headroom/pyproject.toml

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

[project]
name = "headroom-ai"
version = "0.3.5"
description = "The Context Optimization Layer for LLM Applications - Cut costs by 50-90%"
readme = "README.md"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
    { name = "Headroom Contributors" }
]
maintainers = [
    { name = "Headroom Contributors" }
]
keywords = [
    "llm",
    "openai",
    "anthropic",
    "claude",
    "gpt",
    "context",
    "token",
    "optimization",
    "compression",
    "caching",
    "proxy",
    "ai",
    "machine-learning",
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: Apache Software License",
    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Software Development :: Libraries :: Python Modules",
    "Typing :: Typed",
]
dependencies = [
    "tiktoken>=0.5.0",
    "pydantic>=2.0.0",
    "openai>=2.14.0",
    "sentence-transformers>=5.2.0",
    "litellm>=1.0.0",
    "accelerate>=1.12.0",
    "sentencepiece>=0.2.1",
    "protobuf>=6.33.4",
    "semantic-router>=0.1.12",
    "pillow>=10.0.0",             # Image processing for compression
    "datasets>=4.5.0",
    "hnswlib>=0.8.0",             # HNSW vector index for memory system
    "click>=8.1.0",               # CLI framework
    "rich>=13.0.0",               # Rich terminal output
]

[project.optional-dependencies]
# Semantic relevance scoring with embeddings
relevance = [
    "sentence-transformers>=2.2.0",
    "numpy>=1.24.0",
]
# Proxy server
proxy = [
    "fastapi>=0.100.0",
    "uvicorn>=0.23.0",
    "httpx[http2]>=0.24.0",  # http2 extra enables h2 for HTTP/2 support
]
# Report generation
reports = [
    "jinja2>=3.0.0",
]
# ML-based compression (LLMLingua-2)
llmlingua = [
    "llmlingua>=0.2.0",
    "torch>=2.0.0",
    "transformers>=4.30.0",
]
# AST-based code compression (tree-sitter)
code = [
    "tree-sitter-language-pack>=0.10.0",
]
# Agno agent framework integration
agno = [
    "agno>=1.0.0",
]
# AWS Strands Agents SDK integration
strands = [
    "strands-agents>=0.1.0",
]
# MCP server for Claude Code integration (CCR without API access)
mcp = [
    "mcp>=1.0.0",
    "httpx>=0.24.0",
]
# Voice filler detection (training and inference)
voice = [
    "onnxruntime>=1.16.0",       # Fast CPU inference
    "transformers>=4.30.0",      # Model loading and tokenization
    "torch>=2.0.0",              # Training
]
# Voice training only (includes voice deps + training extras)
voice-train = [
    "headroom-ai[voice]",
    "datasets>=2.14.0",          # Data loading
    "accelerate>=0.20.0",        # Training acceleration
]
# Evaluation framework for testing compression accuracy
evals = [
    "datasets>=2.14.0",           # HuggingFace datasets
    "sentence-transformers>=2.2.0", # Semantic similarity
    "numpy>=1.24.0",              # Numerical operations
    "scikit-learn>=1.3.0",        # ML metrics
    "anthropic>=0.18.0",          # Anthropic API for evals
    "openai>=1.0.0",              # OpenAI API for evals
]
# Memory system extras (hierarchical memory with vector search)
memory = [
    "hnswlib>=0.8.0", # HNSW vector index for semantic search
    "sqlite-vec>=0.1.6",
]
# AWS Bedrock backend
bedrock = [
    "boto3>=1.28.0",
]
# HTML content extraction (web scraping results)
html = [
    "trafilatura>=1.6.0",
]
# Comprehensive LLM benchmarks (EleutherAI lm-evaluation-harness)
benchmark = [
    "lm-eval>=0.4.0",
    "openai>=1.0.0",
    "anthropic>=0.18.0",
]
# Development dependencies
dev = [
    "pytest>=7.0.0",
    "pytest-cov>=4.0.0",
    "pytest-asyncio>=0.21.0",
    "ruff>=0.1.0",
    "mypy>=1.0.0",
    "pre-commit>=3.0.0",
    "openai>=1.0.0",
    "anthropic>=0.18.0",
    "ollama>=0.4.0",  # For Ollama integration tests (local LLM, no API key needed)
    "langchain-ollama>=0.2.0",  # For LangChain+Ollama integration tests
    "hnswlib>=0.8.0",  # For memory system tests
]
# All optional dependencies
all = [
    "headroom-ai[relevance,proxy,reports,llmlingua,code,evals,memory,voice,html,benchmark,mcp]",
]

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

[project.urls]
Homepage = "https://github.com/chopratejas/headroom"
Documentation = "https://github.com/chopratejas/headroom#readme"
Repository = "https://github.com/chopratejas/headroom"
Issues = "https://github.com/chopratejas/headroom/issues"
Changelog = "https://github.com/chopratejas/headroom/blob/main/CHANGELOG.md"

[tool.hatch.build.targets.wheel]
packages = ["headroom"]
# Include non-Python files (dashboard templates, etc.)
artifacts = [
    "headroom/dashboard/templates/*.html",
]

[tool.hatch.build.targets.sdist]
include = [
    "/headroom",
    "/tests",
    "/LICENSE",
    "/NOTICE",
    "/README.md",
    "/CHANGELOG.md",
]

[tool.ruff]
target-version = "py310"
line-length = 100

[tool.ruff.lint]
select = [
    "E",   # pycodestyle errors
    "W",   # pycodestyle warnings
    "F",   # pyflakes
    "I",   # isort
    "B",   # flake8-bugbear
    "C4",  # flake8-comprehensions
    "UP",  # pyupgrade
]
ignore = [
    "E501",  # line too long (handled by formatter)
    "B008",  # do not perform function calls in argument defaults
    "B905",  # zip without strict parameter
    "UP038", # isinstance(x, (A, B)) is clearer than isinstance(x, A | B)
]

[tool.ruff.lint.isort]
known-first-party = ["headroom"]

[tool.ruff.format]
quote-style = "double"
indent-style = "space"

[tool.mypy]
python_version = "3.10"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
ignore_missing_imports = true

# Per-module overrides for modules with dynamic typing patterns
[[tool.mypy.overrides]]
module = [
    "headroom.proxy.server",
    "headroom.integrations.langchain",
    "headroom.integrations.mcp",
    "headroom.ccr.mcp_server",
    "headroom.relevance.embedding",
    "headroom.reporting.generator",
]
disallow_untyped_defs = false

[[tool.mypy.overrides]]
module = [
    "headroom.tokenizers.*",
    "headroom.providers.litellm",
    "headroom.providers.google",
]
disallow_untyped_defs = false
warn_return_any = false

# Ignore third-party stubs with syntax errors
[[tool.mypy.overrides]]
module = ["mlx.*"]
ignore_errors = true

[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
python_functions = ["test_*"]
addopts = "-v --tb=short"
asyncio_mode = "auto"

[tool.coverage.run]
source = ["headroom"]
branch = true
omit = [
    "headroom/cli.py",
    "*/tests/*",
]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "def __repr__",
    "raise NotImplementedError",
    "if TYPE_CHECKING:",
    "if __name__ == .__main__.:",
]