pyproject.toml

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

[project]
name = "adaptloop"
version = "0.1.0"
description = "Event-driven ML adaptation platform: Redpanda ingest of production LLM traces, Bytewax aggregation, PostgreSQL curation, LoRA fine-tuning with MLflow registry."
readme = "README.md"
requires-python = ">=3.11,<3.13"
license = { text = "MIT" }

dependencies = [
    "pydantic>=2.8",
    "pydantic-settings>=2.4",
    "sqlalchemy>=2.0",
    "psycopg[binary]>=3.1",
    "alembic>=1.13",
    "pgvector>=0.3",
    "redis>=5.0",
    "aiokafka>=0.11",
    "bytewax[kafka]>=0.21",
    "confluent-kafka>=2.3",
    "structlog>=24.4",
    "orjson>=3.10",
    "python-dotenv>=1.0",
    "minio>=7.2",
    "pyarrow>=17.0",
    "arq>=0.26",
    "fastapi>=0.115",
    "uvicorn[standard]>=0.30",
    "mlflow>=2.16,<3",
    "httpx>=0.27",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.3",
    "pytest-asyncio>=0.24",
    "ruff>=0.6",
    "mypy>=1.11",
]
training = [
    "torch>=2.2",
    "transformers>=4.44",
    "peft>=0.12",
    "datasets>=2.21",
    "accelerate>=0.33",
]

[project.scripts]
adaptloop-synthetic = "adaptloop.producers.synthetic_epc_producer:main"
adaptloop-bridge = "adaptloop.producers.gateway_trace_bridge:main"
adaptloop-aggregator = "adaptloop.consumers.signal_aggregator:main"
adaptloop-curate = "adaptloop.curation.dataset_builder:main"
adaptloop-train = "adaptloop.training.pipeline:main"
adaptloop-promote = "adaptloop.api.cli:main"
adaptloop-api = "adaptloop.api.serve:main"
adaptloop-canary = "adaptloop.canary.watcher:main"

[tool.hatch.build.targets.wheel]
packages = ["adaptloop"]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "UP", "B", "ASYNC"]

[tool.mypy]
python_version = "3.11"
ignore_missing_imports = true

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