From a90ee4984852d7f63d6427c4288e12cf7276bc44 Mon Sep 17 00:00:00 2001 From: hailin Date: Sat, 10 May 2025 02:57:56 +0800 Subject: [PATCH] . --- app/api/search.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/app/api/search.py b/app/api/search.py index cfe5d7b..010dc1c 100644 --- a/app/api/search.py +++ b/app/api/search.py @@ -4,7 +4,6 @@ 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.embeddings.huggingface import HuggingFaceEmbedding import os import logging @@ -22,18 +21,18 @@ def search_docs(request: QueryRequest, user_id: str = Query(..., description=" try: logger.info(f"Received search request from user: {user_id} with query: {request.query}") - # 修正后的索引路径，确保指向具体的 index.faiss 文件 - index_path = os.path.join("index_data", user_id, "index.faiss") # 指向文件，而非目录 + # 修正后的索引路径，确保指向整个目录，而不是单个文件 + index_path = os.path.join("index_data", user_id) # 使用整个目录路径 logger.info(f"Looking for index at path: {index_path}") - # 检查索引是否存在 + # 检查索引目录是否存在 if not os.path.exists(index_path): 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") - # 构建 LlamaIndex 检索器 + # 加载整个 Faiss 向量存储目录 logger.info(f"Loading Faiss vector store from path: {index_path}") - faiss_store = FaissVectorStore.from_persist_path(index_path) + faiss_store = FaissVectorStore.from_persist_dir(index_path) # 从目录加载 service_context = ServiceContext.from_defaults(embed_model=embedder, llm=None) logger.info("Service context created successfully.")