# SPDX-FileCopyrightText: 2025-2026 CodeNib Contributors
#
# SPDX-License-Identifier: Apache-2.0

[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "codenib"
version = "0.2.5"
description = "A multi-view data system for serving repository context to coding agents"
readme = "README.md"
requires-python = ">=3.10"
license = "Apache-2.0"
authors = [{ name = "Zhongming Yu", email = "zhy025@ucsd.edu" }]
keywords = [
    "code-search",
    "coding-agents",
    "model-context-protocol",
    "repository-context",
    "static-analysis",
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "Programming Language :: Python :: 3 :: Only",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Programming Language :: Python :: 3.14",
    "Operating System :: OS Independent",
    "Topic :: Software Development",
    "Topic :: Software Development :: Libraries :: Python Modules",
]
dependencies = [
    "fastapi>=0.100.0",
    "filelock>=3.0.0",
    "pydantic>=2.0.0",
    "pyyaml>=6.0",
    "rank_bm25>=0.2.2",
    "regex>=2024.11.6",
    "rich>=14.0.0",
    "tree-sitter>=0.25.2",
    "tree-sitter-language-pack>=1.8.1,<1.9.0",
    "uvicorn>=0.20.0",
]

[project.urls]
Documentation = "https://docs.codenib.ai/"
Homepage = "https://codenib.ai"
Issues = "https://github.com/sysevol-ai/CodeNib/issues"
Repository = "https://github.com/sysevol-ai/CodeNib.git"

[project.scripts]
codenib = "codenib.cli:main"
codenib-mcp = "codenib._optional_entrypoints:mcp_main"
codenib-web = "codenib.web.app:main"
codenib-lsp-provider-validate = "codenib._optional_entrypoints:lsp_provider_validate_main"
codenib-lsp-replay-benchmark = "codenib._optional_entrypoints:lsp_replay_benchmark_main"
codenib-prebuilt-normalize-graphs = "codenib._optional_entrypoints:prebuilt_normalize_graphs_main"
codenib-lsp-agent-ab = "codenib._optional_entrypoints:lsp_agent_ab_main"
codenib-lsp-provider-protocol-check = "codenib._optional_entrypoints:lsp_agent_ab_main"
codenib-lsp-agent-study-manifest = "codenib._optional_entrypoints:lsp_agent_study_manifest_main"
codenib-lsp-agent-study-artifacts = "codenib._optional_entrypoints:lsp_agent_study_artifacts_main"
codenib-lsp-agent-study-run = "codenib._optional_entrypoints:lsp_agent_study_run_main"
codenib-artifact-bundle = "codenib.eval.artifact_bundle:main"
codenib-swe-explore-benchmark = "codenib.eval.benchmarks.swe_explore_runner:main"
codenib-contextbench = "codenib._optional_entrypoints:contextbench_main"
codenib-arb = "codenib._optional_entrypoints:arb_main"
codenib-quality-cost-report = "codenib.eval.reports.quality_cost:main"
codenib-serve = "codenib._optional_entrypoints:serving_main"

