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/workflows/checkpoint/checkpoint_with_human_in_the_loop.py

@@ -20,9 +20,9 @@ from agent_framework import (
     AgentExecutor,
     AgentExecutorRequest,
     AgentExecutorResponse,
-    ChatMessage,
     Executor,
     FileCheckpointStorage,
+    Message,
     Workflow,
     WorkflowBuilder,
     WorkflowCheckpoint,
@@ -97,7 +97,7 @@ class BriefPreparer(Executor):
         # Hand the prompt to the writer agent. We always route through the
         # workflow context so the runtime can capture messages for checkpointing.
         await ctx.send_message(
-            AgentExecutorRequest(messages=[ChatMessage("user", text=prompt)], should_respond=True),
+            AgentExecutorRequest(messages=[Message("user", text=prompt)], should_respond=True),
             target_id=self._agent_id,
         )
 
@@ -159,7 +159,7 @@ class ReviewGateway(Executor):
             f"Human guidance: {reply}"
         )
         await ctx.send_message(
-            AgentExecutorRequest(messages=[ChatMessage("user", text=prompt)], should_respond=True),
+            AgentExecutorRequest(messages=[Message("user", text=prompt)], should_respond=True),
             target_id=self._writer_id,
         )
 

python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py

@@ -7,11 +7,11 @@ from pathlib import Path
 from typing import cast
 
 from agent_framework import (
+    Agent,
     AgentResponse,
-    ChatAgent,
-    ChatMessage,
     Content,
     FileCheckpointStorage,
+    Message,
     Workflow,
     WorkflowEvent,
     tool,
@@ -57,7 +57,7 @@ def submit_refund(refund_description: str, amount: str, order_id: str) -> str:
     return f"refund recorded for order {order_id} (amount: {amount}) with details: {refund_description}"
 
 
-def create_agents(client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent, ChatAgent]:
+def create_agents(client: AzureOpenAIChatClient) -> tuple[Agent, Agent, Agent]:
     """Create a simple handoff scenario: triage, refund, and order specialists."""
 
     triage = client.as_agent(
@@ -91,7 +91,7 @@ def create_agents(client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent,
     return triage, refund, order
 
 
-def create_workflow(checkpoint_storage: FileCheckpointStorage) -> tuple[Workflow, ChatAgent, ChatAgent, ChatAgent]:
+def create_workflow(checkpoint_storage: FileCheckpointStorage) -> tuple[Workflow, Agent, Agent, Agent]:
     """Build the handoff workflow with checkpointing enabled."""
 
     client = AzureOpenAIChatClient(credential=AzureCliCredential())
@@ -284,9 +284,9 @@ async def resume_with_responses(
 
         elif event.type == "output":
             print("\n[Workflow Output Event - Conversation Update]")
-            if event.data and isinstance(event.data, list) and all(isinstance(msg, ChatMessage) for msg in event.data):  # type: ignore
-                # Now safe to cast event.data to list[ChatMessage]
-                conversation = cast(list[ChatMessage], event.data)  # type: ignore
+            if event.data and isinstance(event.data, list) and all(isinstance(msg, Message) for msg in event.data):  # type: ignore
+                # Now safe to cast event.data to list[Message]
+                conversation = cast(list[Message], event.data)  # type: ignore
                 for msg in conversation[-3:]:  # Show last 3 messages
                     author = msg.author_name or msg.role
                     text = msg.text[:100] + "..." if len(msg.text) > 100 else msg.text

python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py

@@ -40,14 +40,14 @@ async def basic_checkpointing() -> None:
     print("Basic Checkpointing with Workflow as Agent")
     print("=" * 60)
 
-    chat_client = OpenAIChatClient()
+    client = OpenAIChatClient()
 
-    assistant = chat_client.as_agent(
+    assistant = client.as_agent(
         name="assistant",
         instructions="You are a helpful assistant. Keep responses brief.",
     )
 
-    reviewer = chat_client.as_agent(
+    reviewer = client.as_agent(
         name="reviewer",
         instructions="You are a reviewer. Provide a one-sentence summary of the assistant's response.",
     )
@@ -81,9 +81,9 @@ async def checkpointing_with_thread() -> None:
     print("Checkpointing with Thread Conversation History")
     print("=" * 60)
 
-    chat_client = OpenAIChatClient()
+    client = OpenAIChatClient()
 
-    assistant = chat_client.as_agent(
+    assistant = client.as_agent(
         name="memory_assistant",
         instructions="You are a helpful assistant with good memory. Reference previous conversation when relevant.",
     )
@@ -124,9 +124,9 @@ async def streaming_with_checkpoints() -> None:
     print("Streaming with Checkpointing")
     print("=" * 60)
 
-    chat_client = OpenAIChatClient()
+    client = OpenAIChatClient()
 
-    assistant = chat_client.as_agent(
+    assistant = client.as_agent(
         name="streaming_assistant",
         instructions="You are a helpful assistant.",
     )