67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
#!/usr/bin/env python3
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"""
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测试output变量提取逻辑
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"""
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import sys
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sys.path.insert(0, 'backend')
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from app.services.workflow_engine import WorkflowEngine
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# 模拟llm-format节点的输入数据
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input_data = {
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'right': {
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'right': {
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'right': '是的，我记得！根据我们之前的对话，你告诉我你的名字叫"老七"。我会在本次对话中记住这个名字，以便更好地为你提供帮助。如果你希望我用其他称呼，也可以随时告诉我。',
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'query': '你还记得我的名字吗？'
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},
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'memory': {
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'conversation_history': [],
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'user_profile': {},
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'context': {}
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},
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'query': '你还记得我的名字吗？'
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},
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'memory': {
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'conversation_history': [],
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'user_profile': {},
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'context': {}
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},
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'query': '你还记得我的名字吗？'
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}
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# 创建WorkflowEngine实例
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engine = WorkflowEngine("test", {"nodes": [], "edges": []})
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# 测试_get_nested_value方法
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print("测试_get_nested_value方法:")
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value1 = engine._get_nested_value(input_data, 'output')
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print(f" _get_nested_value(input_data, 'output'): {value1}")
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# 测试output变量提取逻辑
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print("\n测试output变量提取逻辑:")
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right_value = input_data.get('right')
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print(f" right_value类型: {type(right_value)}")
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print(f" right_value: {str(right_value)[:100]}")
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if right_value is not None:
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if isinstance(right_value, str):
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value = right_value
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print(f" ✅ 从right字段（字符串）提取: {value[:100]}")
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elif isinstance(right_value, dict):
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current = right_value
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depth = 0
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while isinstance(current, dict) and depth < 10:
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if 'right' in current:
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current = current['right']
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depth += 1
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if isinstance(current, str):
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value = current
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print(f" ✅ 从right字段（嵌套{depth}层）提取: {value[:100]}")
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break
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else:
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break
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else:
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print(f" ❌ 无法提取字符串值")
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print("\n测试完成")
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