Xiaoxia AI
a8177c1268
- domain: ClassificationJob entity with AssetClassification enum (scenic, product, person, animal, food, tech, sport, music, other) - ports: ClassificationJobRepository interface - application: SubmitClassificationJobUseCase - adapters: InMemoryClassificationJobRepository - worker: classify_asset task with mock classification logic - tests: full classification pipeline test - all 8 integration tests passing
79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
from packages.application import SubmitClassificationJobCommand, SubmitClassificationJobUseCase
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from packages.adapters.in_memory import InMemoryClassificationJobRepository
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from packages.domain import ClassificationJobStatus, AssetClassification
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def simulate_classify_asset(job_id: str, job_repo: InMemoryClassificationJobRepository) -> dict:
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"""Simulate classification logic without Celery."""
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job = job_repo.get(job_id)
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if job is None:
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return {"status": "failed", "error": "job not found"}
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try:
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# Update job status to PROCESSING
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job.status = ClassificationJobStatus.PROCESSING
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job_repo.update(job)
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# Mock classification
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asset_id_hash = sum(ord(c) for c in job.asset_id)
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classifications = list(AssetClassification)
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classification = classifications[asset_id_hash % len(classifications)]
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confidence = 0.85
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# Update job status to COMPLETED
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job.status = ClassificationJobStatus.COMPLETED
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job.classification = classification.value
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job.confidence = confidence
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job_repo.update(job)
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return {
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"status": "completed",
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"job_id": job.id,
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"classification": classification.value,
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"confidence": confidence,
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}
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except Exception as e:
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# Update job status to FAILED
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job.status = ClassificationJobStatus.FAILED
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job.error_message = str(e)
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job_repo.update(job)
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return {
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"status": "failed",
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"job_id": job.id,
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"error": str(e),
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}
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def test_classification_pipeline():
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"""Test the full classification pipeline: submit job -> worker processes -> result."""
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job_repo = InMemoryClassificationJobRepository()
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# Submit classification job
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use_case = SubmitClassificationJobUseCase(job_repo)
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job = use_case.execute(
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SubmitClassificationJobCommand(
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workspace_id="ws-1",
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project_id="proj-1",
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asset_id="asset-123",
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)
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)
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assert job.status == ClassificationJobStatus.PENDING
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assert job.classification == ""
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assert job.confidence == 0.0
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# Simulate worker task execution
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result = simulate_classify_asset(job.id, job_repo)
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assert result["status"] == "completed"
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assert "classification" in result
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assert "confidence" in result
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# Verify job was updated
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updated_job = job_repo.get(job.id)
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assert updated_job is not None
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assert updated_job.status == ClassificationJobStatus.COMPLETED
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assert updated_job.classification != ""
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assert updated_job.confidence > 0.0
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