[project.optional-dependencies]
auth = [
    "keyring>=25.0.0",
    "requests>=2.25.0",
]
grep = [
    "requests>=2.25.0",
    "ripgrep-bin>=15.2.0,<16",
]
# LiteLLM imports its MCP gateway while dispatching ordinary function tools.
# Select its coupled transport dependencies instead of relying on a test extra.
agent = [
    "litellm[mcp]>=1.93.0",
    "openai>=1.0.0",
    "requests>=2.25.0",
]
datasets = [
    "datasets>=4.0.0",
]
graph = [
    "igraph>=0.11.6",
    "protobuf>=3.20.0",
]
mcp = [
    "mcp>=2.0.0,<3",
]
semantic = [
    "einops>=0.8.0",
    "faiss-cpu>=1.7.0",
    "numpy>=1.24.0",
    "openai>=1.0.0",
    "sentence-transformers>=2.3.0",
    # The pinned CodeRankEmbed model calls get_extended_attention_mask,
    # removed in Transformers 5.17. Keep full/test aligned with this bound.
    "transformers<5.17",
]
semantic-remote = [
    "faiss-cpu>=1.7.0",
    "numpy>=1.24.0",
    "openai>=1.0.0",
]
# Speculative serving (``codenib-serve``). fastapi/uvicorn/pydantic are already
# core dependencies, so this only adds the streaming transport and the model
# runtime. Deliberately kept out of `full`: torch would make the aggregate
# extra multi-gigabyte for users who only want retrieval.
serving = [
    "numpy>=1.24.0",
    "sse-starlette>=2.0.0",
    "torch>=2.2.0",
    "transformers>=5.15.0",
]
# Vertex AI backends (``vertex_ai/...`` model strings, via gcloud ADC).
# Keep the provider SDK coupled to LiteLLM's own compatibility constraint
# instead of maintaining a second, looser google-cloud-aiplatform pin here.
vertex = [
    "litellm[google,mcp]>=1.93.0",
]
zoekt = [
    "requests>=2.25.0",
]
full = [
    "datasets>=4.0.0",
    "einops>=0.8.0",
    "faiss-cpu>=1.7.0",
    "igraph>=0.11.6",
    "litellm[google,mcp]>=1.93.0",
    "mcp>=2.0.0,<3",
    "numpy>=1.24.0",
    "openai>=1.0.0",
    "protobuf>=3.20.0",
    "requests>=2.25.0",
    "sentence-transformers>=2.3.0",
    "transformers<5.17",
]
dev = [
    "black>=22.3.0",
    "build>=1.2.0",
    "isort>=5.10.1",
    "mypy>=0.950",
    "flake8>=4.0.1",
    "flake8-bugbear>=24.4.0",
    # Docs. Keep this list in sync with the `docs` dependency group below.
    # MkDocs 2.0 drops the plugin system with no migration path, which would
    # take mkdocstrings and api-autonav with it.
    "mkdocs<2.0.0",
    "mkdocs-material>=9.5.0",
    "mkdocstrings-python>=2.0.0",
    "mkdocs-api-autonav>=0.4.0",
]
test = [
    "datasets>=4.0.0",
    "einops>=0.8.0",
    "faiss-cpu>=1.7.0",
    "igraph>=0.11.6",
    "litellm[mcp]>=1.93.0",
    "matplotlib>=3.4.0",
    "mcp>=2.0.0,<3",
    "numpy>=1.24.0",
    "openai>=1.0.0",
    "protobuf>=3.20.0",
    "pytest>=6.0.0",
    "pytest-cov>=3.0.0",
    "pytest-timeout>=2.1.0",
    "pytest-xdist>=3.0.0",
    "requests>=2.25.0",
    "sentence-transformers>=2.3.0",
    # Lets the serving endpoint tests run in the default tier; tests that
    # exercise the model runtime are marked `slow`.
    "sse-starlette>=2.0.0",
    "tomli>=1.1.0; python_version < '3.11'",
    "transformers<5.17",
]

[dependency-groups]
# CI installs only this group for the static documentation build. Keep the
# matching packages in the published `dev` extra for `make dev` users.
docs = [
    "black>=22.3.0",
    "mkdocs<2.0.0",
    "mkdocs-material>=9.5.0",
    "mkdocstrings-python>=2.0.0",
    "mkdocs-api-autonav>=0.4.0",
]

[tool.setuptools]
include-package-data = true

[tool.setuptools.packages.find]
where = ["."]  # list of folders that contain the packages (["."] by default)
include = ["codenib*"]  # package names should match these glob patterns (["*"] by default)
exclude = ["eval*"]  # exclude packages matching these glob patterns

[tool.setuptools.package-data]
"codenib.agent" = ["*.cjs"]
"codenib.agent.skills" = ["*/config.yaml", "*/skill.md"]
"codenib.eval" = ["pricing/*.json"]
"codenib.scip_interface" = ["*.proto", "*.yml", "*.sh", "README.md"]

[tool.pytest.ini_options]
testpaths = ["test"]
pythonpath = ["."]
norecursedirs = [
    "third_party",
    ".git",
    ".cache",
    ".mypy_cache",
    ".pytest_cache",
    ".venv",
    "venv",
    "env",
    "build",
    "dist",
]
markers = [
    "slow: marks tests that need LLM API, GPU, or HuggingFace downloads (deselect with '-m \"not slow\"')",
    "integration: marks tests that use external repos but are read-only / parallel-safe (chunkers, fixture-based SCIP)",
    "integration_serial: marks tests that mutate shared repos (process_instance, git checkout/apply) and must run sequentially",
    "integration_serial_consumer: marks tests that consume graph.pkl written by integration_serial (run in a separate job after integration-serial via job-level needs, mirroring scip-core)",
]

[tool.black]
line-length = 88
target-version = ["py310"]
extend-exclude = '''
/(
    build
  | dist
  | third_party
  | docs/_build
  | .*\.egg-info
)/
'''