Python: support checkpoints for workflow orchestrations and sub-workflows (#863)

* Magentic checkpoint wip

* Magentic checkpoint updates

* Support checkpointing for magentic orchestration.

* Checkpointing for sub-workflows

* Use _execute_contexts instead of _pending_requests

* Remove unnecessary type ignores

* Support checkpoints for other orchestrations, refactor some code.

* Regenerate uv.lock

python/packages/main/tests/workflow/test_sequential.py

@@ -21,6 +21,7 @@ from agent_framework import (
     WorkflowStatusEvent,
     handler,
 )
+from agent_framework._workflow._checkpoint import InMemoryCheckpointStorage
 
 
 class _EchoAgent(BaseAgent):
@@ -114,3 +115,46 @@ async def test_sequential_with_custom_executor_summary() -> None:
     assert msgs[0].role == Role.USER
     assert msgs[1].role == Role.ASSISTANT and "A1 reply" in msgs[1].text
     assert msgs[2].role == Role.ASSISTANT and msgs[2].text.startswith("Summary of users:")
+
+
+@pytest.mark.asyncio
+async def test_sequential_checkpoint_resume_round_trip() -> None:
+    storage = InMemoryCheckpointStorage()
+
+    initial_agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
+    wf = SequentialBuilder().participants(list(initial_agents)).with_checkpointing(storage).build()
+
+    baseline_output: list[ChatMessage] | None = None
+    async for ev in wf.run_stream("checkpoint sequential"):
+        if isinstance(ev, WorkflowOutputEvent):
+            baseline_output = ev.data  # type: ignore[assignment]
+        if isinstance(ev, WorkflowStatusEvent) and ev.state == WorkflowRunState.IDLE:
+            break
+
+    assert baseline_output is not None
+
+    checkpoints = await storage.list_checkpoints()
+    assert checkpoints
+    checkpoints.sort(key=lambda cp: cp.timestamp)
+
+    resume_checkpoint = next(
+        (cp for cp in checkpoints if (cp.metadata or {}).get("checkpoint_type") == "superstep"),
+        checkpoints[-1],
+    )
+
+    resumed_agents = (_EchoAgent(id="agent1", name="A1"), _EchoAgent(id="agent2", name="A2"))
+    wf_resume = SequentialBuilder().participants(list(resumed_agents)).with_checkpointing(storage).build()
+
+    resumed_output: list[ChatMessage] | None = None
+    async for ev in wf_resume.run_stream_from_checkpoint(resume_checkpoint.checkpoint_id):
+        if isinstance(ev, WorkflowOutputEvent):
+            resumed_output = ev.data  # type: ignore[assignment]
+        if isinstance(ev, WorkflowStatusEvent) and ev.state in (
+            WorkflowRunState.IDLE,
+            WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
+        ):
+            break
+
+    assert resumed_output is not None
+    assert [m.role for m in resumed_output] == [m.role for m in baseline_output]
+    assert [m.text for m in resumed_output] == [m.text for m in baseline_output]