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comet-ml--opik/sdks/opik_optimizer/pyproject.toml
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chore: import upstream snapshot with attribution
2026-07-13 13:25:44 +08:00

196 lines
4.5 KiB
TOML

[project]
name = "opik_optimizer"
version = "3.1.1"
description = "Open-source automatic agent and prompt optimization toolkit with Opik"
authors = [
{name = "Comet ML", email = "support@comet.com"}
]
license = {text = "Apache 2.0"}
readme = "README.md"
requires-python = ">=3.10,<3.15"
dependencies = [
"datasets",
"deap>=1.4.3",
"gepa>=0.0.7",
"hf_xet",
# LiteLLM dependency comments:
# - Exclude 1.81.x: HTTP client closed during concurrent calls
# See: https://github.com/BerriAI/litellm/issues/19608
# - Exclude 1.82.7, 1.82.8: compromised in supply chain attack (TeamPCP)
# See: https://docs.litellm.ai/blog/security-update-march-2026
# - Exclude 1.82.*, 1.83.0-1.83.6: CVE-2026-42208 (SQL injection in proxy auth path,
# affects 1.81.16-1.83.6, fixed in 1.83.7).
# See: https://docs.litellm.ai/blog/cve-2026-42208-litellm-proxy-sql-injection
"litellm>=1.79.2,!=1.81.*,!=1.82.*,!=1.83.0,!=1.83.1,!=1.83.2,!=1.83.3,!=1.83.4,!=1.83.5,!=1.83.6",
"mcp>=1.0.0",
"opik>=1.9.7",
"optuna",
"pandas",
"pydantic",
"pyrate-limiter",
"tqdm",
"rich",
"pillow"
]
[project.optional-dependencies]
dev = [
# Test Related
"pytest",
"pytest-cov",
"pytest-xdist",
"pytest-asyncio",
"pytest-env",
"pytest-profiling",
# Pre-commit
"pre-commit",
"radon",
"xenon",
"lizard",
# Test required packages
# "google-adk",
"huggingface-hub",
"langgraph",
"bm25s",
"PyStemmer",
"scikit-learn",
]
benchmarks = [ # Extras - pip install opik_optimizer[benchmarks]
"modal",
"bm25s[full]",
"PyStemmer",
"huggingface-hub",
"ujson",
"pyarrow", # For optimized Parquet format
]
bm25 = [ # Extras - pip install opik_optimizer[bm25]
"bm25s[full]",
"PyStemmer",
"huggingface-hub",
"ujson",
"pyarrow", # For optimized Parquet format
]
[tool.setuptools.packages.find]
where = ["src"]
[tool.setuptools.package-data]
opik_optimizer = ["data/*.json", "data/*.jsonl"]
[project.urls]
Homepage = "https://github.com/comet-ml/opik/blob/main/sdks/opik_optimizer/README.md"
Repository = "https://github.com/comet-ml/opik"
[tool.mypy]
follow_imports = "normal"
ignore_missing_imports = false
disallow_untyped_defs = true
disallow_untyped_calls = true
check_untyped_defs = true
mypy_path = ["typings", "src"]
exclude = "(^|.*/)scripts/benchmarks/"
[[tool.mypy.overrides]]
module = [
"opik.*",
"deap.*",
"litellm.*",
"rich.*",
"pydantic.*",
"optuna.*",
"numpy.*",
"rapidfuzz.*",
"PIL.*",
"datasets.*",
"pyarrow.*",
"gepa.*",
"mcp.*",
"bm25s.*",
"Stemmer.*",
"dsp.*",
"huggingface_hub.*",
"pydantic_ai.*",
"crewai.*",
"langgraph.*",
"agent_framework.*",
"langchain_openai.*",
"google.adk.*",
"google.genai.*",
"opik_optimizer.mcp_utils.*",
]
ignore_missing_imports = true
[[tool.mypy.overrides]]
module = [
"scripts.optimizer_algorithms.*",
"scripts.llm_frameworks.*",
"scripts.archive.*",
"scripts.validation_dataset",
"validation_dataset",
]
ignore_errors = true
[tool.uv]
managed = false
[tool.pytest.ini_options]
filterwarnings = [
"ignore::UserWarning:pydantic.main",
"ignore::pytest.PytestConfigWarning",
"ignore::RuntimeWarning:litellm.integrations.opik.opik",
"ignore:There is no current event loop:DeprecationWarning:litellm._service_logger",
"ignore:Argument ``multivariate`` is an experimental feature.:optuna._experimental",
]
[tool.coverage.run]
branch = true
source = ["opik_optimizer"]
omit = ["opik_optimizer/tests/*"]
[tool.coverage.report]
show_missing = true
skip_covered = true
[tool.ruff]
extend-exclude = ["external"]
[tool.ruff.lint]
select = ["E", "F", "I"] # Enable pycodestyle (E), pyflakes (F), and isort (I)
ignore = ["E402"] # Ignore module level import not at top of file
[tool.ruff.lint.isort]
known-first-party = ["opik_optimizer"]
combine-as-imports = true
[tool.vulture]
min_confidence = 60
paths = ["src", "tests", "scripts", "benchmarks"]
ignore_names = [
"__getattr__",
"_coerce_aliases",
"_normalize",
"DATASET_CONFIG",
"HF_CACHE_HOME",
"HF_DATASETS_CACHE",
"OPTIMIZER_CONFIGS",
"additionalProperties",
"by_alias",
"by_name",
"detail",
"drop_params",
"from_attributes",
"get_optimized_model",
"get_optimized_model_kwargs",
"get_optimized_parameters",
"input_text",
"is_jupyter",
"llm_calls",
"llm_calls_tools",
"make_reflective_dataset",
"model_config",
"pytestmark",
"return_value",
"side_effect",
"strict",
]