[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "topological-coherence"
version = "0.3.0"
description = "Toroidal topology primitives for LLM coherence research (v7: replication update — inference-time bias null result, prompt hardening effective)"
readme = "README_PYPI.md"
license = "Apache-2.0"
authors = [
{ name = "Sylvain Cormier", email = "sylvain@paraxiom.io" }
]
keywords = [
"attention",
"transformer",
"hallucination",
"topology",
"tonnetz",
"llm",
"machine-learning",
"logit-bias",
"coherence",
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
requires-python = ">=3.9"
dependencies = [
"torch>=2.0.0",
"numpy>=1.21.0",
]
[project.optional-dependencies]
hf = [
"transformers>=4.30.0",
]
demo = [
"gradio>=4.0.0",
]
dev = [
"pytest>=7.0.0",
"black",
"ruff",
]
[project.urls]
Homepage = "https://github.com/Paraxiom/topological-coherence"
Documentation = "https://paraxiom.org/presentations/coherence.html"
Repository = "https://github.com/Paraxiom/topological-coherence"
Paper = "https://doi.org/10.5281/zenodo.18187835"
[tool.hatch.build.targets.wheel]
packages = ["src/topological_coherence"]
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/README.md",
"/README_PYPI.md",
"/LICENSE",
]