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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>
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@@ -4,7 +4,7 @@
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Tests include:
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- Entity discovery and info retrieval
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- Agent execution (sync and streaming) using real ChatAgent with mock LLM
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- Agent execution (sync and streaming) using real Agent with mock LLM
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- Workflow execution using real WorkflowBuilder with FunctionExecutor
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- Edge cases like non-streaming agents
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"""
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@@ -15,7 +15,7 @@ from pathlib import Path
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from typing import Any
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import pytest
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from agent_framework import AgentExecutor, ChatAgent, FunctionExecutor, WorkflowBuilder
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from agent_framework import Agent, AgentExecutor, FunctionExecutor, WorkflowBuilder
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# Import mock classes from conftest for direct use in some tests
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from conftest import MockBaseChatClient
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@@ -77,15 +77,15 @@ async def test_executor_get_entity_info(executor):
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# =============================================================================
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# Agent Execution Tests (using real ChatAgent with mock LLM)
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# Agent Execution Tests (using real Agent with mock LLM)
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# =============================================================================
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async def test_agent_sync_execution(executor_with_real_agent):
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"""Test synchronous agent execution with REAL ChatAgent (mock LLM).
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"""Test synchronous agent execution with REAL Agent (mock LLM).
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This tests the full execution pipeline without needing an API key:
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- Real ChatAgent class with middleware
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- Real Agent class with middleware
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- Real message normalization
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- Mock chat client for LLM calls
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"""
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@@ -130,7 +130,7 @@ async def test_agent_sync_execution_respects_model_field(executor_with_real_agen
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async def test_chat_client_receives_correct_messages(executor_with_real_agent):
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"""Verify the mock chat client receives properly formatted messages.
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This tests that the REAL ChatAgent properly:
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This tests that the REAL Agent properly:
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- Normalizes input messages
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- Formats messages for the chat client
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"""
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@@ -297,18 +297,18 @@ async def test_full_pipeline_workflow_events_are_json_serializable():
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This is particularly important for workflows with AgentExecutor because:
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- AgentExecutor produces executor_completed event (type='executor_completed') with AgentExecutorResponse
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- AgentExecutorResponse contains AgentResponse and ChatMessage objects
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- AgentExecutorResponse contains AgentResponse and Message objects
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- These are SerializationMixin objects, not Pydantic, which caused the original bug
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This test ensures the ENTIRE streaming pipeline works end-to-end.
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"""
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# Create a workflow with AgentExecutor (the problematic case)
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mock_client = MockBaseChatClient()
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agent = ChatAgent(
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agent = Agent(
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id="serialization_test_agent",
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name="Serialization Test Agent",
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description="Agent for testing serialization",
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chat_client=mock_client,
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client=mock_client,
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system_message="You are a test assistant.",
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)
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@@ -466,15 +466,15 @@ async def test_executor_parse_raw_string_for_string_workflow():
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@pytest.mark.asyncio
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async def test_executor_parse_converts_to_chat_message_for_sequential_workflow(sequential_workflow):
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"""Sequential workflows convert string input to ChatMessage."""
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from agent_framework import ChatMessage
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"""Sequential workflows convert string input to Message."""
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from agent_framework import Message
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executor, _entity_id, _mock_client, workflow = sequential_workflow
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# Sequential workflows expect ChatMessage, so raw string becomes ChatMessage
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# Sequential workflows expect Message, so raw string becomes Message
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parsed = executor._parse_raw_workflow_input(workflow, "hello")
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assert isinstance(parsed, ChatMessage)
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assert isinstance(parsed, Message)
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assert parsed.text == "hello"
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@@ -538,7 +538,7 @@ def test_extract_workflow_hil_responses_handles_stringified_json():
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async def test_executor_handles_streaming_agent():
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"""Test executor handles agents with run(stream=True) method."""
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from agent_framework import AgentResponse, AgentResponseUpdate, AgentThread, ChatMessage, Content
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from agent_framework import AgentResponse, AgentResponseUpdate, AgentThread, Content, Message
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class StreamingAgent:
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"""Agent with run() method supporting stream parameter."""
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@@ -556,7 +556,7 @@ async def test_executor_handles_streaming_agent():
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async def _run_impl(self, messages):
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return AgentResponse(
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messages=[ChatMessage(role="assistant", contents=[Content.from_text(text=f"Processed: {messages}")])],
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messages=[Message(role="assistant", contents=[Content.from_text(text=f"Processed: {messages}")])],
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response_id="test_123",
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)
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