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merged 4 commits into from
Nov 19, 2025
Merged

Feat/custom pipeline #267

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5fef607
feat(platform,application): configureable pipeline
helmut-hoffer-von-ankershoffen Nov 19, 2025
35b5f56
test(application): reactivate test_cli_run_submit_and_describe_and_ca…
helmut-hoffer-von-ankershoffen Nov 19, 2025
c55a75d
chore(deps): some
helmut-hoffer-von-ankershoffen Nov 19, 2025
589e683
refactor(application): dry
helmut-hoffer-von-ankershoffen Nov 19, 2025
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14 changes: 7 additions & 7 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ requires-python = ">=3.11, <3.14"

dependencies = [
# From Template
"fastapi[standard,all]>=0.121.1,<1",
"fastapi[standard,all]>=0.121.3,<1",
"humanize>=4.14.0,<5",
"nicegui[native]>=3.1.0,<3.2.0", # Regression in 3.2.0
"packaging>=25.0,<26",
Expand All @@ -83,24 +83,24 @@ dependencies = [
"pydantic-settings>=2.12.0,<3",
"pywin32>=310,<311 ; sys_platform == 'win32'",
"pyyaml>=6.0.3,<7",
"sentry-sdk>=2.44.0,<3",
"sentry-sdk>=2.45.0,<3",
"typer>=0.20.0,<1",
"uptime>=3.0.1,<4",
# Custom
"aiopath>=0.6.11,<1",
"boto3>=1.40.61,<2",
"boto3>=1.41.0,<2",
"certifi>=2025.11.12,<2026",
"defusedxml>=0.7.1",
"dicom-validator>=0.7.3,<1",
"dicomweb-client[gcp]>=0.59.3,<1",
"duckdb>=0.10.0,<=1.4.1",
"fastparquet>=2024.11.0,<2025",
"google-cloud-storage>=3.5.0,<4",
"google-cloud-storage>=3.6.0,<4",
"google-crc32c>=1.7.1,<2",
"highdicom>=0.26.1,<1",
"html-sanitizer>=2.6.0,<3",
"httpx>=0.28.1,<1",
"idc-index-data==22.1.2",
"idc-index-data==22.1.5",
"ijson>=3.4.0.post0,<4",
"jsf>=0.11.2,<1",
"jsonschema[format-nongpl]>=4.25.1,<5",
Expand Down Expand Up @@ -131,7 +131,7 @@ jupyter = ["jupyter>=1.1.1,<2"]
marimo = [
"cloudpathlib>=0.23.0,<1",
"ipython>=9.7.0,<10",
"marimo>=0.17.7,<1",
"marimo>=0.17.8,<1",
"matplotlib>=3.10.7,<4",
"shapely>=2.1.0,<3",
]
Expand Down Expand Up @@ -165,7 +165,7 @@ dev = [
"pytest-timeout>=2.4.0,<3",
"pytest-watcher>=0.4.3,<1",
"pytest-xdist[psutil]>=3.8.0,<4",
"ruff>=0.14.4,<1",
"ruff>=0.14.5,<1",
"scalene>=1.5.55,<2",
"sphinx>=8.2.3,<9",
"sphinx-autobuild>=2025.8.25,<2026",
Expand Down
54 changes: 53 additions & 1 deletion src/aignostics/application/_cli.py
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Original file line number Diff line number Diff line change
Expand Up @@ -366,6 +366,22 @@ def run_execute( # noqa: PLR0913, PLR0917
validate_only: Annotated[
bool, typer.Option(help="If True, cancel the run post validation, before analysis.")
] = False,
gpu_type: Annotated[
str,
typer.Option(help="GPU type to use for processing (L4 or A100)."),
] = "A100",
gpu_provisioning_mode: Annotated[
str,
typer.Option(help="GPU provisioning mode (SPOT or ON_DEMAND)."),
] = "ON_DEMAND",
max_gpus_per_slide: Annotated[
int,
typer.Option(help="Maximum number of GPUs to allocate per slide (1-8).", min=1, max=8),
] = 1,
cpu_provisioning_mode: Annotated[
str,
typer.Option(help="CPU provisioning mode (SPOT or ON_DEMAND)."),
] = "ON_DEMAND",
) -> None:
"""Prepare metadata, upload data to platform, and submit an application run, then incrementally download results.

