[project]
name = "intern-decision-serve"
version = "0.1.0"
description = "Intern-Decision-4B (its own inference.py) behind semif-serve's HTTP surface"
requires-python = ">=3.12"
dependencies = [
  "fastapi==0.118.0",
  "uvicorn==0.37.0",
]

[project.optional-dependencies]
# The real engine: the 2026-09-30 bench stack (semif-serve 0.1.4's torch/transformers plus what
# the checkpoint's own inference.py imports: PIL and the Qwen3.5 processor, which needs torchvision).
model = [
  "torch==2.10.0",
  "torchvision==0.25.0",
  "transformers==5.17.0",
  "pillow==12.3.0",
]
# Qwen3.5's fast kernels, as in the bench image (without them transformers runs its slower
# reference PyTorch paths, and the bench numbers were measured with them).
fast = [
  "flash-linear-attention==0.5.2",
  "causal-conv1d @ https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.7.0/causal_conv1d-1.7.0+cu12torch2.10cxx11abiTRUE-cp312-cp312-linux_x86_64.whl ; sys_platform == 'linux' and platform_machine == 'x86_64'",
]

[dependency-groups]
dev = ["pytest==8.4.2", "httpx==0.28.1"]

[build-system]
requires = ["setuptools>=68"]
build-backend = "setuptools.build_meta"

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

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

[[tool.uv.index]]
name = "pytorch-cu128"
url = "https://download.pytorch.org/whl/cu128"
explicit = true

[tool.uv.sources]
torch = { index = "pytorch-cu128" }
torchvision = { index = "pytorch-cu128" }

[tool.uv]
# Hold the transitive pins to the 2026-09-30 bench image (semif-serve:0.1.4's lock), so the
# service runs the stack its acceptance numbers are compared against.
constraint-dependencies = ["numpy==2.2.6", "huggingface-hub==1.31.0", "regex==2026.9.10", "tokenizers==0.23.2", "safetensors==0.8.0"]