diff --git a/.github/copilot-instructions.md b/.github/copilot-instructions.md new file mode 100644 index 00000000..0f5b8e65 --- /dev/null +++ b/.github/copilot-instructions.md @@ -0,0 +1,11 @@ +# KonfAI — GitHub Copilot Instructions + +Follow the canonical repository instructions in `AGENTS.md`. + +- Never commit directly to `main`; always use a focused feature branch. +- Keep each diff small and open a pull request for review. +- Do not merge your own pull request. +- Use Conventional Commits. +- Never include Maestro, Claude, Codex, generated-by/generated-with text, or AI co-author branding in commit messages. +- Run `pixi run format`, `pixi run check`, and relevant pre-commit hooks before finalising. +- Do not introduce dependencies silently or load complete medical imaging datasets into RAM. diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 00000000..a079a611 --- /dev/null +++ b/.github/pull_request_template.md @@ -0,0 +1,48 @@ + + +## Description + + + +## Related issues + + + +## Type of change + +- [ ] `feat` — new feature +- [ ] `fix` — bug fix +- [ ] `perf` — performance improvement +- [ ] `refactor` — no behaviour change +- [ ] `docs` — documentation only +- [ ] `test` — tests only +- [ ] `build` / `ci` / `chore` — tooling, deps, CI +- [ ] Breaking change (describe the migration below) + +## How has this been tested? + + + +```bash +pixi run check +``` + +## Checklist + +- [ ] PR title and commits follow **Conventional Commits** +- [ ] `pixi run check` passes (ruff lint + format + tests) +- [ ] `pixi run --environment dev python -m pytest konfai-apps/tests` passes *(if `konfai-apps/` changed)* +- [ ] Tests added/updated for the change +- [ ] Docs updated *(if user-facing CLI/config behaviour changed)* +- [ ] No new runtime dependency without a matching `pyproject.toml` extra +- [ ] Lazy/patch data access preserved (no full-volume reads added) + +## Breaking changes & migration + + diff --git a/.github/workflows/commit-hygiene.yml b/.github/workflows/commit-hygiene.yml new file mode 100644 index 00000000..eeeecfe6 --- /dev/null +++ b/.github/workflows/commit-hygiene.yml @@ -0,0 +1,53 @@ +name: commit-hygiene + +on: + pull_request: + +permissions: + contents: read + +jobs: + validate-commits: + runs-on: ubuntu-latest + steps: + - name: Check out full history + uses: actions/checkout@v5 + with: + fetch-depth: 0 + + - name: Set up Python + uses: actions/setup-python@v6 + with: + python-version: "3.13" + + - name: Install Commitizen + run: python -m pip install commitizen==4.13.0 + + - name: Validate Conventional Commits + env: + BASE_SHA: ${{ github.event.pull_request.base.sha }} + HEAD_SHA: ${{ github.event.pull_request.head.sha }} + run: cz check --rev-range "${BASE_SHA}..${HEAD_SHA}" + + - name: Reject agent branding + env: + BASE_SHA: ${{ github.event.pull_request.base.sha }} + HEAD_SHA: ${{ github.event.pull_request.head.sha }} + shell: bash + run: | + set -euo pipefail + status=0 + + while IFS= read -r commit; do + message_file="$(mktemp)" + git show --no-patch --format=%B "$commit" > "$message_file" + echo "Checking $(git show --no-patch --format='%h %s' "$commit")" + + if ! python scripts/check_commit_message.py "$message_file"; then + status=1 + fi + + rm -f "$message_file" + done < <(git rev-list --reverse "${BASE_SHA}..${HEAD_SHA}") + + exit "$status" diff --git a/.github/workflows/konfai_ci.yml b/.github/workflows/konfai_ci.yml index 16afc27c..24debc98 100644 --- a/.github/workflows/konfai_ci.yml +++ b/.github/workflows/konfai_ci.yml @@ -5,6 +5,7 @@ on: paths: - ".github/workflows/konfai_ci.yml" - "konfai/**" + - "konfai-apps/**" - "tests/**" - "pyproject.toml" - "README.md" @@ -12,6 +13,7 @@ on: paths: - ".github/workflows/konfai_ci.yml" - "konfai/**" + - "konfai-apps/**" - "tests/**" - "pyproject.toml" - "README.md" @@ -27,7 +29,7 @@ jobs: steps: - uses: actions/checkout@v5 - + - name: Set up Python uses: actions/setup-python@v6 with: @@ -37,7 +39,63 @@ jobs: run: | python -m pip install -U pip pip install -e ".[dev]" - + - name: Run pytest run: | pytest -q tests + + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + + - name: Set up Python + uses: actions/setup-python@v6 + with: + python-version: "3.12" + + - name: Install ruff + run: pip install ruff==0.15.2 + + - name: Run ruff lint + run: ruff check konfai konfai-apps/konfai_apps + + format: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + + - name: Set up Python + uses: actions/setup-python@v6 + with: + python-version: "3.12" + + - name: Install ruff + run: pip install ruff==0.15.2 + + - name: Check formatting + run: ruff format --check konfai konfai-apps/konfai_apps + + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + with: + fetch-depth: 0 + + - name: Set up Python + uses: actions/setup-python@v6 + with: + python-version: "3.12" + + - name: Install build + run: pip install build setuptools-scm + + - name: Build sdist and wheel + run: python -m build --sdist --wheel + + - name: Upload wheel artifact + uses: actions/upload-artifact@v4 + with: + name: konfai-wheel + path: dist/*.whl diff --git a/.github/workflows/pre-commit.yml b/.github/workflows/pre-commit.yml index d8c0c870..6c40c8b9 100644 --- a/.github/workflows/pre-commit.yml +++ b/.github/workflows/pre-commit.yml @@ -1,9 +1,14 @@ name: pre-commit +# Run repository hygiene, Ruff, mypy, and Bandit hooks on pull requests. +# Commit-message hooks are exercised separately by commit-hygiene.yml because +# pre-commit/action runs the pre-commit stage, not the commit-msg stage. on: - push: pull_request: +permissions: + contents: read + jobs: pre-commit: runs-on: ubuntu-latest diff --git a/.gitignore b/.gitignore index eedceb11..5a9abeb5 100644 --- a/.gitignore +++ b/.gitignore @@ -16,3 +16,4 @@ apps/impact_reg apps/impact_seg docs/build/ .codex +docs/_build/ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index ad2b7ad6..c889181f 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,23 +1,41 @@ +exclude: ^(?:\.pixi/|docs/_build/|dist/|.