Expand Down Expand Up @@ -401,10 +417,15 @@ def run_execute( # noqa: PLR0913, PLR0917
metadata_csv_file=metadata_csv_file,
application_version=application_version,
note=note,
tags=None,
due_date=due_date,
deadline=deadline,
onboard_to_aignostics_portal=onboard_to_aignostics_portal,
validate_only=validate_only,
gpu_type=gpu_type,
gpu_provisioning_mode=gpu_provisioning_mode,
max_gpus_per_slide=max_gpus_per_slide,
cpu_provisioning_mode=cpu_provisioning_mode,
)
result_download(
run_id=run_id,
Expand Down Expand Up @@ -652,6 +673,22 @@ def run_submit( # noqa: PLR0913, PLR0917
validate_only: Annotated[
bool, typer.Option(help="If True, cancel the run post validation, before analysis.")
] = False,
gpu_type: Annotated[
str,
typer.Option(help="GPU type to use for processing (L4 or A100)."),
] = "A100",
gpu_provisioning_mode: Annotated[
str,
typer.Option(help="GPU provisioning mode (SPOT or ON_DEMAND)."),
] = "ON_DEMAND",
max_gpus_per_slide: Annotated[
int,
typer.Option(help="Maximum number of GPUs to allocate per slide (1-8).", min=1, max=8),
] = 1,
cpu_provisioning_mode: Annotated[
str,
typer.Option(help="CPU provisioning mode (SPOT or ON_DEMAND)."),
] = "ON_DEMAND",
) -> str:
"""Submit run by referencing the metadata CSV file.

Expand Down Expand Up @@ -701,11 +738,26 @@ def run_submit( # noqa: PLR0913, PLR0917
app_version.version_number,
metadata_dict,
)

# Build custom metadata with pipeline configuration
custom_metadata = {
"pipeline": {
"gpu": {
"gpu_type": gpu_type,
"provisioning_mode": gpu_provisioning_mode,
"max_gpus_per_slide": max_gpus_per_slide,
},
"cpu": {
"provisioning_mode": cpu_provisioning_mode,
},
},
}

application_run = Service().application_run_submit_from_metadata(
application_id=application_id,
metadata=metadata_dict,
application_version=application_version,
custom_metadata=None, # TODO(Helmut): Add support for custom metadata
custom_metadata=custom_metadata,
note=note,
tags={tag.strip() for tag in tags.split(",") if tag.strip()} if tags else None,
due_date=due_date,
Expand Down
101 changes: 98 additions & 3 deletions src/aignostics/application/_gui/_page_application_describe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,9 @@
WIDTH_1200px = "width: 1200px; max-width: none"
MESSAGE_METADATA_GRID_IS_NOT_INITIALIZED = "Metadata grid is not initialized."

CLASS_SUBSECTION_HEADER = "text-h6 mb-0 pb-0"
CLASS_WIDTH_ONE_THIRD = "w-1/3"


@binding.bindable_dataclass
class SubmitForm:
Expand All @@ -50,6 +53,10 @@ class SubmitForm:
deadline: str = (datetime.now().astimezone() + timedelta(hours=24)).strftime("%Y-%m-%d %H:%M")
validate_only: bool = False
onboard_to_aignostics_portal: bool = False
gpu_type: str = "A100"
gpu_provisioning_mode: str = "ON_DEMAND"
max_gpus_per_slide: int = 1
cpu_provisioning_mode: str = "ON_DEMAND"


