修改了模型命名
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@@ -132,8 +132,8 @@ class Memory_graph:
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class Hippocampus:
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def __init__(self,memory_graph:Memory_graph):
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self.memory_graph = memory_graph
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self.llm_model_get_topic = LLM_request(model = global_config.llm_normal_minor,temperature=0.5)
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self.llm_model_summary = LLM_request(model = global_config.llm_normal,temperature=0.5)
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self.llm_topic_judge = LLM_request(model = global_config.llm_topic_judge,temperature=0.5)
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self.llm_summary_by_topic = LLM_request(model = global_config.llm_summary_by_topic,temperature=0.5)
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def get_all_node_names(self) -> list:
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"""获取记忆图中所有节点的名字列表
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@@ -179,7 +179,7 @@ class Hippocampus:
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#获取topics
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topic_num = self.calculate_topic_num(input_text, compress_rate)
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topics_response = await self.llm_model_get_topic.generate_response(self.find_topic_llm(input_text, topic_num))
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topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(input_text, topic_num))
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# 修改话题处理逻辑
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# 定义需要过滤的关键词
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filter_keywords = ['表情包', '图片', '回复', '聊天记录']
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@@ -196,7 +196,7 @@ class Hippocampus:
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for topic in filtered_topics:
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topic_what_prompt = self.topic_what(input_text, topic)
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# 创建异步任务
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task = self.llm_model_summary.generate_response_async(topic_what_prompt)
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task = self.llm_summary_by_topic.generate_response_async(topic_what_prompt)
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tasks.append((topic.strip(), task))
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# 等待所有任务完成
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@@ -506,7 +506,7 @@ class Hippocampus:
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Returns:
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list: 识别出的主题列表
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"""
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topics_response = await self.llm_model_get_topic.generate_response(self.find_topic_llm(text, 5))
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topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(text, 5))
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# print(f"话题: {topics_response[0]}")
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topics = [topic.strip() for topic in topics_response[0].replace(",", ",").replace("、", ",").replace(" ", ",").split(",") if topic.strip()]
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# print(f"话题: {topics}")
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