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feat：拆分重命名模型配置，修复动作恢复问题

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This commit is contained in:
SengokuCola
2025-05-27 14:28:41 +08:00
parent 5b8e4c0690
commit 0391111c82
19 changed files with 119 additions and 118 deletions
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10
src/chat/memory_system/Hippocampus.py
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@@ -193,7 +193,6 @@ class MemoryGraph:
class Hippocampus:
def __init__(self):
self.memory_graph = MemoryGraph()
self.llm_topic_judge = None
self.model_summary = None
self.entorhinal_cortex = None
self.parahippocampal_gyrus = None
@@ -205,8 +204,7 @@ class Hippocampus:
# 从数据库加载记忆图
self.entorhinal_cortex.sync_memory_from_db()
# TODO: API-Adapter修改标记
self.llm_topic_judge = LLMRequest(global_config.model.topic_judge, request_type="memory")
self.model_summary = LLMRequest(global_config.model.summary, request_type="memory")
self.model_summary = LLMRequest(global_config.model.memory_summary, request_type="memory")
def get_all_node_names(self) -> list:
"""获取记忆图中所有节点的名字列表"""
@@ -344,7 +342,7 @@ class Hippocampus:
# 使用LLM提取关键词
topic_num = min(5, max(1, int(len(text) * 0.1))) # 根据文本长度动态调整关键词数量
# logger.info(f"提取关键词数量: {topic_num}")
topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(text, topic_num))
topics_response = await self.model_summary.generate_response(self.find_topic_llm(text, topic_num))
# 提取关键词
keywords = re.findall(r"<([^>]+)>", topics_response[0])
@@ -699,7 +697,7 @@ class Hippocampus:
# 使用LLM提取关键词
topic_num = min(5, max(1, int(len(text) * 0.1))) # 根据文本长度动态调整关键词数量
# logger.info(f"提取关键词数量: {topic_num}")
topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(text, topic_num))
topics_response = await self.model_summary.generate_response(self.find_topic_llm(text, topic_num))
# 提取关键词
keywords = re.findall(r"<([^>]+)>", topics_response[0])
@@ -1126,7 +1124,7 @@ class ParahippocampalGyrus:
# 2. 使用LLM提取关键主题
topic_num = self.hippocampus.calculate_topic_num(input_text, compress_rate)
topics_response = await self.hippocampus.llm_topic_judge.generate_response(
topics_response = await self.hippocampus.model_summary.generate_response(
self.hippocampus.find_topic_llm(input_text, topic_num)
)