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/orchestrations/handoff_simple.py

@@ -4,9 +4,9 @@ import asyncio
 from typing import Annotated, cast
 
 from agent_framework import (
+    Agent,
     AgentResponse,
-    ChatAgent,
-    ChatMessage,
+    Message,
     WorkflowEvent,
     WorkflowRunState,
     tool,
@@ -54,17 +54,17 @@ def process_return(order_number: Annotated[str, "Order number to process return
     return f"Return initiated successfully for order {order_number}. You will receive return instructions via email."
 
 
-def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent, ChatAgent, ChatAgent]:
+def create_agents(client: AzureOpenAIChatClient) -> tuple[Agent, Agent, Agent, Agent]:
     """Create and configure the triage and specialist agents.
 
     Args:
-        chat_client: The AzureOpenAIChatClient to use for creating agents.
+        client: The AzureOpenAIChatClient to use for creating agents.
 
     Returns:
         Tuple of (triage_agent, refund_agent, order_agent, return_agent)
     """
     # Triage agent: Acts as the frontline dispatcher
-    triage_agent = chat_client.as_agent(
+    triage_agent = client.as_agent(
         instructions=(
             "You are frontline support triage. Route customer issues to the appropriate specialist agents "
             "based on the problem described."
@@ -73,7 +73,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Refund specialist: Handles refund requests
-    refund_agent = chat_client.as_agent(
+    refund_agent = client.as_agent(
         instructions="You process refund requests.",
         name="refund_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -81,7 +81,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Order/shipping specialist: Resolves delivery issues
-    order_agent = chat_client.as_agent(
+    order_agent = client.as_agent(
         instructions="You handle order and shipping inquiries.",
         name="order_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -89,7 +89,7 @@ def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAg
     )
 
     # Return specialist: Handles return requests
-    return_agent = chat_client.as_agent(
+    return_agent = client.as_agent(
         instructions="You manage product return requests.",
         name="return_agent",
         # In a real application, an agent can have multiple tools; here we keep it simple
@@ -138,7 +138,7 @@ def _handle_events(events: list[WorkflowEvent]) -> list[WorkflowEvent[HandoffAge
                     print(f"- {speaker}: {message.text}")
             elif event.type == "output":
                 # The output of the handoff workflow is a collection of chat messages from all participants
-                conversation = cast(list[ChatMessage], event.data)
+                conversation = cast(list[Message], event.data)
                 if isinstance(conversation, list):
                     print("\n=== Final Conversation Snapshot ===")
                     for message in conversation:
@@ -189,10 +189,10 @@ async def main() -> None:
     replace the scripted_responses with actual user input collection.
     """
     # Initialize the Azure OpenAI chat client
-    chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
+    client = AzureOpenAIChatClient(credential=AzureCliCredential())
 
     # Create all agents: triage + specialists
-    triage, refund, order, support = create_agents(chat_client)
+    triage, refund, order, support = create_agents(client)
 
     # Build the handoff workflow
     # - participants: All agents that can participate in the workflow