diff --git a/.github/workflows/mkdocs-build.yml b/.github/workflows/mkdocs-build.yml new file mode 100644 index 0000000..7d0ec2a --- /dev/null +++ b/.github/workflows/mkdocs-build.yml @@ -0,0 +1,11 @@ +name: MkDocs Build (RationAI Standard) +on: + push: + branches: + - main + pull_request: + types: [opened, synchronize, reopened] + +jobs: + run: + uses: RationAI/.github/.github/workflows/mkdocs-build.yml@main diff --git a/README.md b/README.md index 970ada9..bb03b5b 100644 --- a/README.md +++ b/README.md @@ -21,7 +21,7 @@ from PIL import Image client = rationai.Client() # Load an image -image = Image.open("path/to/image.jpg") +image = Image.open("path/to/image.jpg").convert("RGB") # Classify the image result = client.models.classify_image("model-name", image) @@ -58,6 +58,7 @@ asyncio.run(main()) Classify an image using the specified model. **Parameters:** + - `model`: The name of the model to use for classification - `image`: The image to classify (must be uint8 RGB image) - `timeout`: Optional timeout for the request (defaults to 100 seconds) @@ -69,13 +70,13 @@ Classify an image using the specified model. Segment an image using the specified model. **Parameters:** + - `model`: The name of the model to use for segmentation - `image`: The image to segment (must be uint8 RGB image) - `timeout`: Optional timeout for the request (defaults to 100 seconds) **Returns:** Segmentation mask as numpy array with shape `(num_classes, height, width)` - ### Slide (`client.slide`) #### `heatmap(model: str, slide_path: str, tissue_mask_path: str, output_path: str, stride_fraction: float = 0.5, output_bigtiff_tile_height: int = 512, output_bigtiff_tile_width: int = 512, timeout: int = 1000) -> str` @@ -83,6 +84,7 @@ Segment an image using the specified model. Generate a heatmap for a whole slide image using the specified model. **Parameters:** + - `model`: The name of the model to use for heatmap generation - `slide_path`: Path to the whole slide image - `tissue_mask_path`: Path to the tissue mask for the slide @@ -101,6 +103,7 @@ Generate a heatmap for a whole slide image using the specified model. Check quality of a whole slide image. **Parameters:** + - `wsi_path`: Path to the whole slide image - `output_path`: Directory to save output masks - `config`: Optional `SlideCheckConfig` for the quality check @@ -113,6 +116,7 @@ Check quality of a whole slide image. Check quality of multiple slides concurrently. **Parameters:** + - `wsi_paths`: List of paths to whole slide images - `output_path`: Directory to save output masks - `config`: Optional `SlideCheckConfig` for the quality check @@ -126,6 +130,7 @@ Check quality of multiple slides concurrently. Generate a QC report from processed slides. **Parameters:** + - `backgrounds`: List of paths to background (slide) images - `mask_dir`: Directory containing generated masks - `save_location`: Path where the report HTML will be saved @@ -148,16 +153,16 @@ import rationai async def process_images_with_semaphore(image_paths, model_name, max_concurrent): semaphore = asyncio.Semaphore(max_concurrent) - + async def bounded_segment(client, path): async with semaphore: - image = load_image(path) + image = Image.open(path).convert("RGB") return await client.models.segment_image(model_name, image) - + async with rationai.AsyncClient() as client: tasks = [bounded_segment(client, path) for path in image_paths] results = await asyncio.gather(*tasks) - + return results # Process up to 16 images concurrently @@ -174,16 +179,16 @@ from rationai import AsyncClient async def process_with_as_completed(image_paths, model_name, max_concurrent): semaphore = asyncio.Semaphore(max_concurrent) - + async def bounded_request(client, path): async with semaphore: - image = load_image(path) + image = Image.open(path).convert("RGB") return path, await client.models.segment_image(model_name, image) - + async with