community[patch]: optimize xinference llm import (#25809)

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- [ ] **PR title**: "community: optimize xinference llm import"

- [ ] **PR message**: 
- **Description:** from xinferece_client import RESTfulClient when there
is no importing xinference.
    - **Dependencies:** xinferece_client
- **Why do so:** the total xinference(pip install xinference[all]) is
too heavy for installing, let alone it is useless for langchain user
except RESTfulClient. The modification has maintained consistency with
the xinference embeddings
[embeddings/xinference](../blob/master/libs/community/langchain_community/embeddings/xinference.py#L89).

libs/community/langchain_community/llms/xinference.py

@@ -17,6 +17,12 @@ class Xinference(LLM):
 
        pip install "xinference[all]"
 
+    If you're simply using the services provided by Xinference, you can utilize the xinference_client package:
+
+    .. code-block:: bash
+
+        pip install xinference_client
+
     Check out: https://github.com/xorbitsai/inference
     To run, you need to start a Xinference supervisor on one server and Xinference workers on the other servers
 
@@ -91,11 +97,14 @@ class Xinference(LLM):
     ):
         try:
             from xinference.client import RESTfulClient
-        except ImportError as e:
+        except ImportError:
-            raise ImportError(
+            try:
-                "Could not import RESTfulClient from xinference. Please install it"
+                from xinference_client import RESTfulClient
-                " with `pip install xinference`."
+            except ImportError as e:
-            ) from e
+                raise ImportError(
+                    "Could not import RESTfulClient from xinference. Please install it"
+                    " with `pip install xinference` or `pip install xinference_client`."
+                ) from e
 
         model_kwargs = model_kwargs or {}