*\.egg-info/) + +default_install_hook_types: + - pre-commit + - commit-msg + +default_stages: + - pre-commit + repos: - - repo: https://github.com/psf/black - rev: 25.1.0 + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.6.0 hooks: - - id: black - args: ["--line-length=120"] + - id: check-added-large-files + - id: check-case-conflict + - id: check-json + - id: check-merge-conflict + - id: check-toml + - id: check-xml + - id: check-yaml + - id: debug-statements + - id: detect-private-key + - id: end-of-file-fixer + exclude: ^apps/mrsegmentator/README\.md$ + - id: mixed-line-ending + exclude: ^apps/mrsegmentator/README\.md$ + - id: trailing-whitespace + args: [--markdown-linebreak-ext=md] + exclude: ^apps/mrsegmentator/README\.md$ - - repo: https://github.com/PyCQA/flake8 - rev: 7.3.0 + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.15.2 hooks: - - id: flake8 - additional_dependencies: - - flake8-bugbear - - pep8-naming - - flake8-builtins - - flake8-comprehensions - args: - - --max-line-length=120 - - --extend-ignore=E203,W503,B006,B008 - + - id: ruff + args: [--fix, --exit-non-zero-on-fix] + files: ^(konfai/|konfai-apps/konfai_apps/|scripts/) + - id: ruff-format + files: ^(konfai/|konfai-apps/konfai_apps/|scripts/) - repo: https://github.com/pre-commit/mirrors-mypy rev: v1.17.0 @@ -25,24 +43,13 @@ repos: - id: mypy additional_dependencies: - types-requests + files: ^konfai/ args: - --ignore-missing-imports - --check-untyped-defs - --install-types - --non-interactive - - repo: https://github.com/asottile/pyupgrade - rev: v3.21.2 - hooks: - - id: pyupgrade - args: ["--py310-plus"] - - - repo: https://github.com/pre-commit/mirrors-isort - rev: v5.10.1 - hooks: - - id: isort - args: ["--profile=black", "--line-length=120"] - - repo: https://github.com/PyCQA/bandit rev: 1.8.6 hooks: @@ -51,3 +58,17 @@ repos: files: ^(konfai/|konfai-apps/konfai_apps/) exclude: ^(tests/|konfai-apps/tests/) pass_filenames: false + + - repo: https://github.com/commitizen-tools/commitizen + rev: v4.13.0 + hooks: + - id: commitizen + stages: [commit-msg] + + - repo: local + hooks: + - id: forbid-agent-commit-branding + name: Forbid AI agent branding in commit messages + entry: python scripts/check_commit_message.py + language: python + stages: [commit-msg] diff --git a/.readthedocs.yaml b/.readthedocs.yaml index a4eb7ecc..1cb9c92d 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -21,4 +21,4 @@ python: install: - requirements: docs/requirements.txt - method: pip - path: . \ No newline at end of file + path: . diff --git a/AGENTS.md b/AGENTS.md new file mode 100644 index 00000000..9f128982 --- /dev/null +++ b/AGENTS.md @@ -0,0 +1,280 @@ +# KonfAI — Agent Guide + +This is the canonical reference for humans and AI agents working on KonfAI. Read it before making changes. For the current code-quality audit and known issues, see [`AUDIT.md`](AUDIT.md). + +## 1. What KonfAI is + +KonfAI is a **modular, extensible, and fully configurable deep-learning framework for medical imaging** (Boussot & Dillenseger, 2025 — arXiv:2508.09823). The central idea: a model, its data pipeline, losses/metrics, optimizers/schedulers, augmentations, post-processing, and the whole train/predict/evaluate workflow are described in **structured YAML config files, without modifying the underlying code**. YAML is mapped onto Python objects by a **reflection engine** (`konfai/utils/config.py`). You describe *what* you want and KonfAI instantiates it; the config doubles as a complete, self-contained, reproducible record of the experiment. + +**Why it exists:** to separate *experimental intent* (the YAML) from *implementation details* (the code), improving reproducibility, transparency, and traceability while still allowing advanced, non-standard workflows that other frameworks (PyTorch Lightning, MONAI, nnU-Net, NiftyNet) make hard. KonfAI has produced top-ranking results in MICCAI challenges (SynthRAD 2025, TrackRAD 2025, CURVAS 2024/2025, PANTHER) across segmentation, registration, and image synthesis. + +**Three design principles** (from the paper): +1. **Declarative configuration** — every component is identified by its Python class path and *all* constructor arguments live in the YAML; the pipeline is reconstructable from config alone (no hardcoded values). +2. **Modularity & controlled extensibility** — interchangeable components (models, losses, transforms, schedulers, augmentations) are instantiated at runtime through a unified registry; each inherits a shared base (`Network`, `Criterion`/loss, `Transform`, …). Extend by subclassing and referencing the new class by path in YAML — no core edits. +3. **Experiment traceability & workspace management** — each experiment lives in a dedicated workspace (config snapshot, logs, predictions, checkpoints, evaluation JSON). + +**Advanced capabilities** it abstracts natively (the reason it's worth the complexity): patch-based learning in **2D / 2.5D / 3D**, **test-time augmentation (TTA)**, **model ensembling**, **deep supervision / multi-head / intermediate-feature access**, and **multi-model setups** (GANs, teacher–student/adversarial). The key enabler is that models declare *every* submodule explicitly via `add_module`, so any layer/head/skip/attention block is **referenceable by name** in YAML (e.g. for a loss, a perceptual feature, or a deep-supervision head) — standard PyTorch `forward()` hides these. + +Two design pillars run through the entire codebase: + +1. **Config-by-reflection.** `apply_config(path)` inspects a callable's signature at call time and recursively builds its arguments from the YAML subtree it owns (`@config("Key")`). Defaults are *materialised back* into the YAML file so a run leaves a fully-resolved config on disk. +2. **Lazy, patch-based imaging.** Volumes are never loaded whole into RAM. Data is read as overlapping patches, optionally streamed chunk-by-chunk, and predictions are reassembled with overlap blending. **Preserving this invariant is mandatory.** + +A third, newer pillar is emerging: + +3. **Declarative models.** Networks are routed module graphs assembled via `add_module` (with `in_branch`/`out_branch` routing metadata). Models can be written as Python classes in `konfai/models/` *or* described entirely in a `.yml` file via the **YAML model builder** (`konfai/utils/model_builder.py`). See §7. + +## 2. Repository layout + +| Path | Role | +|---|---| +| `konfai/` | Core package (config, data, network, workflows, utils) | +| `konfai-apps/` | **Separate** installable package `konfai_apps` (app management, HF repos, FastAPI server) — own `pyproject.toml` | +| `apps/` | Ready-to-use model app bundles (excluded from the `konfai` wheel) | +| `examples/` | Runnable `Segmentation` and `Synthesis` workflows (assume CWD = the example dir) | +| `docs/` | Sphinx documentation site | +| `tests/` | Core test suite (`tests/unit`, `tests/integration`) | +| `konfai-apps/tests/` | Apps test suite (run separately — see §8) | + +### Core package map + +| Module | Role | +|---|---| +| `konfai/utils/config.py` | **The reflection engine.