Add test pipeline generator workflow and bump version to 1.0.0

- Introduced a new GitHub Actions workflow for testing the pipeline generator, including steps for setting up Python 3.10, installing dependencies, and running tests.
- Updated the version of the pipeline-generator package from 0.1.0 to 1.0.0 in the uv.lock file.
- Refactored import statements and improved code formatting in various files for better readability and consistency.

Signed-off-by: Victor Chang <[email protected]>

Author: mocsharp

.github/workflows/pr.yml

@@ -55,3 +55,20 @@ jobs:
         with:
           fail_ci_if_error: false
           files: ./coverage.xml
+
+  test-pipeline-generator:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.10
+        uses: actions/setup-python@v2
+        with:
+          python-version: "3.10"
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
+      - name: Install dependencies
+        run: |
+          uv sync
+      - name: Run tests
+        run: |
+          uv run pytest

tools/pipeline-generator/pipeline_generator/cli/main.py

@@ -13,18 +13,18 @@
 
 import logging
 from pathlib import Path
-from typing import Optional, List, Set
+from typing import List, Optional, Set
+
 import click
 from rich.console import Console
-from rich.table import Table
 from rich.logging import RichHandler
+from rich.table import Table
 
 from ..config import load_config
 from ..core import HuggingFaceClient, ModelInfo
 from ..generator import AppGenerator
 from .run import run as run_command
 
-
 # Set up logging with Rich
 logging.basicConfig(
     level=logging.INFO,

tools/pipeline-generator/pipeline_generator/config/__init__.py

@@ -11,6 +11,6 @@
 
 """Configuration module for Pipeline Generator."""
 
-from .settings import Settings, Endpoint, load_config
+from .settings import Endpoint, Settings, load_config
 
 __all__ = ["Settings", "Endpoint", "load_config"]

tools/pipeline-generator/pipeline_generator/core/__init__.py

@@ -11,7 +11,7 @@
 
 """Core functionality for Pipeline Generator."""
 
-from .models import ModelInfo
 from .hub_client import HuggingFaceClient
+from .models import ModelInfo
 
 __all__ = ["ModelInfo", "HuggingFaceClient"]

tools/pipeline-generator/pipeline_generator/core/hub_client.py

@@ -11,15 +11,14 @@
 
 """HuggingFace Hub client for fetching model information."""
 
-from typing import List, Optional, Any
 import logging
+from typing import Any, List, Optional
 
-from huggingface_hub import HfApi, model_info, list_models
+from huggingface_hub import HfApi, list_models, model_info
 from huggingface_hub.utils import HfHubHTTPError
 
-from .models import ModelInfo
 from ..config import Endpoint
-
+from .models import ModelInfo
 
 logger = logging.getLogger(__name__)
 

tools/pipeline-generator/pipeline_generator/core/models.py

@@ -12,7 +12,7 @@
 """Data models for Pipeline Generator."""
 
 from datetime import datetime
-from typing import List, Optional, Dict, Any
+from typing import Any, Dict, List, Optional
 
 from pydantic import BaseModel, Field
 

tools/pipeline-generator/pipeline_generator/generator/app_generator.py

@@ -13,11 +13,12 @@
 
 import logging
 from pathlib import Path
-from typing import Dict, Any, Optional
+from typing import Any, Dict, Optional
+
 from jinja2 import Environment, FileSystemLoader
 
-from .bundle_downloader import BundleDownloader
 from ..config.settings import Settings, load_config
+from .bundle_downloader import BundleDownloader
 
 logger = logging.getLogger(__name__)
 
@@ -40,6 +41,7 @@ def __init__(self, settings: Optional[Settings] = None) -> None:
             loader=FileSystemLoader(str(template_dir)),
             trim_blocks=True,
             lstrip_blocks=True,
+            autoescape=False,
         )
 
     def generate_app(

tools/pipeline-generator/pipeline_generator/generator/bundle_downloader.py

@@ -11,12 +11,12 @@
 
 """Download MONAI Bundles from HuggingFace."""
 
-import logging
 import json
+import logging
 from pathlib import Path
-from typing import Optional, Dict, Any
+from typing import Any, Dict, Optional
 
-from huggingface_hub import snapshot_download, HfApi
+from huggingface_hub import HfApi, snapshot_download
 
 logger = logging.getLogger(__name__)
 

tools/pipeline-generator/pipeline_generator/templates/app.py.j2

@@ -26,43 +26,56 @@ from pathlib import Path
 from pydicom.sr.codedict import codes
 
 from monai.deploy.conditions import CountCondition
+
 {% endif %}
 from monai.deploy.core import AppContext, Application
 from monai.deploy.core.domain import Image
 from monai.deploy.core.io_type import IOType
+
 {% if use_dicom %}
 from monai.deploy.operators.dicom_data_loader_operator import DICOMDataLoaderOperator
 from monai.deploy.operators.dicom_seg_writer_operator import DICOMSegmentationWriterOperator, SegmentDescription
 from monai.deploy.operators.dicom_series_selector_operator import DICOMSeriesSelectorOperator
 from monai.deploy.operators.dicom_series_to_volume_operator import DICOMSeriesToVolumeOperator
+
 {% if 'segmentation' in task.lower() %}
 from monai.deploy.operators.stl_conversion_operator import STLConversionOperator
+
 {% endif %}
 {% elif input_type == "image" %}
 from monai.deploy.operators.image_directory_loader_operator import ImageDirectoryLoader
+
 {% elif input_type == "custom" %}
+from monai.deploy.operators.llama3_vila_inference_operator import Llama3VILAInferenceOperator
+
 # Custom operators for vision-language models
 from monai.deploy.operators.prompts_loader_operator import PromptsLoaderOperator
-from monai.deploy.operators.llama3_vila_inference_operator import Llama3VILAInferenceOperator
 from monai.deploy.operators.vlm_results_writer_operator import VLMResultsWriterOperator
+
 {% else %}
 from monai.deploy.operators.nifti_directory_loader_operator import NiftiDirectoryLoader
+
 {% endif %}
 {% if output_type == "json" %}
 from monai.deploy.operators.json_results_writer_operator import JSONResultsWriter
+
 {% elif output_type == "image_overlay" %}
 from monai.deploy.operators.image_overlay_writer_operator import ImageOverlayWriter
+
 {% elif not use_dicom %}
 from monai.deploy.operators.nifti_writer_operator import NiftiWriter
+
 {% endif %}
 {% if "classification" in task.lower() and input_type == "image" %}
 from monai.deploy.operators.monai_classification_operator import MonaiClassificationOperator
+
 {% elif not (input_type == "custom" and output_type == "custom") %}
 from monai.deploy.operators.monai_bundle_inference_operator import (
     BundleConfigNames,
     IOMapping,
     MonaiBundleInferenceOperator,
 )
+
 {% endif %}
 
 

tools/pipeline-generator/tests/test_bundle_downloader.py

@@ -15,7 +15,6 @@
 from unittest.mock import patch
 
 import pytest
-
 from pipeline_generator.generator.bundle_downloader import BundleDownloader