cfa642cf0a
- 改进表达学习器的提示词格式规范，增强LLM输出解析的容错性 - 优化表达选择器的模型预测模式，添加情境提取和模糊匹配机制 - 增强StyleLearner的错误处理和日志记录，提高训练和预测的稳定性 - 改进流循环管理器的日志输出，避免重复信息刷屏 - 扩展SendAPI的消息查找功能，支持DatabaseMessages对象兼容 - 添加智能回退机制，当模型预测失败时自动切换到经典模式 - 优化数据库查询逻辑，支持跨聊天流的表达方式共享 BREAKING CHANGE: 表达选择器的模型预测模式现在需要情境提取器配合使用，旧版本配置可能需要更新依赖关系
89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
"""
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检查 StyleLearner 模型状态的诊断脚本
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"""
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import sys
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from pathlib import Path
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# 添加项目根目录到路径
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project_root = Path(__file__).parent.parent
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sys.path.insert(0, str(project_root))
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from src.chat.express.style_learner import style_learner_manager
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from src.common.logger import get_logger
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logger = get_logger("debug_style_learner")
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def check_style_learner_status(chat_id: str):
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"""检查指定 chat_id 的 StyleLearner 状态"""
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print("=" * 60)
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print(f"StyleLearner 状态诊断 - Chat ID: {chat_id}")
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print("=" * 60)
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# 获取 learner
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learner = style_learner_manager.get_learner(chat_id)
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# 1. 基本信息
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print(f"\n📊 基本信息:")
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print(f" Chat ID: {learner.chat_id}")
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print(f" 风格数量: {len(learner.style_to_id)}")
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print(f" 下一个ID: {learner.next_style_id}")
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print(f" 最大风格数: {learner.max_styles}")
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# 2. 学习统计
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print(f"\n📈 学习统计:")
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print(f" 总样本数: {learner.learning_stats['total_samples']}")
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print(f" 最后更新: {learner.learning_stats.get('last_update', 'N/A')}")
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# 3. 风格列表（前20个）
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print(f"\n📋 已学习的风格 (前20个):")
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all_styles = learner.get_all_styles()
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if not all_styles:
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print(" ⚠️ 没有任何风格！模型尚未训练")
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else:
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for i, style in enumerate(all_styles[:20], 1):
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style_id = learner.style_to_id.get(style)
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situation = learner.id_to_situation.get(style_id, "N/A")
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print(f" [{i}] {style}")
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print(f" (ID: {style_id}, Situation: {situation})")
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# 4. 测试预测
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print(f"\n🔮 测试预测功能:")
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if not all_styles:
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print(" ⚠️ 无法测试，模型没有训练数据")
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else:
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test_situations = [
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"表示惊讶",
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"讨论游戏",
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"表达赞同"
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]
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for test_sit in test_situations:
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print(f"\n 测试输入: '{test_sit}'")
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best_style, scores = learner.predict_style(test_sit, top_k=3)
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if best_style:
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print(f" ✓ 最佳匹配: {best_style}")
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print(f" Top 3:")
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for style, score in list(scores.items())[:3]:
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print(f" - {style}: {score:.4f}")
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else:
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print(f" ✗ 预测失败")
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print("\n" + "=" * 60)
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print("诊断完成")
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print("=" * 60)
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if __name__ == "__main__":
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# 从诊断报告中看到的 chat_id
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test_chat_ids = [
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"52fb94af9f500a01e023ea780e43606e", # 有78个表达方式
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"46c8714c8a9b7ee169941fe99fcde07d", # 有22个表达方式
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]
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for chat_id in test_chat_ids:
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check_style_learner_status(chat_id)
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print("\n")
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