76 lines
2.4 KiB
Python
76 lines
2.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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增强版优先级算法测试脚本
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"""
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import sys
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import os
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from datetime import datetime
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# 添加路径
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sys.path.append(os.path.dirname(__file__))
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try:
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from src.jixia.debates.enhanced_priority_algorithm import EnhancedPriorityAlgorithm
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print("✅ 算法导入成功！")
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# 创建算法实例
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algorithm = EnhancedPriorityAlgorithm()
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print("✅ 算法实例创建成功！")
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# 测试基本功能
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context = {
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"current_stage": "转",
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"stage_progress": 5,
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"max_progress": 36,
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"time_remaining": 0.7,
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"topic_keywords": ["投资", "AI", "风险"],
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"positive_team_score": 0.6,
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"negative_team_score": 0.4
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}
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recent_speeches = [
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{
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"speaker": "正1",
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"content": "根据最新数据显示，AI投资确实带来了显著的收益增长",
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"timestamp": datetime.now().isoformat(),
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"team": "positive"
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},
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{
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"speaker": "反1",
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"content": "但是我们不能忽视其中的巨大风险，这种投资策略过于激进",
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"timestamp": datetime.now().isoformat(),
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"team": "negative"
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}
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]
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available_speakers = ["正1", "正2", "正3", "正4", "反1", "反2", "反3", "反4"]
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# 测试优先级计算
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print("\n🧪 测试优先级计算...")
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for speaker in available_speakers[:4]: # 测试前4个
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priority = algorithm.calculate_speaker_priority(speaker, context, recent_speeches)
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print(f" {speaker}: {priority:.3f}")
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# 测试获取下一发言者
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print("\n🎯 测试获取下一发言者...")
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next_speaker, score, analysis = algorithm.get_next_speaker(available_speakers, context, recent_speeches)
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print(f"推荐发言者: {next_speaker}")
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print(f"优先级分数: {score:.3f}")
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# 测试算法状态
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print("\n📊 算法状态报告:")
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status = algorithm.get_algorithm_status()
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print(f"版本: {status['version']}")
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print(f"跟踪发言者数量: {status['total_speakers_tracked']}")
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print(f"算法组件: {status['algorithm_components']}")
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print("\n🎉 所有测试通过！增强版优先级算法 v2.1.0 运行正常！")
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except ImportError as e:
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print(f"❌ 导入错误: {e}")
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except Exception as e:
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print(f"❌ 运行错误: {e}")
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import traceback
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traceback.print_exc() |