364 lines
10 KiB
Python
364 lines
10 KiB
Python
"""
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Tests pour la gestion des erreurs du Pipeline.
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Ce module teste le retry, le timeout et le mode résultats partiels.
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"""
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import pytest
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from datetime import datetime, timedelta
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from unittest.mock import Mock, patch
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from pipeline_mco_pmsi.models.clinical import ClinicalDocument
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from pipeline_mco_pmsi.models.metadata import StayMetadata
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from pipeline_mco_pmsi.pipeline import Pipeline
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def test_pipeline_retry_on_failure(db_session, rag_engine):
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"""
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Test le retry avec exponential backoff en cas d'échec.
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Exigences: 14.1, 14.6
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"""
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from pipeline_mco_pmsi.database.models import StayDB
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pipeline = Pipeline(
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db_session=db_session,
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rag_engine=rag_engine,
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max_retries=3,
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retry_delay=0.1, # Court délai pour les tests
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)
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# Créer le séjour dans la base de données
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stay = StayDB(
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stay_id="stay_retry_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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db_session.add(stay)
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db_session.commit()
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documents = [
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ClinicalDocument(
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document_id="doc_retry_001",
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document_type="cr_medical",
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content="Diagnostic: Gastrite aiguë.",
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creation_date=datetime.now(),
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author="Dr. Test",
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priority=2,
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)
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]
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stay_metadata = StayMetadata(
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stay_id="stay_retry_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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# Mock pour simuler des échecs puis succès
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call_count = 0
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original_extract = pipeline.clinical_facts_extractor.extract_facts
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def mock_extract_with_retry(structured_stay):
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nonlocal call_count
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call_count += 1
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if call_count < 2: # Échoue la première fois
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raise RuntimeError("Erreur temporaire")
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return original_extract(structured_stay)
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with patch.object(
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pipeline.clinical_facts_extractor,
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"extract_facts",
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side_effect=mock_extract_with_retry,
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):
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result = pipeline.process_stay(documents, stay_metadata)
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# Vérifications
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assert call_count == 2 # 1 échec + 1 succès
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assert result.success is True
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def test_pipeline_timeout_with_partial_results(db_session, rag_engine):
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"""
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Test le timeout avec mode résultats partiels activé.
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Exigences: 14.6
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"""
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from pipeline_mco_pmsi.database.models import StayDB
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pipeline = Pipeline(
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db_session=db_session,
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rag_engine=rag_engine,
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timeout=0.01, # Timeout très court pour forcer l'erreur
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partial_results_mode=True,
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)
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# Créer le séjour dans la base de données
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stay = StayDB(
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stay_id="stay_timeout_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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db_session.add(stay)
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db_session.commit()
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documents = [
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ClinicalDocument(
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document_id="doc_timeout_001",
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document_type="cr_medical",
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content="Diagnostic: Gastrite aiguë.",
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creation_date=datetime.now(),
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author="Dr. Test",
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priority=2,
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)
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]
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stay_metadata = StayMetadata(
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stay_id="stay_timeout_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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# Mock pour ralentir le traitement
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import time
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def slow_extract(structured_stay):
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time.sleep(0.1) # Plus long que le timeout
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return []
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with patch.object(
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pipeline.clinical_facts_extractor,
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"extract_facts",
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side_effect=slow_extract,
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):
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result = pipeline.process_stay(documents, stay_metadata)
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# Vérifications
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assert result.success is False
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assert "timeout" in result.error_message.lower()
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# Vérifier qu'un problème de validation timeout a été ajouté
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timeout_issues = [
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issue for issue in result.validation_issues
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if "timeout" in issue.message.lower()
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]
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assert len(timeout_issues) > 0
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def test_pipeline_timeout_without_partial_results(db_session, rag_engine):
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"""
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Test le timeout sans mode résultats partiels (doit lever une exception).
