handle the same langchain Document issue

src/vectorstore.py

@@ -16,11 +16,15 @@ if hasattr(torch.backends, 'mps'):
     torch.backends.mps.is_available = lambda: False
 
 from langchain_qdrant import QdrantVectorStore
-from langchain.docstore.document import Document
 from langchain_core.embeddings import Embeddings
 from sentence_transformers import SentenceTransformer
 from langchain_huggingface import HuggingFaceEmbeddings
 
+try:
+    from langchain.docstore.document import Document
+except:
+    from langchain_core.documents import Document
+    
 
 class MatryoshkaEmbeddings(Embeddings):
     """Custom embeddings class that supports Matryoshka dimension truncation."""