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_autonomous.py

@@ -5,9 +5,9 @@ import logging
 from typing import cast
 
 from agent_framework import (
+    Agent,
     AgentResponseUpdate,
-    ChatAgent,
-    ChatMessage,
+    Message,
     resolve_agent_id,
 )
 from agent_framework.azure import AzureOpenAIChatClient
@@ -37,10 +37,10 @@ Key Concepts:
 
 
 def create_agents(
-    chat_client: AzureOpenAIChatClient,
-) -> tuple[ChatAgent, ChatAgent, ChatAgent]:
+    client: AzureOpenAIChatClient,
+) -> tuple[Agent, Agent, Agent]:
     """Create coordinator and specialists for autonomous iteration."""
-    coordinator = chat_client.as_agent(
+    coordinator = client.as_agent(
         instructions=(
             "You are a coordinator. You break down a user query into a research task and a summary task. "
             "Assign the two tasks to the appropriate specialists, one after the other."
@@ -48,7 +48,7 @@ def create_agents(
         name="coordinator",
     )
 
-    research_agent = chat_client.as_agent(
+    research_agent = client.as_agent(
         instructions=(
             "You are a research specialist that explores topics thoroughly using web search. "
             "When given a research task, break it down into multiple aspects and explore each one. "
@@ -60,7 +60,7 @@ def create_agents(
         name="research_agent",
     )
 
-    summary_agent = chat_client.as_agent(
+    summary_agent = client.as_agent(
         instructions=(
             "You summarize research findings. Provide a concise, well-organized summary. When done, return "
             "control to the coordinator."
@@ -73,8 +73,8 @@ def create_agents(
 
 async def main() -> None:
     """Run an autonomous handoff workflow with specialist iteration enabled."""
-    chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
-    coordinator, research_agent, summary_agent = create_agents(chat_client)
+    client = AzureOpenAIChatClient(credential=AzureCliCredential())
+    coordinator, research_agent, summary_agent = create_agents(client)
 
     # Build the workflow with autonomous mode
     # In autonomous mode, agents continue iterating until they invoke a handoff tool
@@ -129,7 +129,7 @@ async def main() -> None:
                 print(data.text, end="", flush=True)
             elif event.type == "output":
                 # The output of the handoff workflow is a collection of chat messages from all participants
-                outputs = cast(list[ChatMessage], event.data)
+                outputs = cast(list[Message], event.data)
                 print("\n" + "=" * 80)
                 print("\nFinal Conversation Transcript:\n")
                 for message in outputs: