pyproject.toml

[build-system]
requires = ["setuptools>=77"]  # a license given as an SPDX expression (PEP 639)
build-backend = "setuptools.build_meta"

[project]
name = "agent-ecc"
version = "0.2.2"
description = "Version-consistent experience consumption for agent training: validate recorded experience against a chosen verifier version, re-evaluate it when needed, and track what each training step actually consumes."
readme = "README.md"
license = "Apache-2.0"
license-files = ["LICENSE", "NOTICE"]
requires-python = ">=3.10"
dependencies = []
keywords = ["reinforcement learning", "agents", "evaluation", "grading", "reproducibility", "swe-bench", "appworld"]
classifiers = [
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]

[project.optional-dependencies]
# the official SWE-bench harness: log parsing, and re-execution in local Docker containers
swebench = ["swebench==5.0.2"]
# the AppWorld evaluator, for re-grading recorded end states
appworld = ["appworld>=0.1.3"]
# the reference re-verification service runs on the standard library; install the extras of the backends it serves
service = []
test = ["pytest>=7"]

[tool.setuptools]
package-dir = {"" = "src"}

[tool.setuptools.packages.find]
where = ["src"]

[tool.setuptools.package-data]
agent_ecc = ["py.typed"]

[tool.pytest.ini_options]
testpaths = ["tests"]
pythonpath = ["src", "tests"]
addopts = "-q"
markers = [
    "swebench: needs the official swebench harness (skipped when it is not installed)",
    "docker: needs a local Docker daemon and SWE-bench images (opt in with AGENT_ECC_DOCKER_TESTS=1)",
]