Initial implementation of HAG (Hopfield-Augmented Generation)HEADmaster

Core Hopfield retrieval module with energy-based convergence guarantees,
memory bank, FAISS baseline retriever, evaluation metrics, and end-to-end
pipeline. All 45 tests passing on CPU with synthetic data.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

1 files changed, 36 insertions, 0 deletions

diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..24f7806
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,36 @@
+[build-system]
+requires = ["setuptools>=68.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "hag"
+version = "0.1.0"
+requires-python = ">=3.10"
+description = "Hopfield-Augmented Generation: RAG with iterative Modern Hopfield Network retrieval"
+
+dependencies = [
+    "torch>=2.0",
+    "numpy>=1.24",
+    "faiss-cpu>=1.7",
+    "transformers>=4.36",
+    "datasets>=2.14",
+    "pyyaml>=6.0",
+    "tqdm>=4.65",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=7.0",
+    "pytest-cov>=4.0",
+]
+eval = [
+    "scikit-learn>=1.3",
+    "umap-learn>=0.5",
+    "matplotlib>=3.7",
+]
+
+[tool.setuptools.packages.find]
+include = ["hag*"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]