submit_form = SubmitForm()
Expand Down Expand Up @@ -619,7 +626,7 @@ class ThumbnailRenderer {
today = now.strftime("%Y/%m/%d")
min_hour = (now + timedelta(hours=1)).hour
min_minute = (now + timedelta(hours=1)).minute
ui.label("Soft Due Date").classes("text-h6 mb-0 pb-0")
ui.label("Soft Due Date").classes("class_subsection_header")
ui.label(
"The platform will try to complete the run before this time, "
"given your subscription tier and available GPU resources."
Expand Down Expand Up @@ -672,7 +679,7 @@ class ThumbnailRenderer {
}}
"""
)
ui.label("Hard Deadline").classes("text-h6 mb-0 pb-0")
ui.label("Hard Deadline").classes("class_subsection_header")
ui.label("The platform might cancel the run if not completed by this time.").classes(
"text-sm mt-0 pt-0"
)
Expand Down Expand Up @@ -702,11 +709,25 @@ def _submit() -> None:
"""Submit the application run."""
ui.notify("Submitting application run ...", type="info")
try:
# Build custom metadata with pipeline configuration
custom_metadata = {
"pipeline": {
"gpu": {
"gpu_type": submit_form.gpu_type,
"provisioning_mode": submit_form.gpu_provisioning_mode,
"max_gpus_per_slide": submit_form.max_gpus_per_slide,
},
"cpu": {
"provisioning_mode": submit_form.cpu_provisioning_mode,
},
},
}
Comment on lines +712 to +724
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Coverage Issue: These 13 lines are uncovered by tests (contributing to 72.91% < 75% threshold).

Recommendation: Add GUI integration test that verifies custom_metadata includes pipeline configuration:

@pytest.mark.integration
async def test_submit_with_pipeline_config(app: nicegui_testing.Screen) -> None:
    """Test pipeline configuration is included in run submission."""
    # Mock user with pipeline access
    app.storage.tab["user_info"] = UserInfo(
        organization=Organization(name="aignostics")
    )
    
    await app.open("/application/heta")
    
    # Set pipeline config values
    app.find("SELECT_GPU_TYPE").set_value("A100")
    app.find("NUMBER_MAX_GPUS_PER_SLIDE").set_value(2)
    
    with patch.object(Service, "application_run_submit_from_metadata") as mock:
        app.find("BUTTON_SUBMISSION_UPLOAD").click()
        assert mock.call_args.kwargs["custom_metadata"]["pipeline"]["gpu"]["gpu_type"] == "A100"

This would cover the custom_metadata building logic and improve patch coverage.


run = service.application_run_submit_from_metadata(
application_id=str(submit_form.application_id),
metadata=submit_form.metadata or [],
application_version=str(submit_form.application_version),
custom_metadata=None, # TODO(Helmut): Allow user to edit custom metadata
custom_metadata=custom_metadata,
note=submit_form.note,
tags=set(submit_form.tags) if submit_form.tags else None,
due_date=datetime.strptime(submit_form.due_date, "%Y-%m-%d %H:%M")
Expand Down Expand Up @@ -816,6 +837,80 @@ def _update_upload_progress() -> None:
break
_upload_ui.refresh(submit_form.metadata)

with ui.step("Pipeline"):
user_info: UserInfo | None = app.storage.tab.get("user_info", None)
can_configure_pipeline = (
user_info
and user_info.organization
and user_info.organization.name
and user_info.organization.name.lower() in {"aignostics", "pre-alpha-org", "lmu", "charite"}
Comment on lines +841 to +846
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Duplication Issue: Organization allow-list appears multiple times in this file (lines 796, 808, 846).

Recommendation: Extract to module constant:

# src/aignostics/application/_constants.py
PIPELINE_CONFIG_ALLOWED_ORGS = {"aignostics", "pre-alpha-org", "lmu", "charite"}

# Then use:
can_configure_pipeline = (
    user_info 
    and user_info.organization 
    and user_info.organization.name 
    and user_info.organization.name.lower() in PIPELINE_CONFIG_ALLOWED_ORGS
)

This reduces the 9% code duplication flagged by SonarQube.

