agentopt/pyproject.toml at main · AgentOptimizer/agentopt · GitHub

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[build-system]
requires = ["hatchling<1.22"]
build-backend = "hatchling.build"

[project]
name = "agentopt-py"
version = "0.1.0"
description = "Find the right LLM models for your AI agents — automatic model selection with accuracy/cost/latency tradeoffs"
requires-python = ">=3.10"
license = {text = "Apache-2.0"}
readme = "README.md"
authors = [
    { name = "AgentOptimizer Team" },
]
keywords = ["llm", "model-selection", "agents", "optimization", "pareto"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Typing :: Typed",
]
dependencies = [
    "httpx>=0.24.0",
    "pydantic>=2.0.0",
]

[project.optional-dependencies]
bayesian = ["torch>=2.0.0", "botorch>=0.10.0", "gpytorch>=1.11.0"]
crewai = ["crewai"]
langgraph = ["langchain-openai<1", "langgraph"]
examples = [
    "ag2",
    "crewai",
    "langchain<1",
    "langchain-openai<1",
    "langgraph",
    "llama-index-core",
    "llama-index-llms-openai",
    "openai",
    "openai-agents",
    "python-dotenv",
]
plot = ["matplotlib>=3.5"]
dev = ["pytest>=8.0"]
docs = ["mkdocs-material", "mkdocstrings[python]"]

[project.urls]
Homepage = "https://github.com/AgentOptimizer/agentopt"
Documentation = "https://agentoptimizer.github.io/agentopt"
Repository = "https://github.com/AgentOptimizer/agentopt"

[tool.hatch.build.targets.wheel]
packages = ["src/agentopt"]

[tool.pytest.ini_options]
testpaths = ["tests"]