multiple: pydantic 2 compatibility, v0.3 (#26443)

Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Dan O'Donovan <dan.odonovan@gmail.com>
Co-authored-by: Tom Daniel Grande <tomdgrande@gmail.com>
Co-authored-by: Grande <Tom.Daniel.Grande@statsbygg.no>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com>
Co-authored-by: ZhangShenao <15201440436@163.com>
Co-authored-by: Friso H. Kingma <fhkingma@gmail.com>
Co-authored-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
Co-authored-by: Morgante Pell <morgantep@google.com>

libs/community/langchain_community/retrievers/docarray.py

@@ -7,6 +7,7 @@ from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.retrievers import BaseRetriever
 from langchain_core.utils.pydantic import get_fields
+from pydantic import ConfigDict
 
 from langchain_community.vectorstores.utils import maximal_marginal_relevance
 
@@ -37,7 +38,7 @@ class DocArrayRetriever(BaseRetriever):
         top_k: Number of documents to return
     """
 
-    index: Any
+    index: Any = None
     embeddings: Embeddings
     search_field: str
     content_field: str
@@ -45,8 +46,9 @@ class DocArrayRetriever(BaseRetriever):
     top_k: int = 1
     filters: Optional[Any] = None
 
-    class Config:
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(
+        arbitrary_types_allowed=True,
+    )
 
     def _get_relevant_documents(
         self,