** `Config` context manager + `@config` + `apply_config`. Read before any config change. | +| `konfai/utils/errors.py` | Typed exception hierarchy (`KonfAIError` → `ConfigError`, `TrainerError`, `DatasetManagerError`, …). Use these; do not invent new ones. | +| `konfai/utils/dataset.py` | Storage abstraction. `Dataset` + `AbstractFile` backends (`SitkFile`, `H5File`, `OmeZarrFile`, `DicomFile`) + the `Attribute` geometry sidecar. | +| `konfai/utils/dicom.py` | DICOM series reader/writer (pydicom). | +| `konfai/utils/ome_zarr.py` | OME-Zarr / OME-NGFF reader/writer (zarr; ngff-zarr is a declared but currently *unused* dep — see AUDIT.md). | +| `konfai/utils/ITK.py` | SimpleITK helpers (transform composition, resampling, mask-bbox cropping). | +| `konfai/utils/runtime.py` | `DistributedObject`, distributed setup/teardown, GPU/VRAM, TensorBoard process, logging. | +| `konfai/utils/utils.py` | `SUPPORTED_EXTENSIONS`, `get_module`, patch-slice math, `split_path_spec`. | +| `konfai/data/data_manager.py` | `DataManager`/`DatasetIter`: builds the flat (dataset, augmentation, patch) index, subset/validation selection, DDP sharding, DataLoaders. | +| `konfai/data/patching.py` | `ModelPatch`/`Accumulator`: sliding-window slicing + overlap-blended reassembly; `DatasetManager` per-case cache/stream layer. | +| `konfai/data/transform.py` | Preprocessing/postprocessing transforms (`Normalize`, `Standardize`, `Resample…`, `Mask`, `Crop`, …) + `TransformLoader`. | +| `konfai/data/augmentation.py` | Data augmentation primitives + ADA for DiffusionGAN. | +| `konfai/network/network.py` | `ModuleArgsDict` (routed graph), `Network` (training machinery), `ModelLoader`, `Measure`. The heart of the model system. | +| `konfai/network/blocks.py` | Reusable blocks (`ConvBlock`, `ResBlock`, `Attention`, `Concat`, `get_torch_module`, …). | +| `konfai/utils/model_builder.py` | The declarative YAML→`Network` builder with a safe module registry. | +| `konfai/models/` | Concrete architectures (segmentation, classification, generation, registration, representation). | +| `konfai/metric/measure.py` | `Criterion` hierarchy (losses + metrics) loaded by name from YAML. | +| `konfai/metric/schedulers.py` | Scalar weight schedulers for criteria. | +| `konfai/trainer.py` / `predictor.py` / `evaluator.py` | The `train()` / `predict()` / `evaluate()` pipelines. | +| `konfai/main.py` | CLI: `konfai` → `main()`, `konfai-cluster` → `cluster()`. Subcommands `TRAIN`, `RESUME`, `PREDICTION`, `EVALUATION`. | +| `konfai/__init__.py` | Env-backed directory/state accessors, device utilities. | + +## 3. Architecture in depth + +### 3.1 Config reflection (`konfai/utils/config.py`) +- `@config("Key")` tags a class/callable with the YAML branch it owns (sets `function._key`). +- `apply_config(path)(Cls)()` opens a `Config` on the resolved dot-path, then walks `inspect.signature` params: primitives are coerced, `Path` resolved, `list`/`dict` expanded, and nested `@config` objects recursively instantiated. +- **Reading config mutates it**: resolved defaults are merged back into the YAML file on `Config.__exit__`. A successful run rewrites the active config with all defaults filled in. +- Defaults use the `"default|"` marker; Python `None` round-trips through YAML as the string `"None"`. + +### 3.2 Data pipeline +`Dataset` (`utils/dataset.py`) maps a logical `(group, name)` onto on-disk artefacts via a backend chosen by `file_format`: `h5`→`H5File`, `omezarr`/`ome-zarr`/`zarr`→`OmeZarrFile`, `dicom`→`DicomFile`, anything else→`SitkFile` (`.mha`/`.nii`/npy/xml/vtk/transforms). Geometry travels in an `Attribute` sidecar (`Origin`, `Spacing`, `Direction` + arbitrary metadata). + +`DataManager`/`DatasetIter` (`data/data_manager.py`) build a flat `(x=dataset, a=augmentation, p=patch)` index, apply subset/validation selection, shard across DDP ranks, and feed PyTorch DataLoaders. `DatasetManager`/`ModelPatch`/`Accumulator` (`data/patching.py`) do the patch slicing and overlap-blended reassembly. Transforms (`data/transform.py`) and augmentations (`data/augmentation.py`) are config-bound and run per case. + +**Data convention:** arrays are always **channel-first** `[C, (Z), Y, X]`. Geometry/spacing is **`(x, y, z)`** order (SimpleITK convention). + +### 3.3 Network graph (`konfai/network/network.py`) +- `ModuleArgsDict` is a `torch.nn.Module` whose ordered children each carry routing metadata. `add_module(name, module, in_branch=[...], out_branch=[...], alias=..., ...)` wires a dataflow graph (a string-keyed branch register; branch `'0'` is the implicit input/main path). +- `Network` adds optimizer/scheduler/criterion wiring, patch-based forward, gradient/cross-GPU checkpointing, alias-based state-dict load/save, and loss/metric aggregation via `Measure`. +- `ModelLoader.get_model()` resolves the configured `classpath`: a `.yml`/`.yaml` suffix → YAML builder (§7); otherwise import the class from `konfai.models` and build it via `apply_config`. Non-`Network` classes are wrapped in `MinimalModel`. + +### 3.4 Workflows & runtime +`train()`/`predict()`/`evaluate()` are wrapped by `run_distributed_app` (`utils/runtime.py`), which builds the configured `DistributedObject`, sets the `KONFAI_*` env vars, forces `KONFAI_CONFIG_MODE='Done'`, and spawns one process per GPU (or submits to SLURM via `submitit`). All disk/logging side effects are gated on `global_rank == 0`. + +## 4. Execution flow (end to end) + +``` +CLI (main.py) ─▶ train()/predict()/evaluate() [@run_distributed_app] + └▶ build_*() ─▶ configure_workflow_environment() # sets KONFAI_config_file/ROOT/STATE + dirs + └▶ KONFAI_CONFIG_MODE = 'Done' + └▶ apply_config()(Trainer/Predictor/Evaluator)() # YAML → object graph + └▶ execute_distributed_object() + └▶ mp.spawn → DistributedObject.__call__(rank) + └▶ setup_gpu() → model.init()/init_outputs_group()/_compute_channels_trace() + └▶ DataManager → DataLoader (lazy patches) + └▶ training loop / inference / evaluation +``` + +## 4b. Commands, config files & workspace + +KonfAI is command-driven. Four CLI states map to three YAML config files: + +| Command | Config file | Top-level key | Purpose | +|---|---|---|---| +| `TRAIN` / `RESUME` | `Config.yml` | `Trainer:` | Model + dataset + losses + augmentations + optimizer/schedulers + training params | +| `PREDICTION` | `Prediction.yml` | `Predictor:` | Load model(s), patch/TTA/ensemble inference, `outputs_dataset` post-processing | +| `EVALUATION` | `Evaluation.yml` | `Evaluator:` | Compare predictions vs ground truth, per-case + aggregate metric JSON | + +Each run creates/updates a **workspace** organised by `train_name` (model name): + +``` +Workspace/ + Checkpoints//.pt # checkpoints (BEST or ALL) + Setups//Config_0.yml # full resolved config snapshot + Statistics//events.out.