mirror of https://github.com/Mai-with-u/MaiBot.git
better：优化表达方式，现在表达方式会随时间更加精准
SengokuCola
parent
4a5ca048ad
commit
a41f4694cf
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@ -3,8 +3,12 @@
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## [0.11.3] - 2025-11-17
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### 功能更改和修复
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- 优化记忆提取策略
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- 优化表达方式学习
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- 修改readme
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提示：清理旧的记忆数据和表达方式，表现更好
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方法：删除数据库中 expression jargon 和 thinking_back 的全部内容
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## [0.11.2] - 2025-11-16
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### 🌟 主要功能更改
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- "海马体Agent"记忆系统上线，最新最好的记忆系统，默认已接入lpmm
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@ -311,6 +311,8 @@ class Expression(BaseModel):
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context = TextField(null=True)
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up_content = TextField(null=True)
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content_list = TextField(null=True)
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count = IntegerField(default=1)
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last_active_time = FloatField()
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chat_id = TextField(index=True)
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create_date = FloatField(null=True) # 创建日期，允许为空以兼容老数据
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@ -77,6 +77,9 @@ class ExpressionLearner:
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self.express_learn_model: LLMRequest = LLMRequest(
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model_set=model_config.model_task_config.utils, request_type="expression.learner"
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)
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self.summary_model: LLMRequest = LLMRequest(
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model_set=model_config.model_task_config.utils_small, request_type="expression.summary"
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)
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self.embedding_model: LLMRequest = LLMRequest(
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model_set=model_config.model_task_config.embedding, request_type="expression.embedding"
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)
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@ -186,25 +189,13 @@ class ExpressionLearner:
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context,
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up_content,
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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) & (Expression.situation == situation) & (Expression.style == style)
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await self._upsert_expression_record(
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situation=situation,
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style=style,
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context=context,
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up_content=up_content,
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current_time=current_time,
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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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expr_obj = query.get()
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expr_obj.last_active_time = current_time
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expr_obj.save()
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else:
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Expression.create(
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situation=situation,
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style=style,
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last_active_time=current_time,
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chat_id=self.chat_id,
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create_date=current_time, # 手动设置创建日期
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context=context,
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up_content=up_content,
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)
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return learnt_expressions
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@ -362,6 +353,10 @@ class ExpressionLearner:
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logger.error(f"学习表达方式失败,模型生成出错: {e}")
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return None
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expressions: List[Tuple[str, str]] = self.parse_expression_response(response)
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expressions = self._filter_self_reference_styles(expressions)
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if not expressions:
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logger.info("过滤后没有可用的表达方式（style 与机器人名称重复）")
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return None
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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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@ -433,6 +428,153 @@ class ExpressionLearner:
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expressions.append((situation, style))
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return expressions
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def _filter_self_reference_styles(self, expressions: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
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"""
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过滤掉style与机器人名称/昵称重复的表达
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"""
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banned_names = set()
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bot_nickname = (global_config.bot.nickname or "").strip()
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if bot_nickname:
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banned_names.add(bot_nickname)
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alias_names = global_config.bot.alias_names or []
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for alias in alias_names:
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alias = alias.strip()
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if alias:
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banned_names.add(alias)
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banned_casefold = {name.casefold() for name in banned_names if name}
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filtered: List[Tuple[str, str]] = []
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removed_count = 0
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for situation, style in expressions:
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normalized_style = (style or "").strip()
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if normalized_style and normalized_style.casefold() not in banned_casefold:
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filtered.append((situation, style))
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else:
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removed_count += 1
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if removed_count:
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logger.debug(f"已过滤 {removed_count} 条style与机器人名称重复的表达方式")
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return filtered
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async def _upsert_expression_record(
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self,
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situation: str,
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style: str,
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context: str,
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up_content: str,
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current_time: float,
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) -> None:
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expr_obj = (
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Expression.select()
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.where((Expression.chat_id == self.chat_id) & (Expression.style == style))
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.first()
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)
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if expr_obj:
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await self._update_existing_expression(
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expr_obj=expr_obj,
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situation=situation,
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context=context,
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up_content=up_content,
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current_time=current_time,
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)
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return
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await self._create_expression_record(
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situation=situation,
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style=style,
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context=context,
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up_content=up_content,
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current_time=current_time,
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)
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async def _create_expression_record(
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self,
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situation: str,
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style: str,
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context: str,
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up_content: str,
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current_time: float,
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) -> None:
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content_list = [situation]
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formatted_situation = await self._compose_situation_text(content_list, 1, situation)
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Expression.create(
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situation=formatted_situation,
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style=style,
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content_list=json.dumps(content_list, ensure_ascii=False),
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count=1,
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last_active_time=current_time,
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chat_id=self.chat_id,
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create_date=current_time,
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context=context,
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up_content=up_content,
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)
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async def _update_existing_expression(
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self,
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expr_obj: Expression,
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situation: str,
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context: str,
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up_content: str,
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current_time: float,
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) -> None:
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content_list = self._parse_content_list(expr_obj.content_list)
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content_list.append(situation)
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expr_obj.content_list = json.dumps(content_list, ensure_ascii=False)
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expr_obj.count = (expr_obj.count or 0) + 1
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expr_obj.last_active_time = current_time
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expr_obj.context = context
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expr_obj.up_content = up_content
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new_situation = await self._compose_situation_text(
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content_list=content_list,
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count=expr_obj.count,
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fallback=expr_obj.situation,
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)
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expr_obj.situation = new_situation
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expr_obj.save()
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def _parse_content_list(self, stored_list: Optional[str]) -> List[str]:
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if not stored_list:
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return []
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try:
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data = json.loads(stored_list)
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except json.JSONDecodeError:
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return []
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return [str(item) for item in data if isinstance(item, str)] if isinstance(data, list) else []
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async def _compose_situation_text(self, content_list: List[str], count: int, fallback: str = "") -> str:
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sanitized = [c.strip() for c in content_list if c.strip()]
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summary = await self._summarize_situations(sanitized)
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if summary:
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return summary
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return "/".join(sanitized) if sanitized else fallback
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async def _summarize_situations(self, situations: List[str]) -> Optional[str]:
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if not situations:
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return None
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prompt = (
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"请阅读以下多个聊天情境描述，并将它们概括成一句简短的话，"
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"长度不超过20个字，保留共同特点：\n"
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f"{chr(10).join(f'- {s}' for s in situations[-10:])}\n只输出概括内容。"
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)
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try:
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summary, _ = await self.summary_model.generate_response_async(prompt, temperature=0.2)
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summary = summary.strip()
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if summary:
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return summary
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except Exception as e:
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logger.error(f"概括表达情境失败: {e}")
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return None
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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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