.

app/api/search.py

@@ -3,7 +3,7 @@ from pydantic import BaseModel
 from app.core.embedding import embedder
 from app.core.config import settings
 from llama_index.vector_stores.faiss import FaissVectorStore
-from llama_index import VectorStoreIndex, ServiceContext
+from llama_index import VectorStoreIndex, ServiceContext, StorageContext
 import os
 import logging
 
@@ -30,9 +30,12 @@ def search_docs(request: QueryRequest, user_id: str = Query(..., description="
             logger.error(f"Index not found for user: {user_id} at {index_path}")
             raise HTTPException(status_code=404, detail="用户索引不存在")
 
-        # 加载整个 Faiss 向量存储目录
+        # 创建 StorageContext 并加载 Faiss 向量存储目录
         logger.info(f"Loading Faiss vector store from path: {index_path}")
-        faiss_store = FaissVectorStore.from_persist_dir(index_path)  # 从目录加载
+        storage_context = StorageContext.from_defaults(persist_dir=index_path)
+        
+        # 加载 Faiss 向量存储
+        faiss_store = FaissVectorStore.from_persist_path(storage_context)
         service_context = ServiceContext.from_defaults(embed_model=embedder, llm=None)
         logger.info("Service context created successfully.")