)

if can_configure_pipeline:
with ui.column(align_items="start").classes("w-full"):
ui.label("GPU Configuration").classes("class_subsection_header")
ui.label(
"Configure GPU resources for processing your whole slide images. "
"These settings control the type and provisioning mode of GPUs used during AI analysis."
).classes("text-sm mt-0 pt-0 mb-4")

with ui.row().classes("w-full gap-4"):
ui.select(
label="GPU Type",
options={"L4": "L4", "A100": "A100"},
value=submit_form.gpu_type,
).bind_value(submit_form, "gpu_type").mark("SELECT_GPU_TYPE").classes(CLASS_WIDTH_ONE_THIRD)

ui.number(
label="Max GPUs per Slide",
value=submit_form.max_gpus_per_slide,
min=1,
max=8,
step=1,
).bind_value(submit_form, "max_gpus_per_slide").mark("NUMBER_MAX_GPUS_PER_SLIDE").classes(
CLASS_WIDTH_ONE_THIRD
)

ui.select(
label="GPU Provisioning Mode",
options={
"SPOT": "Spot nodes (lower cost, better availability, might be preempted and retried)",
"ON_DEMAND": (
"On demand nodes (higher cost, limited availability, processing might be delayed)"
),
},
value=submit_form.gpu_provisioning_mode,
).bind_value(submit_form, "gpu_provisioning_mode").mark("SELECT_GPU_PROVISIONING_MODE").classes(
CLASS_WIDTH_ONE_THIRD
)

ui.separator().classes("my-4")

ui.label("CPU Configuration").classes("class_subsection_header")
ui.label("Configure CPU resources for algorithms that do not require GPU acceleration.").classes(
"text-sm mt-0 pt-0 mb-4"
)

with ui.row().classes("w-full gap-4"):
ui.select(
label="CPU Provisioning Mode",
options={
"SPOT": "Spot nodes (lower cost, better availability, might be preempted and retried)",
"ON_DEMAND": "On demand nodes (higher cost, limited availability, might be delayed)",
},
value=submit_form.cpu_provisioning_mode,
).bind_value(submit_form, "cpu_provisioning_mode").mark("SELECT_CPU_PROVISIONING_MODE").classes(
"w-1/2"
)
else:
ui.label(
"Pipeline configuration is not available for your organization. Default settings will be used."
).classes("text-body1")

with ui.stepper_navigation():
ui.button("Next", on_click=stepper.next).mark("BUTTON_PIPELINE_NEXT")
ui.button("Back", on_click=stepper.previous).props("flat")

with ui.step("Submit"):
_upload_ui([])
ui.timer(0.1, callback=_update_upload_progress)
Expand Down
63 changes: 62 additions & 1 deletion src/aignostics/platform/_sdk_metadata.py
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Expand Up @@ -7,16 +7,76 @@
import os
import sys
from datetime import UTC, datetime
from enum import StrEnum
from typing import Any, Literal

from loguru import logger
from pydantic import BaseModel, Field, ValidationError
from pydantic import BaseModel, Field, PositiveInt, ValidationError

from aignostics.utils import user_agent

SDK_METADATA_SCHEMA_VERSION = "0.0.4"
ITEM_SDK_METADATA_SCHEMA_VERSION = "0.0.3"

# Pipeline orchestration defaults
DEFAULT_GPU_TYPE = "A100"
DEFAULT_MAX_GPUS_PER_SLIDE = 1
DEFAULT_GPU_PROVISIONING_MODE = "ON_DEMAND"
DEFAULT_CPU_PROVISIONING_MODE = "ON_DEMAND"

Comment on lines +21 to +26
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Code Quality: Excellent use of module-level constants for defaults!

