feat: 移除不必要的命名空间导入，优化本地存储初始化

scripts/import_openie.py

@@ -10,13 +10,14 @@ from time import sleep
 
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 
-from src.chat.knowledge.lpmmconfig import PG_NAMESPACE, global_config
+from src.chat.knowledge.lpmmconfig import global_config
 from src.chat.knowledge.embedding_store import EmbeddingManager
 from src.chat.knowledge.llm_client import LLMClient
 from src.chat.knowledge.open_ie import OpenIE
 from src.chat.knowledge.kg_manager import KGManager
 from src.common.logger import get_logger
 from src.chat.knowledge.utils.hash import get_sha256
+from src.manager.local_store_manager import local_storage
 
 
 # 添加项目根目录到 sys.path
@@ -61,7 +62,7 @@ def hash_deduplicate(
     for _, (raw_paragraph, triple_list) in enumerate(zip(raw_paragraphs.values(), triple_list_data.values())):
         # 段落hash
         paragraph_hash = get_sha256(raw_paragraph)
-        if f"{PG_NAMESPACE}-{paragraph_hash}" in stored_pg_hashes and paragraph_hash in stored_paragraph_hashes:
+        if f"{local_storage['pg_namespace']}-{paragraph_hash}" in stored_pg_hashes and paragraph_hash in stored_paragraph_hashes:
             continue
         new_raw_paragraphs[paragraph_hash] = raw_paragraph
         new_triple_list_data[paragraph_hash] = triple_list
@@ -228,7 +229,7 @@ def main():  # sourcery skip: dict-comprehension
 
     # 数据比对：Embedding库与KG的段落hash集合
     for pg_hash in kg_manager.stored_paragraph_hashes:
-        key = f"{PG_NAMESPACE}-{pg_hash}"
+        key = f"{local_storage['pg_namespace']}-{pg_hash}"
         if key not in embed_manager.stored_pg_hashes:
             logger.warning(f"KG中存在Embedding库中不存在的段落：{key}")
 

src/chat/knowledge/embedding_store.py

@@ -11,7 +11,7 @@ import pandas as pd
 import faiss
 
 from .llm_client import LLMClient
-from .lpmmconfig import ENT_NAMESPACE, PG_NAMESPACE, REL_NAMESPACE, global_config
+from .lpmmconfig import global_config
 from .utils.hash import get_sha256
 from .global_logger import logger
 from rich.traceback import install
@@ -25,6 +25,9 @@ from rich.progress import (
     SpinnerColumn,
     TextColumn,
 )
+from src.manager.local_store_manager import local_storage
+from src.llm_models.utils_model import LLMRequest
+
 
 install(extra_lines=3)
 ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
@@ -90,11 +93,11 @@ class EmbeddingStore:
         self.namespace = namespace
         self.llm_client = llm_client
         self.dir = dir_path
-        self.embedding_file_path = dir_path + "/" + namespace + ".parquet"
+        self.embedding_file_path = f"{dir_path}/{namespace}.parquet"
-        self.index_file_path = dir_path + "/" + namespace + ".index"
+        self.index_file_path = f"{dir_path}/{namespace}.index"
         self.idx2hash_file_path = dir_path + "/" + namespace + "_i2h.json"
 
-        self.store = dict()
+        self.store = {}
 
         self.faiss_index = None
         self.idx2hash = None
@@ -296,17 +299,17 @@ class EmbeddingManager:
     def __init__(self, llm_client: LLMClient):
         self.paragraphs_embedding_store = EmbeddingStore(
             llm_client,
-            PG_NAMESPACE,
+            local_storage['pg_namespace'],
             EMBEDDING_DATA_DIR_STR,
         )
         self.entities_embedding_store = EmbeddingStore(
             llm_client,
-            ENT_NAMESPACE,
+            local_storage['pg_namespace'],
             EMBEDDING_DATA_DIR_STR,
         )
         self.relation_embedding_store = EmbeddingStore(
             llm_client,
-            REL_NAMESPACE,
+            local_storage['pg_namespace'],
             EMBEDDING_DATA_DIR_STR,
         )
         self.stored_pg_hashes = set()

src/chat/knowledge/kg_manager.py

@@ -20,22 +20,16 @@ from quick_algo import di_graph, pagerank
 
 from .utils.hash import get_sha256
 from .embedding_store import EmbeddingManager, EmbeddingStoreItem
-from .lpmmconfig import (
+from .lpmmconfig import global_config
-    ENT_NAMESPACE,
+from src.manager.local_store_manager import local_storage
-    PG_NAMESPACE,
-    RAG_ENT_CNT_NAMESPACE,
-    RAG_GRAPH_NAMESPACE,
-    RAG_PG_HASH_NAMESPACE,
-    global_config,
-)
 
 from .global_logger import logger
 
-ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
+
 KG_DIR = (
-    os.path.join(ROOT_PATH, "data/rag")
+    os.path.join(local_storage['root_path'], "data/rag")
     if global_config["persistence"]["rag_data_dir"] is None
-    else os.path.join(ROOT_PATH, global_config["persistence"]["rag_data_dir"])
+    else os.path.join(local_storage['root_path'], global_config["persistence"]["rag_data_dir"])
 )
 KG_DIR_STR = str(KG_DIR).replace("\\", "/")
 
