Ruff fix
This commit is contained in:
墨梓柒
@@ -1,7 +1,6 @@
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import time
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import json
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import os
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from datetime import datetime
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from typing import List, Optional, Tuple
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import traceback
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from src.common.logger import get_logger
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@@ -158,8 +157,6 @@ class ExpressionLearner:
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traceback.print_exc()
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return
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async def learn_and_store(self, num: int = 10) -> List[Tuple[str, str, str]]:
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"""
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学习并存储表达方式
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@@ -169,7 +166,7 @@ class ExpressionLearner:
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if learnt_expressions is None:
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logger.info("没有学习到表达风格")
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return []
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# 展示学到的表达方式
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learnt_expressions_str = ""
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for (
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@@ -186,7 +183,7 @@ class ExpressionLearner:
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# 存储到数据库 Expression 表并训练 style_learner
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has_new_expressions = False # 记录是否有新的表达方式
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learner = style_learner_manager.get_learner(self.chat_id) # 获取 learner 实例
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for (
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situation,
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style,
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@@ -195,9 +192,7 @@ class ExpressionLearner:
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) in learnt_expressions:
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# 查找是否已存在相似表达方式
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query = Expression.select().where(
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(Expression.chat_id == self.chat_id)
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& (Expression.situation == situation)
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& (Expression.style == style)
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(Expression.chat_id == self.chat_id) & (Expression.situation == situation) & (Expression.style == style)
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)
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if query.exists():
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# 表达方式完全相同，只更新时间戳
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@@ -216,39 +211,37 @@ class ExpressionLearner:
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up_content=up_content,
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)
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has_new_expressions = True
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# 训练 style_learner（up_content 和 style 必定存在）
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try:
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learner.add_style(style, situation)
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# 学习映射关系
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success = style_learner_manager.learn_mapping(
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self.chat_id,
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up_content,
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style
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)
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success = style_learner_manager.learn_mapping(self.chat_id, up_content, style)
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if success:
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logger.debug(f"StyleLearner学习成功: {self.chat_id} - {up_content} -> {style}" + (f" (situation: {situation})" if situation else ""))
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logger.debug(
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f"StyleLearner学习成功: {self.chat_id} - {up_content} -> {style}"
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+ (f" (situation: {situation})" if situation else "")
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)
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else:
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logger.warning(f"StyleLearner学习失败: {self.chat_id} - {up_content} -> {style}")
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except Exception as e:
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logger.error(f"StyleLearner学习异常: {self.chat_id} - {e}")
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# 保存当前聊天室的 style_learner 模型
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if has_new_expressions:
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try:
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logger.info(f"开始保存聊天室 {self.chat_id} 的 StyleLearner 模型...")
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save_success = learner.save(style_learner_manager.model_save_path)
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if save_success:
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logger.info(f"StyleLearner 模型保存成功，聊天室: {self.chat_id}")
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else:
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logger.warning(f"StyleLearner 模型保存失败，聊天室: {self.chat_id}")
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except Exception as e:
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logger.error(f"StyleLearner 模型保存异常: {e}")
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return learnt_expressions
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async def match_expression_context(
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@@ -334,7 +327,7 @@ class ExpressionLearner:
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matched_expressions = []
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used_pair_indices = set() # 用于跟踪已经使用的expression_pair索引
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logger.debug(f"match_responses 类型: {type(match_responses)}, 长度: {len(match_responses)}")
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logger.debug(f"match_responses 内容: {match_responses}")
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@@ -344,12 +337,12 @@ class ExpressionLearner:
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if not isinstance(match_response, dict):
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logger.error(f"match_response 不是字典类型: {type(match_response)}, 内容: {match_response}")
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continue
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# 获取表达方式序号
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if "expression_pair" not in match_response:
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logger.error(f"match_response 缺少 'expression_pair' 字段: {match_response}")
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continue
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pair_index = int(match_response["expression_pair"]) - 1 # 转换为0-based索引
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# 检查索引是否有效且未被使用过
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@@ -367,9 +360,7 @@ class ExpressionLearner:
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return matched_expressions
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async def learn_expression(
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self, num: int = 10
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) -> Optional[List[Tuple[str, str, str, str]]]:
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async def learn_expression(self, num: int = 10) -> Optional[List[Tuple[str, str, str, str]]]:
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"""从指定聊天流学习表达方式
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Args:
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@@ -409,7 +400,6 @@ class ExpressionLearner:
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expressions: List[Tuple[str, str]] = self.parse_expression_response(response)
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# logger.debug(f"学习{type_str}的response: {response}")
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# 对表达方式溯源
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matched_expressions: List[Tuple[str, str, str]] = await self.match_expression_context(
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expressions, random_msg_match_str
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@@ -426,17 +416,17 @@ class ExpressionLearner:
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if similarity >= 0.85: # 85%相似度阈值
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pos = i
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break
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if pos is None or pos == 0:
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# 没有匹配到目标句或没有上一句，跳过该表达
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continue
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# 检查目标句是否为空
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target_content = bare_lines[pos][1]
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if not target_content:
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# 目标句为空，跳过该表达
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continue
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prev_original_idx = bare_lines[pos - 1][0]
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up_content = filter_message_content(random_msg[prev_original_idx].processed_plain_text or "")
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if not up_content:
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@@ -449,7 +439,6 @@ class ExpressionLearner:
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return filtered_with_up
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def parse_expression_response(self, response: str) -> List[Tuple[str, str, str]]:
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"""
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解析LLM返回的表达风格总结，每一行提取"当"和"使用"之间的内容，存储为(situation, style)元组
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@@ -483,21 +472,21 @@ class ExpressionLearner:
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def _build_bare_lines(self, messages: List) -> List[Tuple[int, str]]:
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"""
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为每条消息构建精简文本列表，保留到原消息索引的映射
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Args:
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messages: 消息列表
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Returns:
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List[Tuple[int, str]]: (original_index, bare_content) 元组列表
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"""
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bare_lines: List[Tuple[int, str]] = []
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for idx, msg in enumerate(messages):
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content = msg.processed_plain_text or ""
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content = filter_message_content(content)
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# 即使content为空也要记录，防止错位
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bare_lines.append((idx, content))
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return bare_lines
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