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/embeddings/deepinfra.py

@@ -2,8 +2,8 @@ from typing import Any, Dict, List, Mapping, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import get_from_dict_or_env, pre_init
+from pydantic import BaseModel, ConfigDict
 
 DEFAULT_MODEL_ID = "sentence-transformers/clip-ViT-B-32"
 MAX_BATCH_SIZE = 1024
@@ -54,8 +54,7 @@ class DeepInfraEmbeddings(BaseModel, Embeddings):
     batch_size: int = MAX_BATCH_SIZE
     """Batch size for embedding requests."""
 
-    class Config:
-        extra = "forbid"
+    model_config = ConfigDict(extra="forbid", protected_namespaces=())
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict: