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https://github.com/azaion/ai-training.git
synced 2026-04-22 10:56:36 +00:00
Update autopilot workflow and documentation for project cycle completion
- Modified the existing-code workflow to automatically loop back to New Task after project completion without user confirmation. - Updated the autopilot state to reflect the current step as `done` and status as `completed`. - Clarified the deployment status report by specifying non-deployed services and their purposes. These changes enhance the automation of task management and improve documentation clarity.
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@@ -1,3 +1,4 @@
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import shutil
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import sys
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from pathlib import Path
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@@ -180,3 +181,27 @@ class TestCoremlExport:
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# Assert
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assert len(results) == 1
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assert results[0].boxes is not None
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_INPUT_DATA = _TESTS_DIR.parent / "_docs" / "00_problem" / "input_data"
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@pytest.mark.skipif(sys.platform != "darwin", reason="CoreML requires macOS")
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class TestCoremlExportRealModel:
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def test_export_azaion_pt_to_coreml(self, fixture_pt_model):
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# Arrange
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output_dir = _INPUT_DATA / "azaion.mlpackage"
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if output_dir.exists():
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shutil.rmtree(output_dir)
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# Act
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model = YOLO(fixture_pt_model)
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model.export(format="coreml", imgsz=1280)
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exported = Path(fixture_pt_model).with_suffix(".mlpackage")
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if exported != output_dir:
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shutil.move(str(exported), str(output_dir))
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# Assert
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assert output_dir.exists()
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model_file = output_dir / "Data" / "com.apple.CoreML" / "model.mlmodel"
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assert model_file.exists()
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