fix/crawler-proxy-config #42
+18
-25
@@ -14,6 +14,7 @@ import pytest
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from pathlib import Path
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from dataclasses import dataclass
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from typing import List, Optional
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from unittest.mock import Mock
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# =============================================================================
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@@ -504,74 +505,66 @@ class TestSemanticSegmentationToggle:
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from kb_workflow.pipeline.processors.srt import SRTProcessor
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from unittest.mock import patch
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with patch('kb_workflow.srt.semantic_engine.SimpleAIClient') as mock_client:
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with patch('kb_workflow.deep_analyzer.SimpleAIClient') as mock_client:
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mock_client.return_value = Mock(api_key="test_key")
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processor = SRTProcessor(
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config={},
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enable_semantic_segmentation=True
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)
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# 验证创建了 SemanticSegmentationEngine
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assert hasattr(processor, 'semantic_engine')
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# 注意:当前实现可能还没有这些属性,这个测试在实现后会通过
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# assert processor.semantic_engine is not None
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# assert processor.segmenter is None
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from kb_workflow.srt.semantic_engine import SemanticSegmentationEngine
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assert isinstance(processor.segmenter, SemanticSegmentationEngine)
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# 验证缓存已启用(默认)
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assert processor.segmenter.strategy.cache is not None
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def test_semantic_segmentation_disabled(self, sample_srt_file_for_toggle):
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"""测试禁用语义分段(默认)"""
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from kb_workflow.pipeline.processors.srt import SRTProcessor
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from kb_workflow.srt.segmenter import SemanticSegmenter
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processor = SRTProcessor(
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config={},
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enable_semantic_segmentation=False
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)
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# 验证使用规则分段器
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# 注意:当前实现可能还没有这些属性,这个测试在实现后会通过
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# assert processor.semantic_engine is None
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# assert processor.segmenter is not None
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pass
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assert isinstance(processor.segmenter, SemanticSegmenter)
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def test_semantic_segmentation_with_cache(self, sample_srt_file_for_toggle):
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"""测试启用语义分段和缓存"""
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from kb_workflow.pipeline.processors.srt import SRTProcessor
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from unittest.mock import patch
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with patch('kb_workflow.srt.semantic_engine.SimpleAIClient') as mock_client:
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with patch('kb_workflow.deep_analyzer.SimpleAIClient') as mock_client:
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mock_client.return_value = Mock(api_key="test_key")
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processor = SRTProcessor(
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config={},
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enable_semantic_segmentation=True,
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enable_cache=True
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)
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# 验证创建了缓存
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# 注意:当前实现可能还没有这些属性,这个测试在实现后会通过
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# assert processor.semantic_engine is not None
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# assert processor.semantic_engine.strategy.cache is not None
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pass
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# 验证创建了 SemanticSegmentationEngine 且缓存已启用
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from kb_workflow.srt.semantic_engine import SemanticSegmentationEngine
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assert isinstance(processor.segmenter, SemanticSegmentationEngine)
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assert processor.segmenter.strategy.cache is not None
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def test_semantic_segmentation_without_cache(self, sample_srt_file_for_toggle):
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"""测试启用语义分段但禁用缓存"""
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from kb_workflow.pipeline.processors.srt import SRTProcessor
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from unittest.mock import patch
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with patch('kb_workflow.srt.semantic_engine.SimpleAIClient') as mock_client:
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with patch('kb_workflow.deep_analyzer.SimpleAIClient') as mock_client:
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mock_client.return_value = Mock(api_key="test_key")
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processor = SRTProcessor(
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config={},
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enable_semantic_segmentation=True,
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enable_cache=False
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)
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# 验证没有创建缓存
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# 注意:当前实现可能还没有这些属性,这个测试在实现后会通过
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# assert processor.semantic_engine is not None
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# assert processor.semantic_engine.strategy.cache is None
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pass
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# 验证创建了 SemanticSegmentationEngine 但缓存未启用
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from kb_workflow.srt.semantic_engine import SemanticSegmentationEngine
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assert isinstance(processor.segmenter, SemanticSegmentationEngine)
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assert processor.segmenter.strategy.cache is None
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@pytest.fixture
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def sample_srt_file_for_toggle(self, tmp_path):
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