fix:修复阈值,降低表达
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@@ -222,7 +222,7 @@ class RelationshipProcessor(BaseProcessor):
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"start_time": time.time(),
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"forget": False,
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})
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if len(self.info_fetching_cache) > 30:
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if len(self.info_fetching_cache) > 20:
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self.info_fetching_cache.pop(0)
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else:
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logger.warning(f"{self.log_prefix} 未找到用户 {person_name} 的ID,跳过调取信息。")
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@@ -181,7 +181,7 @@ class ActionPlanner(BasePlanner):
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prompt = f"{prompt}"
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llm_content, (reasoning_content, _) = await self.planner_llm.generate_response_async(prompt=prompt)
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logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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# logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
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logger.info(f"{self.log_prefix}规划器推理: {reasoning_content}")
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@@ -372,7 +372,7 @@ class DefaultReplyer:
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# 使用相似度匹配选择最相似的表达
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similar_exprs = find_similar_expressions(target_message, learnt_style_expressions, 3)
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for expr in similar_exprs:
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print(f"expr: {expr}")
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# print(f"expr: {expr}")
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if isinstance(expr, dict) and "situation" in expr and "style" in expr:
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style_habbits.append(f"当{expr['situation']}时,使用 {expr['style']}")
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# 2. learnt_grammar_expressions加权随机选2条
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@@ -390,6 +390,8 @@ class DefaultReplyer:
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style_habbits_str = "\n".join(style_habbits)
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grammar_habbits_str = "\n".join(grammar_habbits)
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# 关键词检测与反应
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keywords_reaction_prompt = ""
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