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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>
This commit is contained in:
Eduard van Valkenburg
co-authored by
Evan Mattson
Evan Mattson
parent
a4c9e43afb
commit
0521f5bed8
@@ -11,9 +11,9 @@ from agent_framework import (
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AgentResponseUpdate,
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AgentThread,
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BaseAgent,
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ChatMessage,
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Content,
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Executor,
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Message,
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SupportsAgentRun,
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Workflow,
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WorkflowCheckpoint,
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@@ -48,7 +48,7 @@ def test_magentic_context_reset_behavior():
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participant_descriptions={"Alice": "Researcher"},
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)
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# seed context state
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ctx.chat_history.append(ChatMessage("assistant", ["draft"]))
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ctx.chat_history.append(Message("assistant", ["draft"]))
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ctx.stall_count = 2
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prev_reset = ctx.reset_count
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@@ -61,8 +61,8 @@ def test_magentic_context_reset_behavior():
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@dataclass
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class _SimpleLedger:
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facts: ChatMessage
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plan: ChatMessage
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facts: Message
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plan: Message
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class FakeManager(MagenticManagerBase):
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@@ -108,25 +108,25 @@ class FakeManager(MagenticManagerBase):
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plan_payload = cast(dict[str, Any] | None, ledger_dict.get("plan"))
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if facts_payload is not None and plan_payload is not None:
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try:
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facts = ChatMessage.from_dict(facts_payload)
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plan = ChatMessage.from_dict(plan_payload)
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facts = Message.from_dict(facts_payload)
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plan = Message.from_dict(plan_payload)
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self.task_ledger = _SimpleLedger(facts=facts, plan=plan)
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except Exception: # pragma: no cover - defensive
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pass
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async def plan(self, magentic_context: MagenticContext) -> ChatMessage:
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facts = ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- A\n"])
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plan = ChatMessage("assistant", ["- Do X\n- Do Y\n"])
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async def plan(self, magentic_context: MagenticContext) -> Message:
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facts = Message("assistant", ["GIVEN OR VERIFIED FACTS\n- A\n"])
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plan = Message("assistant", ["- Do X\n- Do Y\n"])
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self.task_ledger = _SimpleLedger(facts=facts, plan=plan)
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combined = f"Task: {magentic_context.task}\n\nFacts:\n{facts.text}\n\nPlan:\n{plan.text}"
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return ChatMessage("assistant", [combined], author_name=self.name)
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return Message("assistant", [combined], author_name=self.name)
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async def replan(self, magentic_context: MagenticContext) -> ChatMessage:
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facts = ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- A2\n"])
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plan = ChatMessage("assistant", ["- Do Z\n"])
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async def replan(self, magentic_context: MagenticContext) -> Message:
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facts = Message("assistant", ["GIVEN OR VERIFIED FACTS\n- A2\n"])
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plan = Message("assistant", ["- Do Z\n"])
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self.task_ledger = _SimpleLedger(facts=facts, plan=plan)
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combined = f"Task: {magentic_context.task}\n\nFacts:\n{facts.text}\n\nPlan:\n{plan.text}"
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return ChatMessage("assistant", [combined], author_name=self.name)
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return Message("assistant", [combined], author_name=self.name)
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async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger:
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# At least two messages in chat history means request is satisfied for testing
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@@ -139,8 +139,8 @@ class FakeManager(MagenticManagerBase):
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instruction_or_question=MagenticProgressLedgerItem(reason="test", answer=self.instruction_text),
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)
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", [self.FINAL_ANSWER], author_name=self.name)
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", [self.FINAL_ANSWER], author_name=self.name)
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class StubAgent(BaseAgent):
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@@ -150,7 +150,7 @@ class StubAgent(BaseAgent):
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def run( # type: ignore[override]
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self,
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messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None,
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messages: str | Message | Sequence[str | Message] | None = None,
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*,
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stream: bool = False,
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thread: AgentThread | None = None,
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@@ -160,7 +160,7 @@ class StubAgent(BaseAgent):
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return self._run_stream()
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async def _run() -> AgentResponse:
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response = ChatMessage("assistant", [self._reply_text], author_name=self.name)
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response = Message("assistant", [self._reply_text], author_name=self.name)
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return AgentResponse(messages=[response])
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return _run()
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@@ -177,7 +177,7 @@ class DummyExec(Executor):
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@handler
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async def _noop(
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self, message: GroupChatRequestMessage, ctx: WorkflowContext[ChatMessage]
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self, message: GroupChatRequestMessage, ctx: WorkflowContext[Message]
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) -> None: # pragma: no cover - not called
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pass
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@@ -190,13 +190,13 @@ async def test_magentic_builder_returns_workflow_and_runs() -> None:
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assert isinstance(workflow, Workflow)
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outputs: list[ChatMessage] = []