* # TensorBoard logs + Predictions//Dataset/... # predicted volumes + Prediction.yml + Evaluations//Metric_*.json # per-case + aggregate metrics + Evaluation.yml + Dataset//. # input data tree (e.g. CT.mha, MASK.mha) +``` + +### Config anatomy (high-value keys an agent will touch) +- **`Trainer.Model`**: `classpath` (e.g. `segmentation.UNet.UNet` or `UNet.yml`), `Optimizer`, `schedulers`, `outputs_criterions` (loss/metric attached to a **named** module output, e.g. `UNetBlock_0:Head:Softmax`), plus the model's own constructor args. +- **`Dataset`**: `groups_src` → `groups_dest` (each group has `transforms`, `is_input`, `patch_transforms`); `dataset_filenames` (e.g. `./Dataset/:a:mha` — the `:a:`/`:i:` flags mean append/intersect and the suffix is the format); `use_cache`, `batch_size`, `subset`, `validation`, `shuffle`, `inline_augmentations`. +- **`Patch`**: `patch_size`, `overlap`, `extend_slice` (>0 ⇒ 2.5D, requires `patch_size[0]==1`), `pad_value`. +- **`augmentations`**: `DataAugmentation_*` → `data_augmentations` (Flip/Rotate/…); `nb` augmentations per sample. +- **Training params**: `epochs`, `it_validation`, `autocast` (AMP), `gradient_checkpoints`, `gpu_checkpoints`, `ema_decay`, `data_log`, `save_checkpoint_mode` (`BEST`/`ALL`), `EarlyStopping`, `manual_seed`. +- **`Predictor.outputs_dataset`**: per output module, `OutputDataset` with `after_reduction_transforms` (Argmax/…), `final_transforms` (TensorCast), `patch_combine`, `reduction` (TTA: Mean/Median/…), `inverse_transform`; top-level `combine` does model ensembling. +- **`Evaluator.metrics`**: per target group, `targets_criterions` → `criterions_loader` (e.g. `Dice`). + +## 5. Environment variables + +These are process-global state set by `configure_workflow_environment`; accessors in `konfai/__init__.py` read them. + +| Variable | Meaning | +|---|---| +| `KONFAI_config_file` | Path to the active YAML config (note the **lowercase** `config_file` suffix — easy to mistype). Read directly from `os.environ` with no fallback. | +| `KONFAI_CONFIG_MODE` | Config behaviour: `Done` (workflows require this), `default`, `Import` (suppresses `apply_config` side effects during module import), `interactive`, `remove`. **Note:** `interactive`/`remove` are effectively dead in the current product (see AUDIT.md). | +| `KONFAI_ROOT` / `KONFAI_STATE` | Workflow root dir / current `State` (TRAIN/RESUME/PREDICTION/EVALUATION). | +| `KONFAI_CONFIG_PATH` | Hidden channel set by `apply_config`, read back by `PerceptualLoss`. | +| `CUDA_VISIBLE_DEVICES`, `KONFAI_MASTER_PORT`, `KONFAI_CLUSTER`, `KONFAI_OVERWRITE` | Distributed/cluster control. | + +## 6. Imaging formats (DICOM & OME-Zarr) + +Both are first-class dataset backends, dispatched by `file_format` and reachable from config (`SUPPORTED_EXTENSIONS` validates the format). Verified working end-to-end (round-trips, patch reads, geometry): + +- **DICOM** (`utils/dicom.py`): groups by `SeriesInstanceUID`, sorts slices by `ImagePositionPatient` projected on the `ImageOrientationPatient` normal, derives `(origin, spacing(x,y,z), direction(9))`, applies HU rescale, supports header-only metadata + lazy per-slice patch reads, and writes uncompressed series. Geometry round-trips **byte-identically to SimpleITK's GDCM reader**. Caveats: write quantises floats to int16 and always uses the CT SOP class; left-handed directions normalise to right-handed on round-trip (standard DICOM behaviour); multi-frame/enhanced DICOM and irregular slice spacing are not handled. See AUDIT.md. +- **OME-Zarr** (`utils/ome_zarr.py`): a thin adapter over **`ngff-zarr`** (no hand-rolled NGFF parsing) — `ngff_zarr.from_ngff_zarr` for lazy chunk-wise reads, `to_ngff_zarr` for writes; output is `ngff-zarr`-interoperable (verified). **Resolution selection:** a multiscale pyramid level can be chosen per source via the dataset-spec suffix **`omezarr@`** (e.g. `./Dataset:a:omezarr@2` reads pyramid level 2, coarser), parsed by `split_format_level()` and threaded to `OmeZarrFile` — independent of any transform; level 0 (full res) by default. The chosen level's `scale` becomes the KonfAI `Spacing`. Caveat: `Direction` is not representable in NGFF and round-trips only via a proprietary `konfai` group attr; KonfAI's own writer emits a single level (multi-level pyramids come from `ngff_zarr.to_multiscales`). + +## 7. Declarative YAML model builder + +`konfai/utils/model_builder.py` builds a routed `Network` from a `.yml` file (`name`/`parameters`/`network`/`modules`). It is **safe by construction**: node types must come from two curated registries (`_MODULE_REGISTRY` for `nn.Module` factories, `_OBJECT_REGISTRY` for config objects) — no `eval`/import injection. Features: `${param}` exact-string references (preserve Python values), `{$multiply: [...]}`, `{$object: BlockConfig, args: {...}}`, nested graphs, full `add_module` routing. + +`ModelLoader` activates it when `classpath` ends in `.yml`/`.yaml` (resolved relative to `KONFAI_config_file`, or under `konfai_root()/models` for `default|…`). See `examples/Segmentation/UNet.yml`. + +**Status (verified):** the example `UNet.yml` builds a model **identical** to the Python `UNet` (1,934,299 params, matching forward). **It does not yet replace `konfai/models/`:** +- The registry has only 13 module types. Replacing the existing models needs many more (`Linear`, `Add`/`Multiply`, `Attention`, `Upsample`, `View`/`Select`, `LatentDistribution`, norm/activation factories, …) and the enum config objects (`DownsampleMode`/`UpsampleMode`/`NormMode`). +- Roughly 70–80% of `models/` is pure `add_module` wiring (UNet, NestedUNet, ResNet, GAN, VAE) and is migratable once the registry grows. The rest carries genuine Python logic that the builder cannot express: custom `forward`/sampling/training loops in `ddpm`, `diffusionGan`, `cStyleGan`, `registration` (spatial-transformer grid math), `convNeXt` (LayerNorm/DropPath), `representation`. + +So: **the YAML builder complements `models/` today and can replace the feed-forward subset after the registry is expanded.** See AUDIT.md for the migration plan. + +## 7b. How a run actually works (mental model) + +Tracing one config key end-to-end makes the reflection engine concrete. Given `Config.yml`: +```yaml +Trainer: + Model: + classpath: segmentation.UNet.UNet + UNet: + dim: 2 + channels: [1, 32, 64, 128, 256] +``` +1. `train()` → `build_train()` → `configure_workflow_environment()` sets `KONFAI_config_file=Config.yml`, then forces `KONFAI_CONFIG_MODE='Done'`. +2. `apply_config("Trainer")(Trainer)()` opens a `Config` on the `Trainer` subtree and walks `Trainer.__init__`'s signature. The `model: ModelLoader` param (a `@config`-tagged type) is recursively built. +3. `ModelLoader.get_model()` reads `classpath`. No `.yml` suffix → `get_module("segmentation.UNet.UNet", "konfai.models")` imports the class, then `apply_config("Trainer.Model.UNet")(UNet)()` binds `dim`, `channels`, … from the `UNet:` subtree (defaults materialised back into the file). +4. `UNet.__init__` issues `add_module(...)` calls → a routed `ModuleArgsDict` graph. +5. On `Config.__exit__`, the resolved subtree is merged back to `Config.yml` (so the file now records every default). + +Swap `classpath: UNet.yml` and step 3 instead calls `build_model_from_yaml` (§7) — same `add_module` graph, no Python class. + +## 7c. Extending KonfAI (custom components) + +Every extension point is "subclass a base, reference it by class path in YAML" — no core edits. The base classes inherit the config + (for modules) the routing machinery. + +- **Custom model:** subclass `konfai.network.network.Network`; build the graph in `__init__` via `add_module(name, module, in_branch=[...], out_branch=[...])