memorizz/pyproject.toml at main · RichmondAlake/memorizz · GitHub

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

[project]
name = "memorizz"
version = "0.0.46"
description = "A memory management library for Python"
readme = "README.md"
requires-python = ">=3.7"
license = "PolyForm-Noncommercial-1.0.0"
authors = [
    { name = "Richmond Alake", email = "richmond.alake@gmail.com" }
]
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: Other/Proprietary License",
    "Operating System :: OS Independent",
]
dependencies = [
    "openai",
    "numpy",
    "pydantic>=2.0.0",
    "python-dotenv>=0.19.0",
    # Gemma 4 was added to transformers in v5.5.0 (April 2026); huggingface-hub
    # 1.x ships the offline/constants surface transformers 5.x relies on.
    "sentence-transformers>=5.0.0",
    "transformers>=5.5.0",
    "huggingface-hub>=1.0.0",
    "accelerate>=1.0.0",
    "requests>=2.31.0",
]

[project.optional-dependencies]
mongodb = ["pymongo>=4.0.0"]
oracle = ["oracledb>=2.0.0"]
filesystem = ["faiss-cpu>=1.7.4"]
anthropic = ["anthropic>=0.26.0"]
# langchain-ollama 1.x dropped the `timeout=` constructor kwarg; the embedding
# provider has a fallback for it but we still want the ollama daemon SDK at a
# version that knows about Gemma 4 tags (>=0.6.0).
ollama = ["langchain_ollama>=1.0.0", "ollama>=0.6.0"]
voyageai = ["voyageai"]
huggingface = [
    "numpy>=1.21,<2",
    "sentence-transformers>=5.0.0",
    "transformers>=5.5.0",
    "huggingface-hub>=1.0.0",
    "accelerate>=1.0.0",
]
# Apple-MLX backend for native arm64 Macs. mlx-lm has no x86_64 wheels — installs
# will fail under Rosetta. Use a native Apple Silicon Python (arm64).
mlx = [
    "mlx>=0.18.0; platform_system == 'Darwin' and platform_machine == 'arm64'",
    "mlx-lm>=0.20.0; platform_system == 'Darwin' and platform_machine == 'arm64'",
]
docs = [
    "mkdocs>=1.6.0",
    "mkdocs-material>=9.5.0",
    "mkdocstrings[python]>=0.24.0",
    "mkdocs-git-revision-date-localized-plugin>=1.2.0",
    "pymdown-extensions>=10.0",
]
sandbox-e2b = ["e2b-code-interpreter>=1.0"]
sandbox-daytona = ["daytona>=1.0"]
sandbox = ["e2b-code-interpreter>=1.0"]
ui = [
    "fastapi>=0.104.0",
    "uvicorn[standard]>=0.24.0",
    "jinja2>=3.1.0",
    "python-multipart>=0.0.6",
]
ingest-pdf = ["pypdf>=4.0.0"]
all = [
    "anthropic>=0.26.0",
    "pymongo>=4.0.0",
    "oracledb>=2.0.0",
    "langchain_ollama>=1.0.0",
    "ollama>=0.6.0",
    "voyageai",
    "faiss-cpu>=1.7.4",
    "numpy>=1.21,<2",
    "sentence-transformers>=5.0.0",
    "transformers>=5.5.0",
    "huggingface-hub>=1.0.0",
    "accelerate>=1.0.0",
    "fastapi>=0.104.0",
    "uvicorn[standard]>=0.24.0",
    "jinja2>=3.1.0",
    "python-multipart>=0.0.6",
    "e2b-code-interpreter>=1.0",
    "daytona>=1.0",
    "pypdf>=4.0.0",
]

[project.scripts]
memorizz = "memorizz.cli:main"

[tool.hatch.metadata]
allow-direct-references = true

[tool.hatch.build.targets.wheel.sources]
"src" = ""

[tool.hatch.build.targets.wheel.force-include]
"eval/longmemeval/evaluate_memorizz.py" = "eval/longmemeval/evaluate_memorizz.py"
"eval/longmemeval/download_dataset.py" = "eval/longmemeval/download_dataset.py"

[tool.hatch.build.targets.sdist]
exclude = [
    "temp_unpack*",
    "eval/longmemeval/data/**",
    "eval/longmemeval/results/**",
    "longmemeval_evaluation.log",
    "matrix_results*.txt",
    "scenario/**",
    "site/**",
]