AsyncClient(models_base_url="http://localhost:8000") as client: - tasks = {asyncio.create_task(bounded_request(client, path)): path + tasks = {asyncio.create_task(bounded_request(client, path)): path for path in image_paths} - + for future in asyncio.as_completed(tasks): path, result = await future print(f"Processed {path}") @@ -192,7 +197,6 @@ async def process_with_as_completed(image_paths, model_name, max_concurrent): asyncio.run(process_with_as_completed(image_paths, "model-name", max_concurrent=16)) ``` - Start with a conservative limit and monitor server resources to find the optimal value for your setup. ## Configuration diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..2894a2c --- /dev/null +++ b/docs/index.md @@ -0,0 +1,44 @@ +# RationAI Python SDK + +Python SDK for interacting with RationAI pathology image analysis services (classification, segmentation, and QC). + +[Quick start](learn/get-started/quick-start.md) + +[How it works](learn/how-it-works.md) + +[API reference](reference/client.md) + +## What you can do + +- Run image classification and segmentation via `client.models`. +- Run quality-control workflows via `client.qc`. +- Choose sync (`Client`) or async (`AsyncClient`) depending on your app. + +## Minimal examples + +### Model example + +```python +from PIL import Image + +import rationai + +image = Image.open("path/to/image.jpg").convert("RGB") + +with rationai.Client() as client: + result = client.models.classify_image("model-name", image) + print(result) +``` + +### QC example + +```python +import rationai + +with rationai.Client() as client: + xopat_url = client.qc.check_slide( + wsi_path="/data/slides/slide.svs", + output_path="/data/qc-output/slide-001", + ) + print(xopat_url) +``` diff --git a/docs/learn/get-started/quick-start.md b/docs/learn/get-started/quick-start.md new file mode 100644 index 0000000..7200266 --- /dev/null +++ b/docs/learn/get-started/quick-start.md @@ -0,0 +1,173 @@ +# Quick start + +## Sync vs Async clients + +This SDK provides two clients: + +- `rationai.Client` (sync): Uses blocking HTTP requests. Best for scripts, notebooks, CLIs, or when your code is already synchronous. +- `rationai.AsyncClient` (async): Uses non-blocking HTTP requests (`await`). Best when you already have an `asyncio` event loop (FastAPI, async workers) or you want to run many requests concurrently. + +Both clients expose the same high-level resources: + +- `client.models` for image classification/segmentation +- `client.qc` for quality control endpoints + +### What’s the actual difference? + +- **Sync** calls (e.g. `client.models.classify_image(...)`) block the current thread until the request completes. +- **Async** calls (e.g. `await client.models.classify_image(...)`) yield control back to the event loop while the network request is in flight, so other tasks can run. + +### Lifecycle (important) + +- Prefer using context managers so connections are closed: + - sync: `with rationai.Client(...) as client: ...` + - async: `async with rationai.AsyncClient(...) as client: ...` +- If you don’t use `with`, call `client.close()` (sync) / `await client.aclose()` (async). + +For details on what is sent over the wire (compression, payloads), see: [How it works](../how-it-works.md). + +## API at a glance + +### Models + +#### `client.models.classify_image` + +Signature: + +`classify_image(model: str, image: PIL.Image.Image | numpy.typing.NDArray[numpy.uint8], timeout=...) -> float | dict[str, float]` + +- `model`: Model name / path appended to `models_base_url`. +- `image`: **uint8 RGB** image (PIL or NumPy array of shape `(H, W, 3)`). +- `timeout`: Optional request timeout (defaults to the client’s timeout). +- Returns: classification result from JSON (often `float` for binary, or `dict[class, prob]`). + +#### `client.models.segment_image` + +Signature: + +`segment_image(model: str, image: PIL.Image.Image | numpy.typing.NDArray[numpy.uint8], timeout=...) -> numpy.typing.NDArray[numpy.float16]` + +- `model`: Model name / path appended to `models_base_url`. +- `image`: **uint8 RGB** image (PIL or NumPy array of shape `(H, W, 3)`). +- `timeout`: Optional request timeout (defaults to the client’s timeout). +- Returns: `float16` NumPy array with shape `(num_classes, height, width)`. + +### Quality control (QC) + +#### `client.qc.check_slide` + +Signature: + +`check_slide(wsi_path: os.PathLike[str] | str, output_path: os.PathLike[str] | str, config: SlideCheckConfig | None = None, timeout=3600) -> str` + +- `wsi_path`: Path to a whole-slide image (evaluated by the QC service). +- `output_path`: Directory where the QC service should write masks (evaluated by the QC service). +- `config`: Optional `SlideCheckConfig` (see reference types). +- `timeout`: Request timeout (default is 3600 seconds). +- Returns: xOpat URL as plain text. + +#### `client.qc.generate_report` + +Signature: + +`generate_report(backgrounds: Iterable[os.PathLike[str] | str], mask_dir: os.PathLike[str] | str, save_location: os.PathLike[str] | str, compute_metrics: bool = True, timeout=...) -> None` + +- `backgrounds`: Iterable of slide/background image paths. +- `mask_dir`: Directory containing generated masks. +- `save_location`: Path where the report HTML should be written. +- `compute_metrics`: Whether to compute aggregated metrics (default: `True`). +- Returns: nothing. + +## Synchronous client + +```python +from PIL import Image +import rationai + +image = Image.open("path/to/image.jpg").convert("RGB") + +with rationai.Client() as client: + result = client.models.classify_image("model-name", image) + print(result) +``` + +## Asynchronous client + +```python +import asyncio +from PIL import Image +import rationai + +image = Image.open("path/to/image.jpg").convert("RGB") + +async def main(): + async with rationai.AsyncClient() as client: + result = await client.models.classify_image("model-name", image) + print(result) + +asyncio.run(main()) +``` + +### Concurrency with the async client + +Use `asyncio` concurrency when you need to process many images. A semaphore is the simplest way to cap concurrency so you don’t overload the server. + +```python +import asyncio +from PIL import Image +import rationai + +async def classify_many(paths: list[str], model: str, *, max_concurrent: int = 8) -> list[float | dict[str, float]]: + sem = asyncio.Semaphore(max_concurrent) + + async def one(client: rationai.AsyncClient, path: str) -> float | dict[str, float]: + async with sem: + image = Image.open(path).convert("RGB") + return await client.models.classify_image(model, image) + + async with rationai.AsyncClient() as client: + return await asyncio.gather(*(one(client, p) for p in paths)) +``` + +## Common pitfalls + +- **PIL image mode**: ensure RGB. + +```python +image = Image.open(path).convert("RGB") +``` + +- **NumPy dtype/shape**: the services expect `uint8` RGB images. + +```python +import numpy as np + +assert arr.dtype == np.uint8 +assert arr.ndim == 3 and arr.shape[2] == 3 +``` + +- **Forgetting to close clients**: prefer `with ...` / `async with ...`. + +- **Too much async concurrency**: cap with a semaphore (start small like 4–16) to avoid server overload/timeouts. + +- **Timeouts**: segmentation/QC can take longer. Increase per-request timeout if needed. + +```python +result = client.models.segment_image("model", image, timeout=300) +``` + +- **QC paths are server-side**: `wsi_path` / `output_path` must exist where the QC service runs. + +## Configuration + +You can override service URLs and timeouts: + +```python +from rationai import Client + +client = Client( + models_base_url="http://localhost:8000", + qc_base_url="http://localhost:8001", + timeout=300, +) +``` diff --git a/docs/learn/how-it-works.md b/docs/learn/how-it-works.md new file mode 100644 index 0000000..d4366df --- /dev/null +++ b/docs/learn/how-it-works.md @@ -0,0 +1,100 @@ +# How it works + +This SDK is a thin client around RationAI services. It does not run ML models locally — it **sends requests** to remote services and returns their responses. + +At a high level: + +- You pass an image (PIL or NumPy) or file paths for QC. +- The SDK builds an HTTP request using `httpx`. +- For model inference, the SDK sends LZ4-compressed raw image bytes. +- It decodes the response into JSON (classification) or a NumPy array (segmentation). + +## Clients and base URLs + +- `rationai.Client` wraps `httpx.Client` (synchronous, blocking I/O) +- `rationai.AsyncClient` wraps `httpx.AsyncClient` (asynchronous, `await`-based) + +Each client holds two service base URLs: + +- `models_base_url`: classification + segmentation endpoints +- `qc_base_url`: quality-control endpoints + +The `client.models` and `client.qc` properties return small resource objects that build requests relative to those base URLs. + +Internally, requests are constructed by joining relative paths onto the configured base URLs (using `httpx.URL(...).join(...)`). + +## Image classification and segmentation + +### What the SDK sends + +For `client.models.classify_image(model, image)` and `client.models.segment_image(model, image)`: + +1. The input `image` is serialized with `image.tobytes()`. +2. The raw bytes are compressed using **LZ4 frame** (`lz4.frame.compress`). +3. The compressed bytes are sent as the raw HTTP request body (binary) using `POST`. + +The request path is literally the `model` string you pass in, joined to `models_base_url`. + +Important: the SDK sends only the raw pixel bytes. It does **not** send image metadata such as width/height/shape, color space, file name, or format. + +### What the SDK expects back + +- **Classification**: JSON (`response.json()`), typically a float (binary) or a mapping of class → probability. +- **Segmentation**: a binary payload (response body) that is LZ4-compressed float16 data. + The SDK decompresses it, interprets it as `np.float16`, and reshapes it to `(num_classes, height, width)`. + +The SDK determines `height` and `width` from the input image: + +- PIL: `image.size` → `(width, height)` +- NumPy: `image.shape[:2]` → `(height, width)` + +So the server response is expected to contain exactly $N \cdot H \cdot W$ float16 values (after decompression), where $N$ is the number of output classes. + +### Input image requirements + +- The server expects an **uint8 RGB** image. +- For NumPy arrays: shape should be `(H, W, 3)` and dtype `uint8`. +- For PIL: ensure it’s RGB (e.g. `image = image.convert("RGB")`). + +Because the SDK sends raw bytes without metadata, the server must already “know” how to interpret the byte stream (expected dtype/channel order). If you send the wrong dtype or channel count/order, you’ll typically get incorrect outputs or server-side errors. + +## Quality control (QC) + +### `check_slide` + +`client.qc.check_slide(wsi_path, output_path, config=...)` sends a JSON payload to the QC service containing: + +- `wsi_path`: path to the WSI +- `output_path`: where masks should be written +- configuration flags from `SlideCheckConfig` + +The SDK retries up to 3 times **only for HTTP 500** responses (using `tenacity`). + +"Paths are evaluated by the server" +`wsi_path` and `output_path` must make sense in the environment where the QC service runs (not necessarily your local machine). + +### `generate_report` + +`client.qc.generate_report(...)` sends a JSON payload to the `/report` endpoint and does not return a value. + +### `check_slides` (async only) + +`await client.qc.check_slides(...)