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/semantic-kernel-migration/orchestrations/magentic.py

@@ -15,7 +15,7 @@ import asyncio
 from collections.abc import Sequence
 from typing import cast
 
-from agent_framework import ChatAgent, HostedCodeInterpreterTool
+from agent_framework import Agent, HostedCodeInterpreterTool
 from agent_framework.openai import OpenAIChatClient, OpenAIResponsesClient
 from agent_framework.orchestrations import MagenticBuilder
 from semantic_kernel.agents import (
@@ -129,29 +129,29 @@ def _print_semantic_kernel_outputs(outputs: Sequence[ChatMessageContent]) -> Non
 
 
 async def run_agent_framework_example(prompt: str) -> str | None:
-    researcher = ChatAgent(
+    researcher = Agent(
         name="ResearcherAgent",
         description="Specialist in research and information gathering",
         instructions=(
             "You are a Researcher. You find information without additional computation or quantitative analysis."
         ),
-        chat_client=OpenAIChatClient(ai_model_id="gpt-4o-search-preview"),
+        client=OpenAIChatClient(ai_model_id="gpt-4o-search-preview"),
     )
 
-    coder = ChatAgent(
+    coder = Agent(
         name="CoderAgent",
         description="A helpful assistant that writes and executes code to process and analyze data.",
         instructions="You solve questions using code. Please provide detailed analysis and computation process.",
-        chat_client=OpenAIResponsesClient(),
+        client=OpenAIResponsesClient(),
         tools=HostedCodeInterpreterTool(),
     )
 
     # Create a manager agent for orchestration
-    manager_agent = ChatAgent(
+    manager_agent = Agent(
         name="MagenticManager",
         description="Orchestrator that coordinates the research and coding workflow",
         instructions="You coordinate a team to complete complex tasks efficiently.",
-        chat_client=OpenAIChatClient(),
+        client=OpenAIChatClient(),
     )
 
     workflow = MagenticBuilder(participants=[researcher, coder], manager_agent=manager_agent).build()