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outputs: list[Message] = []
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orchestrator_event_count = 0
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async for event in workflow.run("compose summary", stream=True):
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if event.type == "output":
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msg = event.data
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if isinstance(msg, list):
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outputs.extend(cast(list[ChatMessage], msg))
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outputs.extend(cast(list[Message], msg))
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elif event.type == "magentic_orchestrator":
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orchestrator_event_count += 1
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@@ -216,8 +216,8 @@ async def test_magentic_as_agent_does_not_accept_conversation() -> None:
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agent = workflow.as_agent(name="magentic-agent")
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conversation = [
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ChatMessage("system", ["Guidelines"], author_name="system"),
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ChatMessage("user", ["Summarize the findings"], author_name="requester"),
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Message("system", ["Guidelines"], author_name="system"),
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Message("user", ["Summarize the findings"], author_name="requester"),
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]
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with pytest.raises(ValueError, match="Magentic only support a single task message to start the workflow."):
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await agent.run(conversation)
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@@ -250,7 +250,7 @@ async def test_magentic_workflow_plan_review_approval_to_completion():
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assert isinstance(req_event.data, MagenticPlanReviewRequest)
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completed = False
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output: list[ChatMessage] | None = None
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output: list[Message] | None = None
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async for ev in wf.run(stream=True, responses={req_event.request_id: req_event.data.approve()}):
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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completed = True
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@@ -262,7 +262,7 @@ async def test_magentic_workflow_plan_review_approval_to_completion():
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assert completed
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assert output is not None
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assert isinstance(output, list)
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assert all(isinstance(msg, ChatMessage) for msg in output)
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assert all(isinstance(msg, Message) for msg in output)
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async def test_magentic_plan_review_with_revise():
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@@ -273,7 +273,7 @@ async def test_magentic_plan_review_with_revise():
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def __init__(self, *args, **kwargs) -> None: # type: ignore[no-untyped-def]
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super().__init__(*args, **kwargs)
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async def replan(self, magentic_context: MagenticContext) -> ChatMessage: # type: ignore[override]
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async def replan(self, magentic_context: MagenticContext) -> Message: # type: ignore[override]
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self.replan_count += 1
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return await super().replan(magentic_context)
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@@ -340,7 +340,7 @@ async def test_magentic_orchestrator_round_limit_produces_partial_result():
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assert isinstance(data, list)
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assert len(data) > 0 # type: ignore
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assert data[-1].role == "assistant" # type: ignore
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assert all(isinstance(msg, ChatMessage) for msg in data) # type: ignore
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assert all(isinstance(msg, Message) for msg in data) # type: ignore
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async def test_magentic_checkpoint_resume_round_trip():
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@@ -406,7 +406,7 @@ class StubManagerAgent(BaseAgent):
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def run(
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self,
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messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None,
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messages: str | Message | Sequence[str | Message] | None = None,
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*,
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stream: bool = False,
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thread: Any = None,
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@@ -416,22 +416,22 @@ class StubManagerAgent(BaseAgent):
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return self._run_stream()
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async def _run() -> AgentResponse:
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return AgentResponse(messages=[ChatMessage("assistant", ["ok"])])
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return AgentResponse(messages=[Message("assistant", ["ok"])])
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return _run()
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async def _run_stream(self) -> AsyncIterable[AgentResponseUpdate]:
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yield AgentResponseUpdate(message_deltas=[ChatMessage("assistant", ["ok"])])
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yield AgentResponseUpdate(message_deltas=[Message("assistant", ["ok"])])
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async def test_standard_manager_plan_and_replan_via_complete_monkeypatch():
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mgr = StandardMagenticManager(StubManagerAgent())
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async def fake_complete_plan(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage:
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async def fake_complete_plan(messages: list[Message], **kwargs: Any) -> Message:
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# Return a different response depending on call order length
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if any("FACTS" in (m.text or "") for m in messages):
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return ChatMessage("assistant", ["- step A\n- step B"])
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return ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- fact1"])
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return Message("assistant", ["- step A\n- step B"])
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return Message("assistant", ["GIVEN OR VERIFIED FACTS\n- fact1"])
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# First, patch to produce facts then plan
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mgr._complete = fake_complete_plan # type: ignore[attr-defined]
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@@ -444,10 +444,10 @@ async def test_standard_manager_plan_and_replan_via_complete_monkeypatch():
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assert any(t in combined.text for t in ("- step A", "- step B", "- step"))
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# Now replan with new outputs
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async def fake_complete_replan(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage:
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async def fake_complete_replan(messages: list[Message], **kwargs: Any) -> Message:
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if any("Please briefly explain" in (m.text or "") for m in messages):
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return ChatMessage("assistant", ["- new step"])
