[langchain_community.llms.xinference]: fix error in xinference.py (#29216)

- [ ] **PR title**: [langchain_community.llms.xinference]: fix error in
xinference.py

- [ ] **PR message**:
- The old code raised an ValidationError:
pydantic_core._pydantic_core.ValidationError: 1 validation error for
Xinference when import Xinference from xinference.py. This issue has
been resolved by adjusting it's type and default value.

File "/media/vdc/python/lib/python3.10/site-packages/pydantic/main.py",
line 212, in __init__
validated_self = self.__pydantic_validator__.validate_python(data,
self_instance=self)
pydantic_core._pydantic_core.ValidationError: 1 validation error for
Xinference
        client
Field required [type=missing, input_value={'server_url':
'http://10...t4', 'model_kwargs': {}}, input_type=dict]
For further information visit https://errors.pydantic.dev/2.9/v/missing

- [ ] **tests**:

       from langchain_community.llms import Xinference
       llm = Xinference(
server_url="http://0.0.0.0:9997", # replace your xinference server url
model_uid={model_uid} # replace model_uid with the model UID return from
launching the model
         )

Author: TheSongg

libs/community/langchain_community/llms/xinference.py

@@ -81,7 +81,7 @@ class Xinference(LLM):
 
     """  # noqa: E501
 
-    client: Any
+    client: Optional[Any] = None
     server_url: Optional[str]
     """URL of the xinference server"""
     model_uid: Optional[str]
@@ -156,6 +156,8 @@ def _call(
         Returns:
             The generated string by the model.
         """
+        if self.client is None:
+            raise ValueError("Client is not initialized!")
         model = self.client.get_model(self.model_uid)
 
         generate_config: "LlamaCppGenerateConfig" = kwargs.get("generate_config", {})