`. Reference with `classpath: my_module.MyNet` (importable) or, for a pure feed-forward graph, write a `.yml` and register any new block via `model_builder.register_module`. +- **Custom loss/metric:** subclass the criterion base in `konfai/metric/measure.py`; `forward` returns a `Tensor` (loss) or a tuple (metric). Reference under `outputs_criterions`/`metrics` by class path, attached to a **named module output** (e.g. `UNetBlock_0:Head:Softmax`). +- **Custom transform:** subclass `konfai.data.transform.Transform`; implement `__call__(name, tensor, cache_attribute)` **and** `transform_shape()` (must predict the output spatial shape exactly — patch planning depends on it). Pair `inverse()` symmetrically if `apply_inverse`. +- **Custom augmentation:** subclass `konfai.data.augmentation.DataAugmentation`; implement `_state_init` (sample params per case index) and `_compute` (apply lazily). Return one shape per input; only `Mask`/`Permute` may change the shape. +- **New imaging format:** add a `Dataset.AbstractFile` backend in `konfai/utils/dataset.py`, dispatch it in `File.__enter__`, and register its aliases in `SUPPORTED_EXTENSIONS` (`utils/utils.py`). Keep the heavy reader lib import-guarded. + +**Routing rules to respect** (`add_module`): branch `'0'` is the implicit input; an `in_branch` must be produced by an earlier module (execution = insertion order, no topo-sort); `out_branch: [-1]` marks a terminal/deep-supervision head; module names must contain no `.`; `alias` lists are positional and load-bearing for pretrained weight remapping. + +## 8. Running things + +### Tests +The dev environment must have the imaging extras installed to exercise the real DICOM/OME-Zarr/ITK paths (the Pixi `dev` env does; a bare `pip install .[dev]` does **not** — see AUDIT.md tooling drift). + +```bash +pixi run test # core unit + integration (tests/) — pytest -q +pixi run --environment dev python -m pytest tests/unit -q # core unit only +pixi run --environment dev python -m pytest konfai-apps/tests # apps suite (NOT run by `pixi run test`) +pixi run test-cov # with coverage +``` + +Baseline (this revision): `tests/unit` 156 passed, `tests/integration` green, `konfai-apps/tests/unit` 25 passed. + +> **Caveat:** root `pytest testpaths=['tests']` excludes `konfai-apps/tests`, so `pixi run test` does **not** run the apps suite. Run it explicitly (the apps CI workflow does). + +### Lint / format / types / build / docs +```bash +pixi run --environment dev lint # ruff check konfai konfai-apps/konfai_apps +pixi run --environment dev format-check # ruff format --check +pixi run --environment dev typecheck # mypy konfai +pixi run --environment dev build # python -m build +pixi run --environment docs build-docs # Sphinx HTML +pixi run check # lint + format-check + test (run before finalising) +``` +(`lint`/`format`/`format-check` exist in both the `dev` and `lint` envs; pass `--environment`.) + +## 9. Optional dependencies + +Install via `pip install konfai[]` or Pixi (the `dev` env bundles the runtime extras; docs deps live in the `docs` env). + +| Extra | Packages | Use | +|---|---|---| +| `itk` | `SimpleITK` | ITK image I/O + transforms | +| `hdf5` | `h5py` | HDF5 datasets | +| `dicom` | `pydicom` | DICOM series backend | +| `omezarr` | `zarr`, `ngff-zarr` | OME-Zarr / NGFF backend | +| `imaging` | `SimpleITK`, `h5py`, `pydicom`, `zarr`, `ngff-zarr` | All imaging backends | +| `monitoring` | `nvidia-ml-py` (imports as `pynvml`) | GPU VRAM monitoring | +| `tensorboard` | `tensorboard` | Training visualisation | +| `vtk` / `lpips` / `cluster` | `vtk` / `lpips` / `submitit` | Mesh I/O / perceptual loss / SLURM | +| `all` | every runtime extra | Full install | +| `dev` | pytest, ruff, build, Sphinx, … | Development | + +> Heavy deps (`SimpleITK`, `h5py`, `pydicom`, `zarr`, `pynvml`, `tensorboard`) are **optional** and import-guarded — code must fail at point-of-use with an install hint, not at import. + +## 10. Invariants — do NOT break these + +- **Never load a full volume into RAM.** Use lazy/patch/streaming access (`can_stream_patch`, `read_data_slice`). +- **Channel-first arrays** `[C,(Z),Y,X]`; **spacing/geometry in `(x,y,z)`** order. `Attribute` geometry keys are `Origin`/`Spacing`/`Direction`. +- **`Attribute` stringifies every value** and reparses geometry via `np.fromstring(s[1:-1], sep=" ")` — only flat scalars/1-D arrays round-trip (nested arrays break; this is a real bug, see AUDIT.md). Read via `__getitem__`/`get_np_array`; do not pre-suffix keys with `_`. +- **`KONFAI_config_file` and `KONFAI_CONFIG_MODE` must be set** before any `Config()`; tests must `monkeypatch.setenv` both. Workflows require `KONFAI_CONFIG_MODE='Done'`. +- **Patch ordering** must match between `disassemble` (read) and `Accumulator` (write); for PREDICTION/EVALUATION, all patches of a case must stay on the same DDP rank. +- **`outputs_criterions` keys** must equal a module's dotted path (e.g. `UNetBlock_0:Head:Argmax`); the `:`/`.` separators are load-bearing. +- **`state_dict` load/save deliberately does not recurse into nested `Network`s** (each owns its optimizer/state); alias lists are positional and load-bearing for pretrained weights. +- **YAML model builder is the trusted-untrusted boundary**: only registry types may be instantiated; module names contain no `.`. +- **Format aliasing**: `ome-zarr`/`ome_zarr`/`zarr` → `omezarr`; keep `SUPPORTED_EXTENSIONS` consistent. +- **`konfai-apps` is a separate package**; `apps/` is excluded from the `konfai` wheel. + +## 11. Coding conventions +- Line length 120 (Ruff). Type annotations on new public functions. Apache-2.0 SPDX header on every new source file. +- No wildcard imports; prefer `pathlib.Path`. Use existing error classes from `konfai/utils/errors.py`. +- Do not import heavy optional deps (`SimpleITK`, `h5py`, `pydicom`, `zarr`) at module top level in code paths that don't need them — guard with `try/except ImportError` + a `_require_*()` helper. + +## 12. Commit conventions +- **Conventional Commits** are enforced in CI (`cz check`): `type(scope): subject` (`feat`, `fix`, `perf`, `docs`, `build`, `ci`, `refactor`, `test`, `chore`). +- A `commit-msg` hook + CI reject AI-agent branding (`maestro`, `claude`, `codex`, "generated by/with") — **avoid these words even in file names referenced in the subject**. +- Imperative present tense, subject < 72 chars. No AI co-author trailers. + +## 13. Rules for AI agents +1. **Read before editing.** Open every file you change. +2. **Keep diffs small.