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return ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- updated"])
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return Message("assistant", ["- new step"])
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return Message("assistant", ["GIVEN OR VERIFIED FACTS\n- updated"])
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mgr._complete = fake_complete_replan # type: ignore[attr-defined]
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combined2 = await mgr.replan(ctx.clone())
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@@ -459,7 +459,7 @@ async def test_standard_manager_progress_ledger_success_and_error():
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ctx = MagenticContext(task="task", participant_descriptions={"alice": "desc"})
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# Success path: valid JSON
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async def fake_complete_ok(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage:
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async def fake_complete_ok(messages: list[Message], **kwargs: Any) -> Message:
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json_text = (
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'{"is_request_satisfied": {"reason": "r", "answer": false}, '
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'"is_in_loop": {"reason": "r", "answer": false}, '
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@@ -467,15 +467,15 @@ async def test_standard_manager_progress_ledger_success_and_error():
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'"next_speaker": {"reason": "r", "answer": "alice"}, '
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'"instruction_or_question": {"reason": "r", "answer": "do"}}'
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)
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return ChatMessage("assistant", [json_text])
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return Message("assistant", [json_text])
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mgr._complete = fake_complete_ok # type: ignore[attr-defined]
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ledger = await mgr.create_progress_ledger(ctx.clone())
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assert ledger.next_speaker.answer == "alice"
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# Error path: invalid JSON now raises to avoid emitting planner-oriented instructions to agents
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async def fake_complete_bad(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage:
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return ChatMessage("assistant", ["not-json"])
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async def fake_complete_bad(messages: list[Message], **kwargs: Any) -> Message:
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return Message("assistant", ["not-json"])
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mgr._complete = fake_complete_bad # type: ignore[attr-defined]
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with pytest.raises(RuntimeError):
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@@ -487,11 +487,11 @@ class InvokeOnceManager(MagenticManagerBase):
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super().__init__(max_round_count=5, max_stall_count=3, max_reset_count=2)
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self._invoked = False
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async def plan(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["ledger"])
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async def plan(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["ledger"])
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async def replan(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["re-ledger"])
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async def replan(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["re-ledger"])
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async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger:
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if not self._invoked:
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@@ -513,8 +513,8 @@ class InvokeOnceManager(MagenticManagerBase):
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instruction_or_question=MagenticProgressLedgerItem(reason="r", answer="done"),
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)
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["final"])
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["final"])
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class StubThreadAgent(BaseAgent):
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@@ -526,7 +526,7 @@ class StubThreadAgent(BaseAgent):
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return self._run_stream()
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async def _run():
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return AgentResponse(messages=[ChatMessage("assistant", ["thread-ok"], author_name=self.name)])
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return AgentResponse(messages=[Message("assistant", ["thread-ok"], author_name=self.name)])
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return _run()
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@@ -543,18 +543,18 @@ class StubAssistantsClient:
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class StubAssistantsAgent(BaseAgent):
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chat_client: object | None = None # allow assignment via Pydantic field
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client: object | None = None # allow assignment via Pydantic field
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def __init__(self) -> None:
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super().__init__(name="agentA")
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self.chat_client = StubAssistantsClient() # type name contains 'AssistantsClient'
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self.client = StubAssistantsClient() # type name contains 'AssistantsClient'
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def run(self, messages=None, *, stream: bool = False, thread=None, **kwargs): # type: ignore[override]
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if stream:
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return self._run_stream()
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async def _run():
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return AgentResponse(messages=[ChatMessage("assistant", ["assistants-ok"], author_name=self.name)])
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return AgentResponse(messages=[Message("assistant", ["assistants-ok"], author_name=self.name)])
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return _run()
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@@ -566,8 +566,8 @@ class StubAssistantsAgent(BaseAgent):
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)
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async def _collect_agent_responses_setup(participant: SupportsAgentRun) -> list[ChatMessage]:
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captured: list[ChatMessage] = []
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async def _collect_agent_responses_setup(participant: SupportsAgentRun) -> list[Message]:
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captured: list[Message] = []
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wf = MagenticBuilder(participants=[participant], intermediate_outputs=True, manager=InvokeOnceManager()).build()
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@@ -578,7 +578,7 @@ async def _collect_agent_responses_setup(participant: SupportsAgentRun) -> list[
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# Capture streaming updates (type="output" with AgentResponseUpdate data)
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if ev.type == "output" and isinstance(ev.data, AgentResponseUpdate):
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captured.append(
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ChatMessage(
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Message(
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role=ev.data.role or "assistant",
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text=ev.data.text or "",
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author_name=ev.data.author_name,
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@@ -711,11 +711,11 @@ class NotProgressingManager(MagenticManagerBase):
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A manager that never marks progress being made, to test stall/reset limits.
