Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747)

* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse

Simplify the public API by removing redundant 'Chat' prefix from core types:
- ChatAgent -> Agent
- RawChatAgent -> RawAgent
- ChatMessage -> Message
- ChatClientProtocol -> SupportsChatGetResponse

Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision.

No backward compatibility aliases - this is a clean breaking change.

* [BREAKING] Rename Agent chat_client parameter to client

* Fix rebase issues: WorkflowMessage references and broken markdown links

* Fix formatting and lint issues from code quality checks

* Fix import ordering in workflow sample files

* fixed rebase

* Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename

- Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests
- Fix isinstance check in A2A agent to use A2AMessage instead of Message
- Fix import in test_workflow_observability.py (Message→WorkflowMessage)

* Fix lint, fmt, and sample errors after ChatMessage→Message rename

- Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs)
- Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample
- Fix _normalize_messages→normalize_messages in custom agent sample
- Fix context.terminate→raise MiddlewareTermination in middleware samples
- Fix with_update_hook→with_transform_hook in override middleware sample
- Add TOptions_co import back to custom_chat_client sample
- Add noqa for FastAPI File() default in chatkit sample
- Fix B023 loop variable capture in weather agent sample

* fix: update Agent constructor calls from chat_client to client in declaration-only tool tests

* fix: add register_cleanup to devui lazy-loading proxy and type stub

* fixed tests and updated new pieces

* fix agui typevar

* fix merge errors

* fix merge conflicts

* fiux merge

* Remove unused links

---------

Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>

python/samples/getting_started/azure_functions/02_multi_agent/README.md

@@ -76,8 +76,8 @@ Expected response:
 {
   "status": "healthy",
   "agents": [
-    {"name": "WeatherAgent", "type": "ChatAgent"},
-    {"name": "MathAgent", "type": "ChatAgent"}
+    {"name": "WeatherAgent", "type": "Agent"},
+    {"name": "MathAgent", "type": "Agent"}
   ],
   "agent_count": 2
 }

python/samples/getting_started/azure_functions/02_multi_agent/function_app.py

@@ -56,15 +56,15 @@ def calculate_tip(bill_amount: float, tip_percentage: float = 15.0) -> dict[str,
 
 
 # 1. Create multiple agents, each with its own instruction set and tools.
-chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
+client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-weather_agent = chat_client.as_agent(
+weather_agent = client.as_agent(
     name="WeatherAgent",
     instructions="You are a helpful weather assistant. Provide current weather information.",
     tools=[get_weather],
 )
 
-math_agent = chat_client.as_agent(
+math_agent = client.as_agent(
     name="MathAgent",
     instructions="You are a helpful math assistant. Help users with calculations like tip calculations.",
     tools=[calculate_tip],

python/samples/getting_started/azure_functions/05_multi_agent_orchestration_concurrency/function_app.py

@@ -30,14 +30,14 @@ CHEMIST_AGENT_NAME = "ChemistAgent"
 
 # 2. Instantiate both agents that the orchestration will run concurrently.
 def _create_agents() -> list[Any]:
-    chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
+    client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    physicist = chat_client.as_agent(
+    physicist = client.as_agent(
         name=PHYSICIST_AGENT_NAME,
         instructions="You are an expert in physics. You answer questions from a physics perspective.",
     )
 
-    chemist = chat_client.as_agent(
+    chemist = client.as_agent(
         name=CHEMIST_AGENT_NAME,
         instructions="You are an expert in chemistry. You answer questions from a chemistry perspective.",
     )

python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py

@@ -45,14 +45,14 @@ class EmailPayload(BaseModel):
 
 # 2. Instantiate both agents so they can be registered with AgentFunctionApp.
 def _create_agents() -> list[Any]:
-    chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
+    client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
-    spam_agent = chat_client.as_agent(
+    spam_agent = client.as_agent(
         name=SPAM_AGENT_NAME,
         instructions="You are a spam detection assistant that identifies spam emails.",
     )
 
-    email_agent = chat_client.as_agent(
+    email_agent = client.as_agent(
         name=EMAIL_AGENT_NAME,
         instructions="You are an email assistant that helps users draft responses to emails with professionalism.",
     )

python/samples/getting_started/azure_functions/08_mcp_server/README.md

@@ -142,20 +142,20 @@ The sample shows how to enable MCP tool triggers with flexible agent configurati
 from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
 
 # Create Azure OpenAI Chat Client
-chat_client = AzureOpenAIChatClient()
+client = AzureOpenAIChatClient()
 
 # Define agents with different roles
-joker_agent = chat_client.as_agent(
+joker_agent = client.as_agent(
     name="Joker",
     instructions="You are good at telling jokes.",
 )
 
-stock_agent = chat_client.as_agent(
+stock_agent = client.as_agent(
     name="StockAdvisor",
     instructions="Check stock prices.",
 )
 
-plant_agent = chat_client.as_agent(
+plant_agent = client.as_agent(
     name="PlantAdvisor",
     instructions="Recommend plants.",
     description="Get plant recommendations.",

python/samples/getting_started/azure_functions/08_mcp_server/function_app.py

@@ -28,23 +28,23 @@ from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
 
 # Create Azure OpenAI Chat Client
 # This uses AzureCliCredential for authentication (requires 'az login')
-chat_client = AzureOpenAIChatClient()
+client = AzureOpenAIChatClient()
 
 # Define three AI agents with different roles
 # Agent 1: Joker - HTTP trigger only (default)
-agent1 = chat_client.as_agent(
+agent1 = client.as_agent(
     name="Joker",
     instructions="You are good at telling jokes.",
 )
 
 # Agent 2: StockAdvisor - MCP tool trigger only
-agent2 = chat_client.as_agent(
+agent2 = client.as_agent(
     name="StockAdvisor",
     instructions="Check stock prices.",
 )
 
 # Agent 3: PlantAdvisor - Both HTTP and MCP tool triggers
-agent3 = chat_client.as_agent(
+agent3 = client.as_agent(
     name="PlantAdvisor",
     instructions="Recommend plants.",
     description="Get plant recommendations.",