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pyproject.toml
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59 lines (55 loc) · 2 KB
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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "sre-engineer-llm"
version = "3.1.0"
description = "Tier-escalating SRE training environment. Basic ships 12 base templates with 5 procgen variants each (72 scenarios) as a runnable RL env; Advanced and Max ship as runnable Python orchestrators that approximate larger designs documented in their YAMLs. Training pipeline ships runnable in notebooks/01 but is not yet executed in this repo. See README.md and docs/ARCHITECTURE.md for the full state."
readme = "README.md"
requires-python = ">=3.10"
dependencies = [
"openenv-core>=0.2.1",
"fastapi>=0.115.0",
"uvicorn[standard]>=0.30.0",
"pydantic>=2.8.0",
"httpx>=0.27.0",
"openai>=1.0.0",
"websockets>=12.0",
"rich>=13.0.0",
"matplotlib>=3.9.0",
"numpy>=2.0.0",
"pyyaml>=6.0",
"pandas>=2.0.0"
]
[project.optional-dependencies]
dev = [
"pytest>=8.0.0",
"pytest-asyncio>=0.23.0"
]
train = [
"datasets>=3.0",
"transformers>=4.46",
"peft>=0.13",
"accelerate>=1.1",
"trl>=0.12.0",
"anthropic>=0.40.0"
]
[project.scripts]
server = "server.app:main"
baseline = "unified_incident_env.scripts.baseline_agent:main"
walkthrough = "unified_incident_env.scripts.walkthrough:main"
trainer-run-episode = "unified_incident_env.trainer.run_episode:main"
trainer-build-dataset = "unified_incident_env.trainer.build_sft_dataset:main"
trainer-eval-models = "unified_incident_env.trainer.eval_models:main"
trainer-build-datasets = "unified_incident_env.trainer.build_datasets:main"
trainer-update-model = "unified_incident_env.trainer.update_model:main"
trainer-run-session = "unified_incident_env.trainer.run_session:main"
trainer-train-external = "unified_incident_env.trainer.train_external:main"
[tool.hatch.build.targets.wheel]
packages = ["sre_gym", "unified_incident_env", "server"]
include = [
"sre_gym/advanced/scenarios/*.yaml",
"sre_gym/max/families/*.yaml",
"sre_gym/max/chaos/*.yaml",
"sre_gym/max/compose/*.yaml",
]