.

scripts/rag_build_query.py

@@ -16,7 +16,7 @@ from scripts.permissions import get_user_allowed_indexes
 USER_INDEX_PATH = "index_data"
 USER_DOC_PATH = "docs"
 
-# ✅ 自动加前缀的 bge-m3 embedding
+# ✅ 自动加前缀的 BGE-m3 embedding 封装类
 class BGEEmbedding(HuggingFaceEmbedding):
     def _get_query_embedding(self, query: str) -> List[float]:
         prefix = "Represent this sentence for searching relevant passages: "
@@ -38,16 +38,19 @@ def build_user_index(user_id: str):
     faiss_index = faiss.IndexFlatL2(1024)
     vector_store = FaissVectorStore(faiss_index=faiss_index)
     persist_dir = os.path.join(USER_INDEX_PATH, user_id)
+    os.makedirs(persist_dir, exist_ok=True)
+
     storage_context = StorageContext.from_defaults(
         persist_dir=persist_dir,
-        vector_store=vector_store
+        vector_store=vector_store,
     )
 
     index = VectorStoreIndex.from_documents(
         documents,
-        storage_context=storage_context,
-        service_context=service_context
+        service_context=service_context,
+        storage_context=storage_context
     )
+
     index.persist(persist_dir=persist_dir)
     print(f"[BUILD] 为用户 {user_id} 构建并保存了完整索引 → {persist_dir}")
 
@@ -65,15 +68,12 @@ def query_user_rag(user_id: str, question: str, top_k: int = 4) -> str:
     all_nodes = index.as_retriever(similarity_top_k=top_k).retrieve(question)
 
     shared_indexes = get_user_allowed_indexes(user_id)
-    if shared_indexes:
-        for shared_name in shared_indexes:
-            shared_path = os.path.join(USER_INDEX_PATH, shared_name)
-            if os.path.exists(shared_path) and shared_path != persist_dir:
-                shared_storage = StorageContext.from_defaults(persist_dir=shared_path)
-                shared_index = VectorStoreIndex.load_from_storage(shared_storage, service_context=service_context)
-                all_nodes += shared_index.as_retriever(similarity_top_k=top_k).retrieve(question)
-    else:
-        print(f"[INFO] 用户 {user_id} 没有共享索引权限")
+    for shared_name in shared_indexes:
+        shared_dir = os.path.join(USER_INDEX_PATH, shared_name)
+        if os.path.exists(shared_dir) and shared_dir != persist_dir:
+            shared_context = StorageContext.from_defaults(persist_dir=shared_dir)
+            shared_index = VectorStoreIndex.load_from_storage(shared_context, service_context=service_context)
+            all_nodes += shared_index.as_retriever(similarity_top_k=top_k).retrieve(question)
 
     sorted_nodes = sorted(all_nodes, key=lambda n: -(n.score or 0))
     top_nodes = sorted_nodes[:top_k]