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春河晴
2025-06-10 16:13:31 +09:00
parent 440e8bf7f3
commit 8d9a88a903
70 changed files with 1598 additions and 1642 deletions
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122
src/chat/memory_system/Hippocampus.py
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@@ -346,7 +346,9 @@ 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, (reasoning_content, model_name) = await self.model_summary.generate_response_async(self.find_topic_llm(text, topic_num))
topics_response, (reasoning_content, model_name) = await self.model_summary.generate_response_async(
self.find_topic_llm(text, topic_num)
)
# 提取关键词
keywords = re.findall(r"<([^>]+)>", topics_response)
@@ -701,7 +703,9 @@ 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, (reasoning_content, model_name) = await self.model_summary.generate_response_async(self.find_topic_llm(text, topic_num))
topics_response, (reasoning_content, model_name) = await self.model_summary.generate_response_async(
self.find_topic_llm(text, topic_num)
)
# 提取关键词
keywords = re.findall(r"<([^>]+)>", topics_response)
@@ -893,7 +897,7 @@ class EntorhinalCortex:
# 获取数据库中所有节点和内存中所有节点
db_nodes = {node.concept: node for node in GraphNodes.select()}
memory_nodes = list(self.memory_graph.G.nodes(data=True))
# 批量准备节点数据
nodes_to_create = []
nodes_to_update = []
@@ -929,22 +933,26 @@ class EntorhinalCortex:
continue
if concept not in db_nodes:
nodes_to_create.append({
"concept": concept,
"memory_items": memory_items_json,
"hash": memory_hash,
"created_time": created_time,
"last_modified": last_modified,
})
else:
db_node = db_nodes[concept]
if db_node.hash != memory_hash:
nodes_to_update.append({
nodes_to_create.append(
{
"concept": concept,
"memory_items": memory_items_json,
"hash": memory_hash,
"created_time": created_time,
"last_modified": last_modified,
})
}
)
else:
db_node = db_nodes[concept]
if db_node.hash != memory_hash:
nodes_to_update.append(
{
"concept": concept,
"memory_items": memory_items_json,
"hash": memory_hash,
"last_modified": last_modified,
}
)
# 计算需要删除的节点
memory_concepts = {concept for concept, _ in memory_nodes}
@@ -954,13 +962,13 @@ class EntorhinalCortex:
if nodes_to_create:
batch_size = 100
for i in range(0, len(nodes_to_create), batch_size):
batch = nodes_to_create[i:i + batch_size]
batch = nodes_to_create[i : i + batch_size]
GraphNodes.insert_many(batch).execute()
if nodes_to_update:
batch_size = 100
for i in range(0, len(nodes_to_update), batch_size):
batch = nodes_to_update[i:i + batch_size]
batch = nodes_to_update[i : i + batch_size]
for node_data in batch:
GraphNodes.update(**{k: v for k, v in node_data.items() if k != "concept"}).where(
GraphNodes.concept == node_data["concept"]
@@ -992,22 +1000,26 @@ class EntorhinalCortex:
last_modified = data.get("last_modified", current_time)
if edge_key not in db_edge_dict:
edges_to_create.append({
"source": source,
"target": target,
"strength": strength,
"hash": edge_hash,
"created_time": created_time,
"last_modified": last_modified,
})
edges_to_create.append(
{
"source": source,
"target": target,
"strength": strength,
"hash": edge_hash,
"created_time": created_time,
"last_modified": last_modified,
}
)
elif db_edge_dict[edge_key]["hash"] != edge_hash:
edges_to_update.append({
"source": source,
"target": target,
"strength": strength,
"hash": edge_hash,
"last_modified": last_modified,
})
edges_to_update.append(
{
"source": source,
"target": target,
"strength": strength,
"hash": edge_hash,
"last_modified": last_modified,
}
)
# 计算需要删除的边
memory_edge_keys = {(source, target) for source, target, _ in memory_edges}
@@ -1017,13 +1029,13 @@ class EntorhinalCortex:
if edges_to_create:
batch_size = 100
for i in range(0, len(edges_to_create), batch_size):
batch = edges_to_create[i:i + batch_size]
batch = edges_to_create[i : i + batch_size]
GraphEdges.insert_many(batch).execute()
if edges_to_update:
batch_size = 100
for i in range(0, len(edges_to_update), batch_size):
batch = edges_to_update[i:i + batch_size]
batch = edges_to_update[i : i + batch_size]
for edge_data in batch:
GraphEdges.update(**{k: v for k, v in edge_data.items() if k not in ["source", "target"]}).where(
(GraphEdges.source == edge_data["source"]) & (GraphEdges.target == edge_data["target"])
@@ -1031,9 +1043,7 @@ class EntorhinalCortex:
if edges_to_delete:
for source, target in edges_to_delete:
GraphEdges.delete().where(
(GraphEdges.source == source) & (GraphEdges.target == target)
).execute()
GraphEdges.delete().where((GraphEdges.source == source) & (GraphEdges.target == target)).execute()
end_time = time.time()
logger.success(f"[同步] 总耗时: {end_time - start_time:.2f}秒")
@@ -1069,13 +1079,15 @@ class EntorhinalCortex:
if not memory_items_json:
continue
nodes_data.append({
"concept": concept,
"memory_items": memory_items_json,
"hash": self.hippocampus.calculate_node_hash(concept, memory_items),
"created_time": data.get("created_time", current_time),
"last_modified": data.get("last_modified", current_time),
})
nodes_data.append(
{
"concept": concept,
"memory_items": memory_items_json,
"hash": self.hippocampus.calculate_node_hash(concept, memory_items),
"created_time": data.get("created_time", current_time),
"last_modified": data.get("last_modified", current_time),
}
)
except Exception as e:
logger.error(f"准备节点 {concept} 数据时发生错误: {e}")
continue
@@ -1084,14 +1096,16 @@ class EntorhinalCortex:
edges_data = []
for source, target, data in memory_edges:
try:
edges_data.append({
"source": source,
"target": target,
"strength": data.get("strength", 1),
"hash": self.hippocampus.calculate_edge_hash(source, target),
"created_time": data.get("created_time", current_time),
"last_modified": data.get("last_modified", current_time),
})
edges_data.append(
{
"source": source,
"target": target,
"strength": data.get("strength", 1),
"hash": self.hippocampus.calculate_edge_hash(source, target),
"created_time": data.get("created_time", current_time),
"last_modified": data.get("last_modified", current_time),
}
)
except Exception as e:
logger.error(f"准备边 {source}-{target} 数据时发生错误: {e}")
continue
@@ -1102,7 +1116,7 @@ class EntorhinalCortex:
batch_size = 500 # 增加批量大小
with GraphNodes._meta.database.atomic():
for i in range(0, len(nodes_data), batch_size):
batch = nodes_data[i:i + batch_size]
batch = nodes_data[i : i + batch_size]
GraphNodes.insert_many(batch).execute()
node_end = time.time()
logger.info(f"[数据库] 写入 {len(nodes_data)} 个节点耗时: {node_end - node_start:.2f}秒")
@@ -1113,7 +1127,7 @@ class EntorhinalCortex:
batch_size = 500 # 增加批量大小
with GraphEdges._meta.database.atomic():
for i in range(0, len(edges_data), batch_size):
batch = edges_data[i:i + batch_size]
batch = edges_data[i : i + batch_size]
GraphEdges.insert_many(batch).execute()
edge_end = time.time()
logger.info(f"[数据库] 写入 {len(edges_data)} 条边耗时: {edge_end - edge_start:.2f}秒")