@@ -46,15 +40,15 @@ class KGManager:
         # 存储段落的hash值，用于去重
         self.stored_paragraph_hashes = set()
         # 实体出现次数
-        self.ent_appear_cnt = dict()
+        self.ent_appear_cnt = {}
         # KG
         self.graph = di_graph.DiGraph()
 
         # 持久化相关
         self.dir_path = KG_DIR_STR
-        self.graph_data_path = self.dir_path + "/" + RAG_GRAPH_NAMESPACE + ".graphml"
+        self.graph_data_path = self.dir_path + "/" + local_storage['rag_graph_namespace'] + ".graphml"
-        self.ent_cnt_data_path = self.dir_path + "/" + RAG_ENT_CNT_NAMESPACE + ".parquet"
+        self.ent_cnt_data_path = self.dir_path + "/" + local_storage['rag_ent_cnt_namespace'] + ".parquet"
-        self.pg_hash_file_path = self.dir_path + "/" + RAG_PG_HASH_NAMESPACE + ".json"
+        self.pg_hash_file_path = self.dir_path + "/" + local_storage['rag_pg_hash_namespace'] + ".json"
 
     def save_to_file(self):
         """将KG数据保存到文件"""
@@ -109,8 +103,8 @@ class KGManager:
                     # 避免自连接
                     continue
                 # 一个triple就是一条边（同时构建双向联系）
-                hash_key1 = ENT_NAMESPACE + "-" + get_sha256(triple[0])
+                hash_key1 = local_storage['ent_namespace'] + "-" + get_sha256(triple[0])
-                hash_key2 = ENT_NAMESPACE + "-" + get_sha256(triple[2])
+                hash_key2 = local_storage['ent_namespace'] + "-" + get_sha256(triple[2])
                 node_to_node[(hash_key1, hash_key2)] = node_to_node.get((hash_key1, hash_key2), 0) + 1.0
                 node_to_node[(hash_key2, hash_key1)] = node_to_node.get((hash_key2, hash_key1), 0) + 1.0
                 entity_set.add(hash_key1)
@@ -128,8 +122,8 @@ class KGManager:
         """构建实体节点与文段节点之间的关系"""
         for idx in triple_list_data:
             for triple in triple_list_data[idx]:
-                ent_hash_key = ENT_NAMESPACE + "-" + get_sha256(triple[0])
+                ent_hash_key = local_storage['ent_namespace'] + "-" + get_sha256(triple[0])
-                pg_hash_key = PG_NAMESPACE + "-" + str(idx)
+                pg_hash_key = local_storage['pg_namespace'] + "-" + str(idx)
                 node_to_node[(ent_hash_key, pg_hash_key)] = node_to_node.get((ent_hash_key, pg_hash_key), 0) + 1.0
 
     @staticmethod
@@ -144,8 +138,8 @@ class KGManager:
         ent_hash_list = set()
         for triple_list in triple_list_data.values():
             for triple in triple_list:
-                ent_hash_list.add(ENT_NAMESPACE + "-" + get_sha256(triple[0]))
+                ent_hash_list.add(local_storage['ent_namespace'] + "-" + get_sha256(triple[0]))
-                ent_hash_list.add(ENT_NAMESPACE + "-" + get_sha256(triple[2]))
+                ent_hash_list.add(local_storage['ent_namespace'] + "-" + get_sha256(triple[2]))
         ent_hash_list = list(ent_hash_list)
 