` runs multiple `check_slide` requests concurrently and yields `SlideCheckResult` objects as each finishes. + +- Concurrency is capped by `max_concurrent` (default: 4). +- Exceptions are captured per-slide and returned as `SlideCheckResult(..., success=False, error=str(e))`. + +## Timeouts + +- The client defaults to a global `timeout=100` seconds. +- QC slide checks use a much larger default (`timeout=3600` seconds) because slide processing can take time. + +You can override: + +- global per-client timeout in the client constructor +- per-request timeout in method calls + +## Errors and status codes + +- The SDK calls `response.raise_for_status()` for all endpoints, so non-2xx responses raise `httpx.HTTPStatusError`. +- QC `check_slide` / async `check_slide` are retried only for HTTP 500 (up to 3 attempts with exponential backoff). diff --git a/docs/reference/client.md b/docs/reference/client.md new file mode 100644 index 0000000..c65899d --- /dev/null +++ b/docs/reference/client.md @@ -0,0 +1,9 @@ +# Client + +## `rationai.client.Client` + +::: rationai.client.Client + +## `rationai.client.AsyncClient` + +::: rationai.client.AsyncClient diff --git a/docs/reference/resources/models.md b/docs/reference/resources/models.md new file mode 100644 index 0000000..a83a47d --- /dev/null +++ b/docs/reference/resources/models.md @@ -0,0 +1,9 @@ +# Models + +## `rationai.resources.models.Models` + +::: rationai.resources.models.Models + +## `rationai.resources.models.AsyncModels` + +::: rationai.resources.models.AsyncModels diff --git a/docs/reference/resources/qc.md b/docs/reference/resources/qc.md new file mode 100644 index 0000000..8d7a4a7 --- /dev/null +++ b/docs/reference/resources/qc.md @@ -0,0 +1,9 @@ +# Quality control + +## `rationai.resources.qc.QualityControl` + +::: rationai.resources.qc.QualityControl + +## `rationai.resources.qc.AsyncQualityControl` + +::: rationai.resources.qc.AsyncQualityControl diff --git a/docs/reference/types/qc.md b/docs/reference/types/qc.md new file mode 100644 index 0000000..e8fb289 --- /dev/null +++ b/docs/reference/types/qc.md @@ -0,0 +1,9 @@ +# QC types + +## `rationai.types.qc.SlideCheckConfig` + +::: rationai.types.qc.SlideCheckConfig + +## `rationai.types.qc.SlideCheckResult` + +::: rationai.types.qc.SlideCheckResult diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 0000000..6bb6237 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,59 @@ +site_name: RationAI Python SDK +site_url: https://github.com/RationAI/rationai-sdk-python +repo_url: https://github.com/RationAI/rationai-sdk-python +repo_name: rationai-sdk-python + +nav: + - Home: index.md + - Learn: + - Get started: + - Quick start: learn/get-started/quick-start.md + - How it works: learn/how-it-works.md + - Reference: + - Client: reference/client.md + - Resources: + - Models: reference/resources/models.md + - Quality control: reference/resources/qc.md + - Types: + - QC types: reference/types/qc.md + +theme: + name: material + icon: + repo: fontawesome/brands/gitlab + features: + - content.code.annotate + - content.code.copy + - content.code.select + - navigation.indexes + - navigation.sections + - navigation.tabs + - navigation.tabs.sticky + - navigation.footer + - search.highlight + - search.share + - search.suggest + - toc.follow + +plugins: + - search + - mkdocstrings: + handlers: + python: + options: + show_if_no_docstring: true + +markdown_extensions: + - admonition + - pymdownx.details + - pymdownx.superfences + - pymdownx.highlight + - pymdownx.inlinehilite + - pymdownx.tabbed: + alternate_style: true + - attr_list + - md_in_html + +extra: + version: + provider: mike diff --git a/pyproject.toml b/pyproject.toml index c30a25f..b9a5b95 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,3 +19,10 @@ dependencies = [ [dependency-groups] dev = ["mypy>=1.18.2", "ruff>=0.14.5"] +docs = [ + "mkdocs>=1.6.0", + "mkdocs-material>=9.5.0", + "mkdocstrings[python]>=0.25.0", + "mike>=2.0.0", + "pymdown-extensions>=10.0", +] diff --git a/rationai/resources/__init__.py b/rationai/resources/__init__.py new file mode 100644 index 0000000..7e353d5 --- /dev/null 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