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"""
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async def plan(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["ledger"])
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async def plan(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["ledger"])
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async def replan(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["re-ledger"])
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async def replan(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["re-ledger"])
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async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger:
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return MagenticProgressLedger(
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@@ -726,8 +726,8 @@ class NotProgressingManager(MagenticManagerBase):
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instruction_or_question=MagenticProgressLedgerItem(reason="r", answer="done"),
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)
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage:
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return ChatMessage("assistant", ["final"])
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async def prepare_final_answer(self, magentic_context: MagenticContext) -> Message:
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return Message("assistant", ["final"])
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async def test_magentic_stall_and_reset_reach_limits():
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@@ -747,7 +747,7 @@ async def test_magentic_stall_and_reset_reach_limits():
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output_event = next((e for e in events if e.type == "output"), None)
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assert output_event is not None
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assert isinstance(output_event.data, list)
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assert all(isinstance(msg, ChatMessage) for msg in output_event.data) # type: ignore
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assert all(isinstance(msg, Message) for msg in output_event.data) # type: ignore
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assert len(output_event.data) > 0 # type: ignore
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||||
assert output_event.data[-1].text is not None # type: ignore
|
||||
assert output_event.data[-1].text == "Workflow terminated due to reaching maximum reset count." # type: ignore
|
||||
@@ -760,7 +760,7 @@ async def test_magentic_checkpoint_runtime_only() -> None:
|
||||
manager = FakeManager(max_round_count=10)
|
||||
wf = MagenticBuilder(participants=[DummyExec("agentA")], manager=manager).build()
|
||||
|
||||
baseline_output: ChatMessage | None = None
|
||||
baseline_output: Message | None = None
|
||||
async for ev in wf.run("runtime checkpoint test", checkpoint_storage=storage, stream=True):
|
||||
if ev.type == "output":
|
||||
baseline_output = ev.data # type: ignore[assignment]
|
||||
@@ -794,7 +794,7 @@ async def test_magentic_checkpoint_runtime_overrides_buildtime() -> None:
|
||||
participants=[DummyExec("agentA")], checkpoint_storage=buildtime_storage, manager=manager
|
||||
).build()
|
||||
|
||||
baseline_output: ChatMessage | None = None
|
||||
baseline_output: Message | None = None
|
||||
async for ev in wf.run("override test", checkpoint_storage=runtime_storage, stream=True):
|
||||
if ev.type == "output":
|
||||
baseline_output = ev.data # type: ignore[assignment]
|
||||
@@ -821,8 +821,8 @@ async def test_magentic_context_no_duplicate_on_reset():
|
||||
ctx = MagenticContext(task="task", participant_descriptions={"Alice": "Researcher"})
|
||||
|
||||
# Add some history
|
||||
ctx.chat_history.append(ChatMessage("assistant", ["response1"]))
|
||||
ctx.chat_history.append(ChatMessage("assistant", ["response2"]))
|
||||
ctx.chat_history.append(Message("assistant", ["response1"]))
|
||||
ctx.chat_history.append(Message("assistant", ["response2"]))
|
||||
assert len(ctx.chat_history) == 2
|
||||
|
||||
# Reset
|
||||
@@ -832,7 +832,7 @@ async def test_magentic_context_no_duplicate_on_reset():
|
||||
assert len(ctx.chat_history) == 0, "chat_history should be empty after reset"
|
||||
|
||||
# Add new history
|
||||
ctx.chat_history.append(ChatMessage("assistant", ["new_response"]))
|
||||
ctx.chat_history.append(Message("assistant", ["new_response"]))
|
||||
assert len(ctx.chat_history) == 1, "Should have exactly 1 message after adding to reset context"
|
||||
|
||||
|
||||
@@ -844,8 +844,8 @@ async def test_magentic_checkpoint_restore_no_duplicate_history():
|
||||
wf = MagenticBuilder(participants=[DummyExec("agentA")], checkpoint_storage=storage, manager=manager).build()
|
||||
|
||||
# Run with conversation history to create initial checkpoint
|
||||
conversation: list[ChatMessage] = [
|
||||
ChatMessage("user", ["task_msg"]),
|
||||
conversation: list[Message] = [
|
||||
Message("user", ["task_msg"]),
|
||||
]
|
||||
|
||||
async for event in wf.run(conversation, stream=True):
|
||||
@@ -1022,8 +1022,8 @@ def test_magentic_agent_factory_with_standard_manager_options():
|
||||
from agent_framework_orchestrations._magentic import _MagenticTaskLedger # type: ignore
|
||||
|
||||
custom_task_ledger = _MagenticTaskLedger(
|
||||
facts=ChatMessage("assistant", ["Custom facts"]),
|
||||
plan=ChatMessage("assistant", ["Custom plan"]),
|
||||
facts=Message("assistant", ["Custom facts"]),
|
||||
plan=Message("assistant", ["Custom plan"]),
|
||||
)
|
||||
|
||||
participant = StubAgent("agentA", "reply from agentA")
|
||||
|
||||
Reference in New Issue
Block a user