         synonym_hash_set = set()
@@ -250,7 +244,7 @@ class KGManager:
         for src_tgt in node_to_node.keys():
             for node_hash in src_tgt:
                 if node_hash not in existed_nodes:
-                    if node_hash.startswith(ENT_NAMESPACE):
+                    if node_hash.startswith(local_storage['ent_namespace']):
                         # 新增实体节点
                         node = embedding_manager.entities_embedding_store.store[node_hash]
                         assert isinstance(node, EmbeddingStoreItem)
@@ -259,7 +253,7 @@ class KGManager:
                         node_item["type"] = "ent"
                         node_item["create_time"] = now_time
                         self.graph.update_node(node_item)
-                    elif node_hash.startswith(PG_NAMESPACE):
+                    elif node_hash.startswith(local_storage['pg_namespace']):
                         # 新增文段节点
                         node = embedding_manager.paragraphs_embedding_store.store[node_hash]
                         assert isinstance(node, EmbeddingStoreItem)
@@ -340,7 +334,7 @@ class KGManager:
             # 关系三元组
             triple = relation[2:-2].split("', '")
             for ent in [(triple[0]), (triple[2])]:
-                ent_hash = ENT_NAMESPACE + "-" + get_sha256(ent)
+                ent_hash = local_storage['ent_namespace'] + "-" + get_sha256(ent)
                 if ent_hash in existed_nodes:  # 该实体需在KG中存在
                     if ent_hash not in ent_sim_scores:  # 尚未记录的实体
                         ent_sim_scores[ent_hash] = []
@@ -418,7 +412,7 @@ class KGManager:
         # 获取最终结果
         # 从搜索结果中提取文段节点的结果
         passage_node_res = [
-            (node_key, score) for node_key, score in ppr_res.items() if node_key.startswith(PG_NAMESPACE)
+            (node_key, score) for node_key, score in ppr_res.items() if node_key.startswith(local_storage['pg_namespace'])
         ]
         del ppr_res
 

src/chat/knowledge/knowledge_lib.py

@@ -1,4 +1,4 @@
-from src.chat.knowledge.lpmmconfig import PG_NAMESPACE, global_config
+from src.chat.knowledge.lpmmconfig import global_config
 from src.chat.knowledge.embedding_store import EmbeddingManager
 from src.chat.knowledge.llm_client import LLMClient
 from src.chat.knowledge.mem_active_manager import MemoryActiveManager
@@ -6,10 +6,83 @@ from src.chat.knowledge.qa_manager import QAManager
 from src.chat.knowledge.kg_manager import KGManager
 from src.chat.knowledge.global_logger import logger
 from src.config.config import global_config as bot_global_config
-# try:
+from src.manager.local_store_manager import local_storage
-#     import quick_algo
+import os
-# except ImportError:
+
-#     print("quick_algo not found, please install it first")
+INVALID_ENTITY = [
+    "",
+    "你",
+    "他",
+    "她",
+    "它",
+    "我们",
+    "你们",
+    "他们",
+    "她们",
+    "它们",
+]
+PG_NAMESPACE = "paragraph"
+ENT_NAMESPACE = "entity"
+REL_NAMESPACE = "relation"
+
+RAG_GRAPH_NAMESPACE = "rag-graph"
+RAG_ENT_CNT_NAMESPACE = "rag-ent-cnt"
+RAG_PG_HASH_NAMESPACE = "rag-pg-hash"
+
+
+ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
+
+def _initialize_knowledge_local_storage():
+    """
+    初始化知识库相关的本地存储配置
+    使用字典批量设置，避免重复的if判断
+    """
+    # 定义所有需要初始化的配置项
+    default_configs = {
+        # 路径配置
+        'root_path': ROOT_PATH,
+        'data_path': f"{ROOT_PATH}/data",
+        'lpmm_raw_data_path': f"{ROOT_PATH}/data/raw_data",
+        'lpmm_openie_data_path': f"{ROOT_PATH}/data/openie",
+        'lpmm_embedding_data_dir': f"{ROOT_PATH}/data/embedding",
+        'lpmm_rag_data_dir': f"{ROOT_PATH}/data/rag",
+        
+        # 实体和命名空间配置
+        'lpmm_invalid_entity': INVALID_ENTITY,
+        'pg_namespace': PG_NAMESPACE,
+        'ent_namespace': ENT_NAMESPACE,
+        'rel_namespace': REL_NAMESPACE,
+        
+        # RAG相关命名空间配置
+        'rag_graph_namespace': RAG_GRAPH_NAMESPACE,
+        'rag_ent_cnt_namespace': RAG_ENT_CNT_NAMESPACE,
+        'rag_pg_hash_namespace': RAG_PG_HASH_NAMESPACE
+    }
+    
+    # 日志级别映射：重要配置用info，其他用debug
+    important_configs = {'root_path', 'data_path'}
+    
+    # 批量设置配置项
+    initialized_count = 0
+    for key, default_value in default_configs.items():
+        if local_storage.get(key) is None:
+            local_storage.set(key, default_value)
+            
+            # 根据重要性选择日志级别
+            if key in important_configs:
+                logger.info(f"设置{key}: {default_value}")
+            else:
+                logger.debug(f"设置{key}: {default_value}")
+            
+            initialized_count += 1
+    
+    if initialized_count > 0:
+        logger.info(f"知识库本地存储初始化完成，共设置 {initialized_count} 项配置")
+    else:
+        logger.debug("知识库本地存储配置已存在，跳过初始化")
+    
+# 初始化本地存储路径
+_initialize_knowledge_local_storage()
 
 # 检查LPMM知识库是否启用
 if bot_global_config.lpmm_knowledge.enable: