From 1966b4eaf88fc2715c8f0b7fca5eb0d4436b6f5d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=A2=A8=E6=A2=93=E6=9F=92?= <1787882683@qq.com>
Date: Tue, 15 Jul 2025 17:13:15 +0800
Subject: [PATCH] fix: remove unused imports and comments

---
 src/chat/knowledge/embedding_store.py | 11 ++++-------
 src/config/official_configs.py        |  3 +++
 template/bot_config_template.toml     |  3 ++-
 3 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/src/chat/knowledge/embedding_store.py b/src/chat/knowledge/embedding_store.py
index b827f4b40..3eb466d21 100644
--- a/src/chat/knowledge/embedding_store.py
+++ b/src/chat/knowledge/embedding_store.py
@@ -11,7 +11,7 @@ import pandas as pd
 import faiss
 
 # from .llm_client import LLMClient
-from .lpmmconfig import global_config
+# from .lpmmconfig import global_config
 from .utils.hash import get_sha256
 from .global_logger import logger
 from rich.traceback import install
@@ -27,15 +27,12 @@ from rich.progress import (
 )
 from src.manager.local_store_manager import local_storage
 from src.chat.utils.utils import get_embedding
+from src.config.config import global_config
 
 
 install(extra_lines=3)
 ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-EMBEDDING_DATA_DIR = (
-    os.path.join(ROOT_PATH, "data", "embedding")
-    if global_config["persistence"]["embedding_data_dir"] is None
-    else os.path.join(ROOT_PATH, global_config["persistence"]["embedding_data_dir"])
-)
+EMBEDDING_DATA_DIR = os.path.join(ROOT_PATH, "data", "embedding")
 EMBEDDING_DATA_DIR_STR = str(EMBEDDING_DATA_DIR).replace("\\", "/")
 TOTAL_EMBEDDING_TIMES = 3  # 统计嵌入次数
 
@@ -260,7 +257,7 @@ class EmbeddingStore:
         # L2归一化
         faiss.normalize_L2(embeddings)
         # 构建索引
-        self.faiss_index = faiss.IndexFlatIP(global_config["embedding"]["dimension"])
+        self.faiss_index = faiss.IndexFlatIP(global_config.lpmm_knowledge.embedding_dimension)
         self.faiss_index.add(embeddings)
 
     def search_top_k(self, query: List[float], k: int) -> List[Tuple[str, float]]:
diff --git a/src/config/official_configs.py b/src/config/official_configs.py
index 4462daba7..25bef7e89 100644
--- a/src/config/official_configs.py
+++ b/src/config/official_configs.py
@@ -589,6 +589,9 @@ class LPMMKnowledgeConfig(ConfigBase):
     qa_res_top_k: int = 10
     """QA最终结果的Top K数量"""
 
+    embedding_dimension: int = 1024
+    """嵌入向量维度，应该与模型的输出维度一致"""
+
 
 @dataclass
 class ModelConfig(ConfigBase):
diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml
index 41fc80d9b..e54c440b5 100644
--- a/template/bot_config_template.toml
+++ b/template/bot_config_template.toml
@@ -1,5 +1,5 @@
 [inner]
-version = "4.1.1"
+version = "4.2.0"
 
 #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 #如果你想要修改配置文件，请在修改后将version的值进行变更
@@ -158,6 +158,7 @@ qa_paragraph_node_weight = 0.05 # 段落节点权重（在图搜索&PPR计算中
 qa_ent_filter_top_k = 10 # 实体过滤TopK
 qa_ppr_damping = 0.8 # PPR阻尼系数
 qa_res_top_k = 3 # 最终提供的文段TopK
+embedding_dimension = 1024 # 嵌入向量维度,应该与模型的输出维度一致
 
 # keyword_rules 用于设置关键词触发的额外回复知识
 # 添加新规则方法：在 keyword_rules 数组中增加一项，格式如下：