.

scripts/rag_build_query.py

@@ -19,7 +19,7 @@ from scripts.permissions import get_user_allowed_indexes
 USER_INDEX_PATH = "index_data"
 USER_DOC_PATH = "docs"
 
-# ✅ 替代 CustomEmbedding，用于 bge-m3 模型，自动加前缀
+# ✅ BGE-m3 模型嵌入类，加前缀
 class BGEEmbedding(HuggingFaceEmbedding):
     def _get_query_embedding(self, query: str) -> List[float]:
         prefix = "Represent this sentence for searching relevant passages: "
@@ -36,11 +36,9 @@ def build_user_index(user_id: str):
     
     documents = SimpleDirectoryReader(doc_dir).load_data()
     embed_model = BGEEmbedding(model_name=settings.MODEL_NAME)
-
     service_context = ServiceContext.from_defaults(embed_model=embed_model, llm=None)
 
-    # ✅ 指定正确维度：bge-m3 是 1024
-    faiss_index = faiss.IndexFlatL2(1024)
+    faiss_index = faiss.IndexFlatL2(1024)  # ✅ bge-m3 是 1024维
     vector_store = FaissVectorStore(faiss_index=faiss_index)
 
     index = VectorStoreIndex.from_documents(
@@ -50,7 +48,7 @@ def build_user_index(user_id: str):
     )
     
     index_path = os.path.join(USER_INDEX_PATH, f"{user_id}.index")
-    faiss.write_index(index.vector_store.index, index_path)
+    faiss.write_index(vector_store.index, index_path)  # ✅ 用传入的 vector_store
     print(f"[BUILD] 为用户 {user_id} 构建并保存了索引 → {index_path}")
 
 def query_user_rag(user_id: str, question: str, top_k: int = 4) -> str:
@@ -59,7 +57,6 @@ def query_user_rag(user_id: str, question: str, top_k: int = 4) -> str:
 
     all_nodes = []
 
-    # 加载用户主索引
     index_path = os.path.join(USER_INDEX_PATH, f"{user_id}.index")
     if not os.path.exists(index_path):
         raise FileNotFoundError(f"[ERROR] 用户 {user_id} 的索引不存在")
@@ -67,7 +64,6 @@ def query_user_rag(user_id: str, question: str, top_k: int = 4) -> str:
     user_index = VectorStoreIndex.from_vector_store(user_store, service_context=service_context)
     all_nodes += user_index.as_retriever(similarity_top_k=top_k).retrieve(question)
 
-    # 加载共享索引
     shared_indexes = get_user_allowed_indexes(user_id)
     if shared_indexes:
         for shared_name in shared_indexes:
@@ -79,7 +75,6 @@ def query_user_rag(user_id: str, question: str, top_k: int = 4) -> str:
     else:
         print(f"[INFO] 用户 {user_id} 没有共享索引权限")
 
-    # 合并 + 按 score 排序
     sorted_nodes = sorted(all_nodes, key=lambda n: -(n.score or 0))
     top_nodes = sorted_nodes[:top_k]