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Exigences: 14.6
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"""
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from pipeline_mco_pmsi.database.models import StayDB
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pipeline = Pipeline(
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db_session=db_session,
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rag_engine=rag_engine,
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timeout=0.01, # Timeout très court
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partial_results_mode=False, # Mode désactivé
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)
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# Créer le séjour dans la base de données
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stay = StayDB(
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stay_id="stay_timeout_002",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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db_session.add(stay)
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db_session.commit()
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documents = [
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ClinicalDocument(
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document_id="doc_timeout_002",
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document_type="cr_medical",
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content="Diagnostic: Gastrite aiguë.",
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creation_date=datetime.now(),
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author="Dr. Test",
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priority=2,
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)
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]
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stay_metadata = StayMetadata(
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stay_id="stay_timeout_002",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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# Mock pour ralentir le traitement
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import time
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def slow_extract(structured_stay):
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time.sleep(0.1)
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return []
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with patch.object(
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pipeline.clinical_facts_extractor,
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"extract_facts",
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side_effect=slow_extract,
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):
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result = pipeline.process_stay(documents, stay_metadata)
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# Vérifications - devrait retourner un résultat d'erreur
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assert result.success is False
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assert result.error_message is not None
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def test_pipeline_max_retries_exceeded(db_session, rag_engine):
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"""
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Test que le pipeline échoue après avoir dépassé le nombre maximum de retries.
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Exigences: 14.1
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"""
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from pipeline_mco_pmsi.database.models import StayDB
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pipeline = Pipeline(
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db_session=db_session,
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rag_engine=rag_engine,
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max_retries=2,
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retry_delay=0.1,
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)
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# Créer le séjour dans la base de données
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stay = StayDB(
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stay_id="stay_max_retry_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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db_session.add(stay)
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db_session.commit()
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documents = [
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ClinicalDocument(
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document_id="doc_max_retry_001",
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document_type="cr_medical",
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content="Diagnostic: Gastrite aiguë.",
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creation_date=datetime.now(),
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author="Dr. Test",
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priority=2,
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)
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]
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stay_metadata = StayMetadata(
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stay_id="stay_max_retry_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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# Mock pour toujours échouer
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def always_fail(structured_stay):
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raise RuntimeError("Erreur persistante")
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with patch.object(
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pipeline.clinical_facts_extractor,
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"extract_facts",
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side_effect=always_fail,
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):
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result = pipeline.process_stay(documents, stay_metadata)
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# Vérifications
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assert result.success is False
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assert result.error_message is not None
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assert "Erreur persistante" in result.error_message
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def test_pipeline_error_handling_with_partial_data(db_session, rag_engine):
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"""
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Test que les données partielles sont préservées en cas d'erreur.
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Exigences: 14.6
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"""
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from pipeline_mco_pmsi.database.models import StayDB
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pipeline = Pipeline(
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db_session=db_session,
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rag_engine=rag_engine,
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partial_results_mode=True,
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)
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# Créer le séjour dans la base de données
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stay = StayDB(
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stay_id="stay_partial_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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db_session.add(stay)
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db_session.commit()
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documents = [
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ClinicalDocument(
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document_id="doc_partial_001",
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document_type="cr_medical",
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content="Diagnostic: Gastrite aiguë.",
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creation_date=datetime.now(),
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author="Dr. Test",
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priority=2,
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)
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]
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stay_metadata = StayMetadata(
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stay_id="stay_partial_001",
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admission_date=datetime.now() - timedelta(days=1),
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discharge_date=datetime.now(),
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specialty="gastro-enterologie",
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unit="medecine",
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age=45,
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sex="M",
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)
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# Mock pour échouer après l'extraction des faits
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def fail_after_facts(proposal, facts, cim10_version, ccam_version):
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raise RuntimeError("Erreur lors de la vérification")
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with patch.object(
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pipeline.verificateur,
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"verify_proposal",
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side_effect=fail_after_facts,
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):
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result = pipeline.process_stay(documents, stay_metadata)
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# Vérifications
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assert result.success is False
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# Les données partielles doivent être présentes
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assert result.structured_stay is not None
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# Le coding_proposal peut être None si l'erreur survient avant ou pendant le codage
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# On vérifie juste que le résultat est bien un échec avec un message d'erreur
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assert result.error_message is not None
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