177 lines
6.2 KiB
Python
177 lines
6.2 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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首次播放逻辑专项测试
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验证第一句TTS触发机制的优化效果
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"""
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import sys
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def test_first_playback_logic():
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"""测试首次播放逻辑"""
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print("🎵 首次播放逻辑专项测试")
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print("=" * 50)
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# 测试场景1: 短句子积累
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print("📝 测试场景1: 短句子积累")
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print(" 模拟LLM生成的短句子流:")
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short_sentences = [
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"你好",
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"嗯",
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"这个",
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"问题",
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"确实",
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"需要",
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"仔细",
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"思考",
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]
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buffer = []
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total_length = 0
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first_trigger = None
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for i, sentence in enumerate(short_sentences):
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buffer.append(sentence)
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total_length = sum(len(s) for s in buffer)
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# 模拟首次播放逻辑
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trigger_reason = None
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if total_length >= 40 and len(buffer) >= 2:
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trigger_reason = f"总长度{total_length}字符，{len(buffer)}个句子"
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elif len(buffer) >= 5:
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trigger_reason = f"缓冲区达到最大值{len(buffer)}"
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if trigger_reason and first_trigger is None:
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first_trigger = i + 1
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print(f" 🎵 第{first_trigger}句触发TTS: {trigger_reason}")
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print(f" 📝 发送内容: '{''.join(buffer)}'")
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break
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else:
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print(f" ⏳ 第{i+1}句: '{sentence}' (累计: {total_length}字符, {len(buffer)}个句子)")
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if first_trigger is None:
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print(" ⚠️ 未触发TTS（需要超时机制）")
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print()
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# 测试场景2: 中等长度句子
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print("📝 测试场景2: 中等长度句子")
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medium_sentences = [
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"你好，很高兴见到你。",
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"今天天气真不错呢。",
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"我们可以一起去公园玩吗？",
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"我想那会是一个很好的主意。",
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]
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buffer = []
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total_length = 0
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first_trigger = None
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for i, sentence in enumerate(medium_sentences):
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buffer.append(sentence)
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total_length = sum(len(s) for s in buffer)
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# 模拟首次播放逻辑
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trigger_reason = None
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if total_length >= 40 and len(buffer) >= 2:
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trigger_reason = f"总长度{total_length}字符，{len(buffer)}个句子"
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elif len(sentence) >= 25 and sentence.endswith(('。', '！', '？', '.', '!', '?')) and len(buffer) >= 2:
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trigger_reason = f"长句子{len(sentence)}字符+缓冲内容"
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if trigger_reason and first_trigger is None:
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first_trigger = i + 1
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print(f" 🎵 第{first_trigger}句触发TTS: {trigger_reason}")
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print(f" 📝 发送内容: '{''.join(buffer)}'")
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break
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else:
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print(f" ⏳ 第{i+1}句: '{sentence}' (累计: {total_length}字符, {len(buffer)}个句子)")
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if first_trigger is None:
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print(" ⚠️ 未触发TTS（需要超时机制）")
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print()
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# 测试场景3: 长句子
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print("📝 测试场景3: 长句子")
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long_sentences = [
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"你好，",
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"我认为这个问题需要我们从多个角度来分析。",
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"首先，让我们仔细了解一下具体情况。",
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]
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buffer = []
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total_length = 0
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first_trigger = None
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for i, sentence in enumerate(long_sentences):
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buffer.append(sentence)
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total_length = sum(len(s) for s in buffer)
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# 模拟首次播放逻辑
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trigger_reason = None
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if total_length >= 40 and len(buffer) >= 2:
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trigger_reason = f"总长度{total_length}字符，{len(buffer)}个句子"
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elif len(sentence) >= 25 and sentence.endswith(('。', '！', '？', '.', '!', '?')) and len(buffer) >= 2:
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trigger_reason = f"长句子{len(sentence)}字符+缓冲内容"
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if trigger_reason and first_trigger is None:
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first_trigger = i + 1
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print(f" 🎵 第{first_trigger}句触发TTS: {trigger_reason}")
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print(f" 📝 发送内容: '{''.join(buffer)}'")
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break
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else:
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print(f" ⏳ 第{i+1}句: '{sentence}' (累计: {total_length}字符, {len(buffer)}个句子)")
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if first_trigger is None:
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print(" ⚠️ 未触发TTS（需要超时机制）")
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print()
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# 测试场景4: 超长单句
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print("📝 测试场景4: 超长单句")
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ultra_long_sentence = "根据我的分析，这个问题的解决方案需要综合考虑多个因素，包括时间成本、资源投入以及最终的实施效果。"
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buffer = ["你好"]
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buffer.append(ultra_long_sentence)
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total_length = sum(len(s) for s in buffer)
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if total_length >= 40 and len(buffer) >= 2:
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print(f" 🎵 第2句触发TTS: 总长度{total_length}字符，{len(buffer)}个句子")
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print(f" 📝 发送内容: '{''.join(buffer)[:50]}...'")
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else:
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print(" ⚠️ 未触发TTS")
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print()
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def show_optimization_comparison():
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"""显示优化对比"""
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print("📈 首次播放逻辑优化对比")
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print("=" * 50)
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comparison = {
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"优化前": {
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"触发条件": "任何完整句子或长句子",
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"最小长度": "无明确要求",
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"积攒机制": "基本没有",
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"可能导致": "播放卡顿，等待数据",
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},
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"优化后": {
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"触发条件": "40+字符且2+句子 或 25+字符完整句+缓冲",
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"最小长度": "总长度40字符或单句25字符",
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"积攒机制": "智能积累多个句子",
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"超时保护": "5秒超时机制",
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"效果": "确保有足够数据才开始播放"
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}
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}
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for aspect, details in comparison.items():
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print(f"\n🔧 {aspect}:")
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for key, value in details.items():
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print(f" • {key}: {value}")
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print(f"\n🎯 核心改进: 确保首次播放有足够的内容，避免因为数据不足导致的播放卡顿")
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if __name__ == "__main__":
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if len(sys.argv) > 1 and sys.argv[1] == "--comparison":
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show_optimization_comparison()
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else:
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test_first_playback_logic()
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show_optimization_comparison() |