feat(graph_engine): add ready_queue state persistence to GraphRuntimeState

- Add ReadyQueueState TypedDict for type-safe queue serialization
- Add ready_queue attribute to GraphRuntimeState for initializing with pre-existing queue state
- Update GraphEngine to load ready_queue from GraphRuntimeState on initialization
- Implement proper type hints using ReadyQueueState for better type safety
- Add comprehensive tests for ready_queue loading functionality

The ready_queue is read-only after initialization and allows resuming workflow
execution with a pre-populated queue of nodes ready to execute.

api/tests/unit_tests/core/workflow/entities/test_graph_runtime_state.py

@@ -4,6 +4,7 @@ import pytest
 
 from core.workflow.entities.graph_runtime_state import GraphRuntimeState
 from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.graph_engine.ready_queue import ReadyQueueState
 
 
 class TestGraphRuntimeState:
@@ -109,3 +110,30 @@ class TestGraphRuntimeState:
 
         # Original should remain unchanged
         assert state.get_output("nested")["level1"]["level2"]["value"] == "test"
+
+    def test_ready_queue_property(self):
+        variable_pool = VariablePool()
+
+        # Test default empty ready_queue
+        state = GraphRuntimeState(variable_pool=variable_pool, start_at=time())
+        assert state.ready_queue == {}
+
+        # Test initialization with ready_queue data as ReadyQueueState
+        queue_data = ReadyQueueState(type="InMemoryReadyQueue", version="1.0", items=["node1", "node2"], maxsize=0)
+        state = GraphRuntimeState(variable_pool=variable_pool, start_at=time(), ready_queue=queue_data)
+        assert state.ready_queue == queue_data
+
+        # Test with different ready_queue data at initialization
+        another_queue_data = ReadyQueueState(
+            type="InMemoryReadyQueue",
+            version="1.0",
+            items=["node3", "node4", "node5"],
+            maxsize=0,
+        )
+        another_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time(), ready_queue=another_queue_data)
+        assert another_state.ready_queue == another_queue_data
+
+        # Test immutability - modifying retrieved queue doesn't affect internal state
+        retrieved_queue = state.ready_queue
+        retrieved_queue["items"].append("node6")
+        assert len(state.ready_queue["items"]) == 2  # Should still be 2, not 3

api/tests/unit_tests/core/workflow/graph_engine/test_graph_engine.py

@@ -744,3 +744,78 @@ def test_event_sequence_validation_with_table_tests():
         else:
             assert result.event_sequence_match is True
         assert result.success, f"Test {i + 1} failed: {result.event_mismatch_details or result.error}"
+
+
+def test_ready_queue_state_loading():
+    """
+    Test that the ready_queue state is properly loaded from GraphRuntimeState
+    during GraphEngine initialization.
+    """
+    # Use the TableTestRunner to create a proper workflow instance
+    runner = TableTestRunner()
+
+    # Create a simple workflow
+    test_case = WorkflowTestCase(
+        fixture_path="simple_passthrough_workflow",
+        inputs={"query": "test"},
+        expected_outputs={"query": "test"},
+        description="Test ready_queue loading",
+    )
+
+    # Load the workflow fixture
+    workflow_runner = runner.workflow_runner
+    fixture_data = workflow_runner.load_fixture("simple_passthrough_workflow")
+
+    # Create graph and runtime state with pre-populated ready_queue
+    ready_queue_data = {
+        "type": "InMemoryReadyQueue",
+        "version": "1.0",
+        "items": ["node1", "node2", "node3"],
+        "maxsize": 0,
+    }
+
+    # We need to create the graph first, then create a new GraphRuntimeState with ready_queue
+    graph, original_runtime_state = workflow_runner.create_graph_from_fixture(fixture_data, query="test")
+
+    # Create a new GraphRuntimeState with the ready_queue data
+    from core.workflow.entities import GraphRuntimeState
+    from core.workflow.graph_engine.ready_queue import ReadyQueueState
+
+    # Convert ready_queue_data to ReadyQueueState
+    ready_queue_state = ReadyQueueState(**ready_queue_data)
+
+    graph_runtime_state = GraphRuntimeState(
+        variable_pool=original_runtime_state.variable_pool,
+        start_at=original_runtime_state.start_at,
+        ready_queue=ready_queue_state,
+    )
+
+    # Update all nodes to use the new GraphRuntimeState
+    for node in graph.nodes.values():
+        node.graph_runtime_state = graph_runtime_state
+
+    # Create GraphEngine
+    command_channel = InMemoryChannel()
+    engine = GraphEngine(
+        tenant_id="test-tenant",
+        app_id="test-app",
+        workflow_id="test-workflow",
+        user_id="test-user",
+        user_from=UserFrom.ACCOUNT,
+        invoke_from=InvokeFrom.DEBUGGER,
+        call_depth=0,
+        graph=graph,
+        graph_config={},
+        graph_runtime_state=graph_runtime_state,
+        command_channel=command_channel,
+    )
+
+    # Verify that the ready_queue was loaded from GraphRuntimeState
+    assert engine._ready_queue.qsize() == 3
+
+    # Verify the initial state matches what was provided
+    initial_queue_state = engine.graph_runtime_state.ready_queue
+    assert initial_queue_state["type"] == "InMemoryReadyQueue"
+    assert initial_queue_state["version"] == "1.0"
+    assert len(initial_queue_state["items"]) == 3
+    assert initial_queue_state["items"] == ["node1", "node2", "node3"]