diff --git a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py
index 917feb2df0b..9939fe71f5d 100644
--- a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py
+++ b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py
@@ -13,7 +13,7 @@ from langchain_core.messages import (
 )
 from langchain_core.messages.ai import UsageMetadata
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from pydantic import Field
+from pydantic import ConfigDict, Field
 
 
 class Chat__ModuleName__(BaseChatModel):
@@ -266,7 +266,7 @@ class Chat__ModuleName__(BaseChatModel):
 
     """  # noqa: E501
 
-    model_name: str = Field(alias="model")
+    model: str = Field(alias="model_name")
     """The name of the model"""
     parrot_buffer_length: int
     """The number of characters from the last message of the prompt to be echoed."""
@@ -276,6 +276,10 @@ class Chat__ModuleName__(BaseChatModel):
     stop: Optional[List[str]] = None
     max_retries: int = 2
 
+    model_config = ConfigDict(
+        populate_by_name=True,
+    )
+
     @property
     def _llm_type(self) -> str:
         """Return type of chat model."""
@@ -293,7 +297,7 @@ class Chat__ModuleName__(BaseChatModel):
             # rules in LLM monitoring applications (e.g., in LangSmith users
             # can provide per token pricing for their model and monitor
             # costs for the given LLM.)
-            "model_name": self.model_name,
+            "model": self.model,
         }
 
     def _generate(
diff --git a/libs/standard-tests/tests/unit_tests/custom_chat_model.py b/libs/standard-tests/tests/unit_tests/custom_chat_model.py
index 1791138cf35..032d69b6406 100644
--- a/libs/standard-tests/tests/unit_tests/custom_chat_model.py
+++ b/libs/standard-tests/tests/unit_tests/custom_chat_model.py
@@ -11,7 +11,7 @@ from langchain_core.messages import (
 )
 from langchain_core.messages.ai import UsageMetadata
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from pydantic import Field
+from pydantic import ConfigDict, Field
 
 
 class ChatParrotLink(BaseChatModel):
@@ -33,7 +33,7 @@ class ChatParrotLink(BaseChatModel):
                                  [HumanMessage(content="world")]])
     """
 
-    model_name: str = Field(alias="model")
+    model: str = Field(alias="model_name")
     """The name of the model"""
     parrot_buffer_length: int
     """The number of characters from the last message of the prompt to be echoed."""
@@ -43,6 +43,10 @@ class ChatParrotLink(BaseChatModel):
     stop: Optional[List[str]] = None
     max_retries: int = 2
 
+    model_config = ConfigDict(
+        populate_by_name=True,
+    )
+
     def _generate(
         self,
         messages: List[BaseMessage],
@@ -163,5 +167,5 @@ class ChatParrotLink(BaseChatModel):
             # rules in LLM monitoring applications (e.g., in LangSmith users
             # can provide per token pricing for their model and monitor
             # costs for the given LLM.)
-            "model_name": self.model_name,
+            "model": self.model,
         }