Minor Suggestion: These constants appear in multiple places. Consider referencing them from a shared constants module to reduce duplication:

# src/aignostics/constants.py (already exists)
# Add pipeline defaults here so both CLI and GUI can reference them

from aignostics.constants import (
    DEFAULT_GPU_TYPE,
    DEFAULT_MAX_GPUS_PER_SLIDE,
    DEFAULT_GPU_PROVISIONING_MODE,
    DEFAULT_CPU_PROVISIONING_MODE,
)

This would help with the 9% code duplication issue flagged by SonarQube.


class GPUType(StrEnum):
"""Type of GPU to use for processing."""

L4 = "L4"
A100 = "A100"


class ProvisioningMode(StrEnum):
"""Provisioning mode for resources."""

SPOT = "SPOT"
ON_DEMAND = "ON_DEMAND"


class CPUConfig(BaseModel):
"""Configuration for CPU resources."""

provisioning_mode: ProvisioningMode = Field(
default_factory=lambda: ProvisioningMode(DEFAULT_CPU_PROVISIONING_MODE),
description="The provisioning mode for CPU resources (SPOT or ON_DEMAND)",
)


class GPUConfig(BaseModel):
"""Configuration for GPU resources."""

gpu_type: GPUType = Field(
default_factory=lambda: GPUType(DEFAULT_GPU_TYPE),
description="The type of GPU to use (L4 or A100)",
)
provisioning_mode: ProvisioningMode = Field(
default_factory=lambda: ProvisioningMode(DEFAULT_GPU_PROVISIONING_MODE),
description="The provisioning mode for GPU resources (SPOT or ON_DEMAND)",
)
max_gpus_per_slide: PositiveInt = Field(
default=DEFAULT_MAX_GPUS_PER_SLIDE,
description="The maximum number of GPUs to allocate per slide",
)


class PipelineConfig(BaseModel):
"""Pipeline configuration for dynamic orchestration."""

gpu: GPUConfig = Field(
default_factory=GPUConfig,
description="GPU resource configuration",
)
cpu: CPUConfig = Field(
default_factory=CPUConfig,
description="CPU resource configuration",
)

Comment on lines +68 to +79
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Excellent Design: 👍 PipelineConfig model with proper Pydantic validation

Strong points:

  • ✅ Enum-based types (GPUType, ProvisioningMode) prevent typos
  • ✅ PositiveInt validation on max_gpus_per_slide
  • ✅ Default factory pattern for mutable defaults
  • ✅ Clear field descriptions for documentation

This is a great example of domain-driven design with strong type safety!


class SubmissionMetadata(BaseModel):
"""Metadata about how the SDK was invoked."""
Expand Down Expand Up @@ -121,6 +181,7 @@ class RunSdkMetadata(BaseModel):
note: str | None = Field(None, description="Optional user note for the run")
workflow: WorkflowMetadata | None = Field(None, description="Workflow control flags")
scheduling: SchedulingMetadata | None = Field(None, description="Scheduling information")
pipeline: PipelineConfig | None = Field(None, description="Pipeline orchestration configuration")

model_config = {"extra": "forbid"} # Reject unknown fields

Expand Down
5 changes: 0 additions & 5 deletions tests/aignostics/application/cli_test.py
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@@ -1,6 +1,5 @@
"""Tests to verify the CLI functionality of the application module."""

import os
import platform
import re
from datetime import UTC, datetime, timedelta
Expand Down Expand Up @@ -254,10 +253,6 @@ def test_cli_run_submit_fails_on_missing_url(runner: CliRunner, tmp_path: Path,
assert "Invalid platform bucket URL: ''" in normalize_output(result.stdout)


@pytest.mark.skipif(
os.getenv("AIGNOSTICS_PLATFORM_ENVIRONMENT", "staging") == "production",
reason="Broken when targeting production",
)
@pytest.mark.e2e
@pytest.mark.long_running
@pytest.mark.flaky(retries=3, delay=5)
Expand Down
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