environments; their dependencies come from the task image or environment
configuration.
To prepare an offline environment or review all optional dependencies, see
Dependency Management.
Prepare the execution environment required by each selected benchmark. Running multiple benchmarks may require
different environments.See Environments in the User Guide for selection guidance, parameters,
resources, and network configuration.
host_process
Docker
Daytona
Modal
host_process runs commands as normal subprocesses and uses the real host filesystem, installed tools, permissions,
and network access. It starts quickly but provides no isolation, and results can vary with host state.Linux and WSL 2 are fully supported. Use macOS only for lightweight or service-backed workloads explicitly supported
by the benchmark documentation, because packages, utilities, paths, and evaluation scripts can still depend on
Linux. Native Windows is unsupported because the current implementation and common workflows rely on /bin/sh,
POSIX paths, permissions, and signals.
Do not use host_process for an untrusted agent or one that can execute commands. It can read, modify, or delete
files available to your user account and start processes directly on the host.
Docker creates an isolated container for each task; its dependencies and filesystem layout come from the task image.
It is more consistent than host_process, but the first run may need to pull a large image.AgentCompass supports local Docker on Linux and WSL 2. Follow the
Docker Engine installation guide, then verify:
docker versiondocker infodocker run --rm hello-world
If the docker group was created during installation, skip the first command.
Membership in the docker group grants root-level privileges on the host.
On WSL 2, choose one topology: install Docker Engine inside the WSL distribution, or enable Docker Desktop
WSL integration. Do not maintain both daemons. Keep the checkout in
the WSL Linux filesystem, such as ~/code/AgentCompass, rather than under /mnt/c/.See the Docker guide for registry credentials, smoke tests, and
parameters.
Daytona runs tasks in cloud sandboxes and supports Linux, WSL, Windows, and macOS. Create an account and an
API key with sandbox access, then set the credential:
export DAYTONA_API_KEY="..."
Windows PowerShell:
$env:DAYTONA_API_KEY = "..."
API endpoints, target, and organization settings are optional. Never commit credentials to the repository. See the
Daytona guide for complete setup.
Modal runs tasks in cloud sandboxes and supports Linux, WSL, Windows, and macOS. Create an account, then follow the
user account setup guide or
service user guide to create a token and set the credentials:
Even if Docker Desktop can start Linux containers on native Windows or macOS, AgentCompass does not currently
support Docker Desktop as a local benchmark environment. Use WSL 2, Daytona, or Modal for coding, terminal, and
other Linux-specific workloads.
Run python --version; recreate the environment with Python >=3.12.
agentcompass: command not found
Activate the environment, reinstall editable mode, or use uv run agentcompass.
uv, pip, or dataset downloads fail
Check DNS, proxy, CA certificates, and HTTPS access to the package index.
Cannot connect to the Docker daemon
Start Docker and run docker info from the same Linux or WSL shell.
Docker works in Windows but not WSL
Enable Docker Desktop integration for that WSL 2 distribution.
Repository operations are slow in WSL
Move the checkout from /mnt/c/ to the WSL Linux filesystem.
Daytona startup fails
Verify the API key and optional API endpoint or target.
Modal authentication fails
Run modal token info and verify the active workspace credentials.
Optional dependency installation fails in a restricted sandbox
Preinstall it in the task image or prepare it before network access is disabled.
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