community[patch]: Support Streaming in Azure Machine Learning (#18246)

- [x] **PR title**: "community: Support streaming in Azure ML and few
naming changes"

- [x] **PR message**:
- **Description:** Added support for streaming for azureml_endpoint.
Also, renamed and AzureMLEndpointApiType.realtime to
AzureMLEndpointApiType.dedicated. Also, added new classes
CustomOpenAIChatContentFormatter and CustomOpenAIContentFormatter and
updated the classes LlamaChatContentFormatter and LlamaContentFormatter
to now show a deprecated warning message when instantiated.

---------

Co-authored-by: Sachin Paryani <saparan@microsoft.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/community/tests/integration_tests/chat_models/test_azureml_endpoint.py

@@ -5,13 +5,15 @@ from langchain_core.outputs import ChatGeneration, LLMResult
 
 from langchain_community.chat_models.azureml_endpoint import (
     AzureMLChatOnlineEndpoint,
-    LlamaChatContentFormatter,
+    CustomOpenAIChatContentFormatter,
 )
 
 
 def test_llama_call() -> None:
     """Test valid call to Open Source Foundation Model."""
-    chat = AzureMLChatOnlineEndpoint(content_formatter=LlamaChatContentFormatter())
+    chat = AzureMLChatOnlineEndpoint(
+        content_formatter=CustomOpenAIChatContentFormatter()
+    )
     response = chat.invoke([HumanMessage(content="Foo")])
     assert isinstance(response, BaseMessage)
     assert isinstance(response.content, str)
@@ -19,7 +21,9 @@ def test_llama_call() -> None:
 
 def test_temperature_kwargs() -> None:
     """Test that timeout kwarg works."""
-    chat = AzureMLChatOnlineEndpoint(content_formatter=LlamaChatContentFormatter())
+    chat = AzureMLChatOnlineEndpoint(
+        content_formatter=CustomOpenAIChatContentFormatter()
+    )
     response = chat.invoke([HumanMessage(content="FOO")], temperature=0.8)
     assert isinstance(response, BaseMessage)
     assert isinstance(response.content, str)
@@ -27,7 +31,9 @@ def test_temperature_kwargs() -> None:
 
 def test_message_history() -> None:
     """Test that multiple messages works."""
-    chat = AzureMLChatOnlineEndpoint(content_formatter=LlamaChatContentFormatter())
+    chat = AzureMLChatOnlineEndpoint(
+        content_formatter=CustomOpenAIChatContentFormatter()
+    )
     response = chat.invoke(
         [
             HumanMessage(content="Hello."),
@@ -40,7 +46,9 @@ def test_message_history() -> None:
 
 
 def test_multiple_messages() -> None:
-    chat = AzureMLChatOnlineEndpoint(content_formatter=LlamaChatContentFormatter())
+    chat = AzureMLChatOnlineEndpoint(
+        content_formatter=CustomOpenAIChatContentFormatter()
+    )
     message = HumanMessage(content="Hi!")
     response = chat.generate([[message], [message]])