** One logical change per PR; no unrelated reformats. +3. **Run `pixi run check`** (and the apps suite if you touched `konfai-apps`) before finalising. +4. **No new runtime dependencies** without explicit request + matching `pyproject.toml` update (declare the dep in the *same* commit as the code that uses it). +5. **Never load imaging datasets fully into RAM.** +6. **Update docs** when changing user-facing CLI/config behaviour, and update `tests/unit/test_config.py` when changing config binding. +7. **Use existing error types**; do not invent exceptions. +8. **Do not skip pre-commit hooks** with `--no-verify`. + +## 14. Common pitfalls +- `Config.__init__` reads `KONFAI_config_file` straight from `os.environ`; tests must set both env vars via `monkeypatch.setenv`. +- `nvidia-ml-py` imports as `pynvml` — not the same string. +- Format readers (DICOM/OME-Zarr/ITK) live in `konfai/utils/` and are imported by `konfai/data/` — do not move them into `data/`. +- `pixi run test` does not run `konfai-apps/tests`; run them explicitly. +- The pip `[dev]` extra and the Pixi `dev` feature define *different* dev environments (see AUDIT.md) — prefer Pixi for full coverage. +- Reading a config rewrites it on disk (defaults materialised on `Config.__exit__`). diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 00000000..a4067aeb --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,5 @@ +# Claude Context + +This project's primary agent instructions are in `AGENTS.md`. + +@AGENTS.md diff --git a/docs/source/contributing.md b/docs/source/contributing.md index af8a8357..f490d565 100644 --- a/docs/source/contributing.md +++ b/docs/source/contributing.md @@ -95,6 +95,30 @@ When updating the docs: - avoid documenting private helpers unless they are essential extension points - update cross-links when you rename or move pages +## AI-assisted contributions + +KonfAI welcomes contributions from AI coding agents as well as human +contributors. The same quality bar applies: PRs from agents must pass the full +check suite and follow the commit conventions documented in `AGENTS.md` and +`CLAUDE.md` at the repository root. + +Key points for AI agents: + +- **Read `AGENTS.md` first** — it is the canonical reference for conventions, + pitfalls, and rules that apply to automated contributions. +- **Run `pixi run check`** (or `pytest -q tests/ && ruff check konfai`) and + `pixi run pre-commit-run` before finalising any change. Do not open a PR + with failing tests, lint errors, or hook failures. +- **Keep diffs focused** — one logical change per PR. Do not mix unrelated + reformats or refactors with a feature or bug fix. +- **Write a plain-English PR description** that explains what was changed and + why. "Generated by …" or vague commit messages are not acceptable. +- **No new runtime dependencies** without an explicit request from a project + maintainer and a matching `pyproject.toml` update. + +See {doc}`development` for the full developer workflow, including how to run +the test suite and build the documentation. + ## See also - {doc}`architecture` diff --git a/docs/source/development.md b/docs/source/development.md new file mode 100644 index 00000000..36bd8f9f --- /dev/null +++ b/docs/source/development.md @@ -0,0 +1,139 @@ +# Development setup + +This page covers everything needed to contribute to KonfAI or run the test +suite locally. The recommended path uses [Pixi](https://pixi.sh), which +manages Python packages, system libraries, and task runners in a single +reproducible environment. + +## Prerequisites + +- **Python 3.10 or later** — the minimum version declared in `pyproject.toml` +- **Pixi** — install once with: + + ```bash + curl -fsSL https://pixi.sh/install.sh | bash + ``` + + See [pixi.sh](https://pixi.sh) for alternative installers. +- **git** + +## Clone and install + +```bash +git clone https://github.com/vboussot/KonfAI.git +cd KonfAI +pixi install # resolves and installs all Pixi environments +``` + +`pixi install` creates isolated environments under `.pixi/` and does **not** +touch your system Python or any other virtual environment. + +## Available tasks + +Run tasks with `pixi run `: + +| Task | Command | Description | +| --- | --- | --- | +| `test` | `pytest -q tests/` | Run the full test suite | +| `test-cov` | `pytest --cov=konfai tests/` | Run tests with coverage report | +| `lint` | `ruff check konfai konfai-apps/konfai_apps` | Lint the source tree | +| `format` | `ruff format konfai konfai-apps/konfai_apps` | Auto-format source files | +| `format-check` | `ruff format --check ...` | Check formatting without modifying files | +| `typecheck` | `mypy konfai --ignore-missing-imports` | Static type checking | +| `build` | `python -m build` | Build sdist and wheel | +| `check` | lint + format-check + test | Full pre-push gate — run before finishing any change | + +Always run `pixi run check` before pushing or opening a PR. + +## pip fallback + +If Pixi is unavailable, use an editable pip install: + +```bash +pip install -e ".[dev]" +pytest -q tests/ +ruff check konfai +ruff format konfai +``` + +## Pre-commit hooks + +The repository ships a `.pre-commit-config.yaml` with both source-file checks and commit-message validation. Install +both hook types once: + +```bash +# with Pixi: +pixi run pre-commit-install + +# or with pip: +python -m pip install pre-commit +pre-commit install --hook-type pre-commit --hook-type commit-msg +``` + +After installation, `git commit` runs file checks plus Conventional Commit and forbidden-branding validation. Run all +file checks manually with: + +```bash +pre-commit run --all-files +``` + +## Branches, commits, and pull requests + +Never commit directly to `main`. Create a focused feature branch for every change: + +```bash +git switch -c fix/short-description +``` + +Use a Conventional Commit message such as `fix(config): improve YAML validation errors`. Commit messages must not +contain agent names, generated-by/generated-with branding, or AI co-author trailers. The `commit-msg` hooks validate +both the Conventional Commit structure and forbidden branding. + +Before pushing, run `pixi run format`, `pixi run check`, and `pre-commit run --all-files`. Push the feature branch, +open a pull request, and leave it open for a maintainer to review and merge; do not merge your own PR. + +## Writing and running tests + +Tests live under `tests/unit/`. Follow the conventions already established +there: + +- one file per module under test (e.g. `tests/unit/test_config.py`) +- use `pytest` fixtures and `monkeypatch` for environment variables +- never import `SimpleITK` or `h5py` unconditionally — guard with `pytest.importorskip` + +Run a single test file: + +```bash +pixi run test -- tests/unit/test_config.py -v +``` + +## Building the documentation + +The documentation uses Sphinx with the MyST parser for Markdown files. + +Build the HTML output: + +```bash +pixi run -e docs build-docs +``` + +Or in live-reload mode during authoring: + +```bash +pixi run -e docs dev-docs +``` + +Without Pixi: + +```bash +pip install -r docs/requirements.txt +make -C docs html +``` + +The output lands in `docs/_build/html/`. + +## AI agent rules + +If you are an AI agent contributing to this repository, read `AGENTS.md` at +the repository root before making changes. It is the canonical source for branch and PR rules, Conventional Commits, +forbidden commit branding, coding norms, checks, and project-specific pitfalls. diff --git a/docs/source/getting-started/installation.md b/docs/source/getting-started/installation.md index 41382071..2e054b35 100644 --- a/docs/source/getting-started/installation.md +++ b/docs/source/getting-started/installation.md @@ -17,16 +17,29 @@ This installs the core CLI entrypoints: Optional extras exposed by the package metadata: ```bash -python -m pip install "konfai[cluster]" -python -m pip install "konfai[vtk]" -python -m pip install "konfai[lpips]" +python -m pip install "konfai[imaging]" # SimpleITK + h5py (most medical imaging workflows) +python -m pip install "konfai[dicom]" # pydicom — DICOM series reader +python -m pip install "konfai[omezarr]" # zarr + ngff-zarr — OME-Zarr dataset read/write +python -m pip install "konfai[all]" # every optional extra at once +python -m pip install "konfai[dev]" # test, docs, lint, and server tooling ``` -These extras enable optional entrypoints or integrations: - -- `konfai-cluster` with `cluster` -- VTK-dependent features with `vtk` -- LPIPS-based metrics with `lpips` +### Optional extras + +| Extra | Pulls in | Use it for | +| --- | --- | --- | +| `itk` | `SimpleITK` | reading/writing ITK formats (`.mha`, `.nii.gz`, …) | +| `hdf5` | `h5py` | HDF5-backed datasets | +| `imaging` | `SimpleITK`, `h5py` | the common medical-imaging stack (ITK + HDF5) | +| `dicom` | `pydicom` | DICOM series input — see {doc}`../concepts/imaging-formats` | +| `omezarr` | `zarr`, `ngff-zarr` | OME-Zarr / OME-NGFF input — see {doc}`../concepts/imaging-formats` | +| `tensorboard` | `tensorboard` | TensorBoard logging | +| `monitoring` | `nvidia-ml-py` | GPU monitoring | +| `vtk` | `vtk` | VTK-dependent rendering and mesh features | +| `lpips` | `lpips` | LPIPS perceptual metrics | +| `cluster` | `submitit` | `konfai-cluster` job submission | +| `all` | all of the above | install every optional extra at once | +| `dev` | pytest, ruff, sphinx, fastapi, … | local development, tests, docs, and the app server | Install the standalone apps package separately when you need packaged app execution: @@ -41,19 +54,41 @@ This provides: - `konfai-apps-server` - the Python API under `konfai_apps` -## Install from source +## Install with Pixi + +[Pixi](https://pixi.sh) is the recommended tool for reproducible environments +because it pins both Python packages and system libraries. + +Install a released version: -Use an editable install when you want to: +```bash +pixi add konfai +``` -- work on the framework itself -- modify example YAML files -- create local Python modules next to your configs -- build the documentation +Or, for a fully locked development environment from the repository: ```bash git clone https://github.com/vboussot/KonfAI.git cd KonfAI -python -m pip install -e . +pixi install # resolves and installs all environments +pixi run test # run the test suite +pixi run lint # ruff lint the source tree +pixi run check # lint + format-check + test (run before pushing) +``` + +See {doc}`../development` for the full developer workflow and the complete task +list. + +## Install from source (pip) + +Use an editable pip install when Pixi is not available or when you need to +install into an existing environment: + +```bash +git clone https://github.com/vboussot/KonfAI.git +cd KonfAI +python -m pip install -e ".[imaging,dev]" +pytest -q tests/ # verify ``` ## PyTorch and GPU notes diff --git a/pixi.lock b/pixi.lock new file mode 100644 index 00000000..d2498fcf --- /dev/null +++ b/pixi.lock @@ -0,0 +1,5088 @@ +version: 7 +platforms: +- name: linux-64 + virtual-packages: + - __unix=0=0 + - __linux=4.18 + - __glibc=2.28 + - __archspec=0=x86_64 +- name: osx-arm64 + virtual-packages: + - __unix=0=0 + - __osx=13.0 + - __archspec=0=m1 +- name: win-64 + virtual-packages: + - __win=10.0 + - __archspec=0=x86_64 +environments: + default: + channels: + - url: 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45a282cde31d808236fd7ea9d919b128653c8b38b393d1c4ab335c62924d9aba + requires_dist: + - annotated-types>=0.6.0 + - pydantic-core==2.46.4 + - typing-extensions>=4.14.1 + - typing-inspection>=0.4.2 + - email-validator>=2.0.0 ; extra == 'email' + - tzdata ; python_full_version >= '3.9' and sys_platform == 'win32' and extra == 'timezone' + requires_python: '>=3.9' +- pypi: https://files.pythonhosted.org/packages/ff/9a/9afaade874b2fa6c752c36f1548f718b5b83af81ed9b76628329dab81c1b/rfc3986-2.0.0-py2.py3-none-any.whl + name: rfc3986 + version: 2.0.0 + sha256: 50b1502b60e289cb37883f3dfd34532b8873c7de9f49bb546641ce9cbd256ebd + requires_dist: + - idna ; extra == 'idna2008' + requires_python: '>=3.7' diff --git a/pyproject.toml b/pyproject.toml index b54e314e..6e2640c0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,17 +14,29 @@ authors = [ { name = "Valentin Boussot", email = "boussot.v@gmail.com" } ] +keywords = ["deep learning", "medical imaging", "YAML", "configuration", "PyTorch", "reproducibility"] + +classifiers = [ + "Development Status :: 4 - Beta", + "Intended Audience :: Science/Research", + "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", + "Programming Language :: Python :: 3.13", + "Topic :: Scientific/Engineering :: Medical Science Apps.", + "Topic :: Scientific/Engineering :: Artificial Intelligence", +] + dependencies = [ "torch", "tqdm", "numpy", "ruamel.yaml", "psutil", - "tensorboard", - "SimpleITK", "lxml", - "h5py", - "nvidia-ml-py", "requests", "huggingface_hub" ] @@ -40,11 +52,28 @@ konfai = "konfai.main:main" konfai-cluster = "konfai.main:cluster" [project.optional-dependencies] +itk = ["SimpleITK"] +hdf5 = ["h5py"] +monitoring = ["nvidia-ml-py"] +tensorboard = ["tensorboard"] +imaging = ["SimpleITK", "h5py", "pydicom", "zarr", "ngff-zarr"] vtk = ["vtk"] lpips = ["lpips"] cluster = ["submitit"] +dicom = ["pydicom"] +omezarr = ["zarr", "ngff-zarr"] +all = [ + "konfai[itk]", + "konfai[hdf5]", + "konfai[monitoring]", + "konfai[tensorboard]", + "konfai[vtk]", + "konfai[lpips]", + "konfai[cluster]", + "konfai[dicom]", + "konfai[omezarr]" +] dev = [ - "submitit", "fastapi", "uvicorn", "python-multipart", @@ -70,3 +99,128 @@ local_scheme = "no-local-version" [tool.setuptools.packages.find] include = ["konfai*"] exclude = ["apps*"] + +[tool.pixi.workspace] +channels = ["conda-forge"] +platforms = ["linux-64", "osx-arm64", "win-64"] + +[tool.pixi.pypi-dependencies] +konfai = { path = ".", editable = true } + +[tool.pixi.dependencies] +python = ">=3.10,<3.14" +pip = "*" + +[tool.pixi.environments] +default = { solve-group = "default" } +dev = { features = ["dev"], solve-group = "default" } +lint = { features = ["lint"], no-default-feature = true, solve-group = "default" } +docs = { features = ["docs"], no-default-feature = true, solve-group = "default" } + +# --------------------------------------------------------------------------- +# Feature: dev +# --------------------------------------------------------------------------- +[tool.pixi.feature.dev.pypi-dependencies] +pytest = "*" +pytest-cov = "*" +ruff = "==0.15.2" +build = "*" +twine = "*" +mypy = "*" +types-requests = "*" +fastapi = "*" +uvicorn = "*" +python-multipart = "*" +submitit = "*" +SimpleITK = "*" +h5py = "*" +tensorboard = "*" +nvidia-ml-py = "*" +pydicom = "*" +zarr = "*" +ngff-zarr = "*" + +[tool.pixi.feature.dev.tasks] +test = { cmd = "pytest -q tests/", description = "Run the test suite" } +test-cov = { cmd = "pytest --cov=konfai --cov-report=term-missing tests/", description = "Run tests with coverage" } +lint = { cmd = "ruff check konfai konfai-apps/konfai_apps", description = "Lint source code" } +format = { cmd = "ruff format konfai konfai-apps/konfai_apps", description = "Format source code" } +format-check = { cmd = "ruff format --check konfai konfai-apps/konfai_apps", description = "Check formatting without modifying files" } +typecheck = { cmd = "python -m mypy konfai --ignore-missing-imports --no-site-packages", description = "Type-check the konfai package" } +build = { cmd = "python -m build", description = "Build sdist and wheel" } +check = { depends-on = ["lint", "format-check", "test"], description = "Run all quality checks" } + +# --------------------------------------------------------------------------- +# Feature: lint +# --------------------------------------------------------------------------- +[tool.pixi.feature.lint.dependencies] +python = ">=3.10,<3.14" + +[tool.pixi.feature.lint.pypi-dependencies] +ruff = "==0.15.2" +pre-commit = "*" + +[tool.pixi.feature.lint.tasks] +lint = { cmd = "ruff check konfai konfai-apps/konfai_apps", description = "Lint source code" } +format = { cmd = "ruff format konfai konfai-apps/konfai_apps", description = "Format source code" } +format-check = { cmd = "ruff format --check konfai konfai-apps/konfai_apps", description = "Check formatting without modifying files" } +pre-commit-install = { cmd = "pre-commit install --hook-type pre-commit --hook-type commit-msg", description = "Install pre-commit and commit-msg hooks" } +pre-commit-run = { cmd = "pre-commit run --all-files", description = "Run pre-commit hooks on all repository files" } + +# --------------------------------------------------------------------------- +# Feature: docs +# --------------------------------------------------------------------------- +[tool.pixi.feature.docs.dependencies] +python = ">=3.10,<3.14" + +[tool.pixi.feature.docs.pypi-dependencies] +sphinx = ">=7.0" +shibuya = "*" +myst-parser = "*" +sphinx-autodoc-typehints = "*" +sphinx-copybutton = "*" +sphinx-togglebutton = "*" +sphinx-tabs = "*" + +[tool.pixi.feature.docs.tasks] +build-docs = { cmd = "make html", cwd = "docs", description = "Build Sphinx documentation" } +dev-docs = { cmd = "sphinx-autobuild docs/source docs/_build/html", description = "Live-reload docs during development" } + +# --------------------------------------------------------------------------- +# Ruff (replaces black + flake8 + isort) +# --------------------------------------------------------------------------- +[tool.ruff] +line-length = 120 +src = ["konfai", "konfai-apps/konfai_apps"] + +[tool.ruff.lint] +select = ["E", "F", "W", "B", "I", "UP", "C4", "RUF"] +extend-ignore = ["E501", "B006", "B008"] + +[tool.ruff.lint.per-file-ignores] +"tests/**" = ["T20"] + +# --------------------------------------------------------------------------- +# Pytest +# --------------------------------------------------------------------------- +[tool.pytest.ini_options] +testpaths = ["tests"] +addopts = "-q" +markers = [ + "slow: marks tests as slow (deselect with -m 'not slow')", + "integration: marks integration tests", +] + +# --------------------------------------------------------------------------- +# Mypy +# --------------------------------------------------------------------------- +[tool.mypy] +ignore_missing_imports = true +check_untyped_defs = true +python_version = "3.10" + +# --------------------------------------------------------------------------- +# Commitizen +# --------------------------------------------------------------------------- +[tool.commitizen] +name = "cz_conventional_commits" diff --git a/scripts/check_commit_message.py b/scripts/check_commit_message.py new file mode 100644 index 00000000..ce187a0f --- /dev/null +++ b/scripts/check_commit_message.py @@ -0,0 +1,57 @@ +# SPDX-License-Identifier: Apache-2.0 +"""Reject agent branding in Git commit messages.""" + +from __future__ import annotations + +import re +import sys +from collections.abc import Sequence +from pathlib import Path + +FORBIDDEN_PATTERNS: tuple[tuple[str, re.Pattern[str]], ...] = ( + ("Maestro", re.compile(r"\bmaestro\b", re.IGNORECASE)), + ("Claude", re.compile(r"\bclaude\b", re.IGNORECASE)), + ("Codex", re.compile(r"\bcodex\b", re.IGNORECASE)), + ("Generated by", re.compile(r"\bgenerated(?:\s+|-)by\b", re.IGNORECASE)), + ("Generated with", re.compile(r"\bgenerated(?:\s+|-)with\b", re.IGNORECASE)), +) + + +def committed_text(message: str) -> str: + """Return message content after removing Git comment lines.""" + return "\n".join(line for line in message.splitlines() if not line.lstrip().startswith("#")) + + +def forbidden_labels(message: str) -> list[str]: + """Return labels for all forbidden patterns found in the message.""" + text = committed_text(message) + return [label for label, pattern in FORBIDDEN_PATTERNS if pattern.search(text)] + + +def main(argv: Sequence[str] | None = None) -> int: + """Validate the commit message file passed as the first argument.""" + arguments = list(sys.argv[1:] if argv is None else argv) + if len(arguments) != 1: + print("Usage: check_commit_message.py ", file=sys.stderr) + return 2 + + message_path = Path(arguments[0]) + try: + message = message_path.read_text(encoding="utf-8", errors="replace") + except OSError as error: + print(f"Error: cannot read commit message file {message_path}: {error}", file=sys.stderr) + return 2 + + matches = forbidden_labels(message) + if not matches: + return 0 + + print("Error: commit message contains forbidden agent branding:", file=sys.stderr) + for label in matches: + print(f" - {label}", file=sys.stderr) + print("Remove agent names, generated-by text, and AI co-author trailers.", file=sys.stderr) + return 1 + + +if __name__ == "__main__": + raise SystemExit(main())