.

scripts/rag_build_query.py

@@ -1,9 +1,31 @@
 import os
 import logging
+from typing import List
+import faiss
+from llama_index import (
+    SimpleDirectoryReader,
+    VectorStoreIndex,
+    ServiceContext,
+    StorageContext,
+    PromptTemplate
+)
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+from llama_index.vector_stores.faiss import FaissVectorStore
+from app.core.config import settings  # 确保配置导入
+from scripts.permissions import get_user_allowed_indexes  # 确保权限导入
 
-# 确保路径变量已定义
-USER_DOC_PATH = "docs"
 USER_INDEX_PATH = "index_data"
+USER_DOC_PATH = "docs"
+
+# ✅ 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: "
+        return super()._get_query_embedding(prefix + query)
+
+    def _get_query_embeddings(self, queries: List[str]) -> List[List[float]]:
+        prefix = "Represent this sentence for searching relevant passages: "
+        return super()._get_query_embeddings([prefix + q for q in queries])
 
 def build_user_index(user_id: str):
     # 设置日志