fix(middleware): fix LLM fallback run status (#3321)

* Fix LLM fallback run status

* optimize LLM fallback maker extraction in streaming path

backend/tests/test_run_worker_rollback.py

@@ -3,12 +3,22 @@ from types import SimpleNamespace
 from unittest.mock import AsyncMock, call
 
 import pytest
+from langchain_core.messages import AIMessage
 from langgraph.checkpoint.base import empty_checkpoint
 from langgraph.checkpoint.memory import InMemorySaver
 
 from deerflow.runtime.runs.manager import RunManager
 from deerflow.runtime.runs.schemas import RunStatus
-from deerflow.runtime.runs.worker import RunContext, _agent_factory_supports_app_config, _build_runtime_context, _install_runtime_context, _rollback_to_pre_run_checkpoint, run_agent
+from deerflow.runtime.runs.worker import (
+    RunContext,
+    _agent_factory_supports_app_config,
+    _build_runtime_context,
+    _extract_llm_error_fallback_message,
+    _install_runtime_context,
+    _rollback_to_pre_run_checkpoint,
+    _try_extract_from_message,
+    run_agent,
+)
 
 
 class FakeCheckpointer:
@@ -95,6 +105,52 @@ async def test_run_agent_threads_explicit_app_config_into_config_only_factory():
     bridge.cleanup.assert_awaited_once_with(record.run_id, delay=60)
 
 
+@pytest.mark.anyio
+async def test_run_agent_marks_llm_error_fallback_as_error_status():
+    run_manager = RunManager()
+    record = await run_manager.create("thread-1")
+    bridge = SimpleNamespace(
+        publish=AsyncMock(),
+        publish_end=AsyncMock(),
+        cleanup=AsyncMock(),
+    )
+
+    class DummyAgent:
+        async def astream(self, graph_input, config=None, stream_mode=None, subgraphs=False):
+            yield {
+                "messages": [
+                    AIMessage(
+                        content="The configured LLM provider is temporarily unavailable after multiple retries.",
+                        additional_kwargs={
+                            "deerflow_error_fallback": True,
+                            "error_type": "APIConnectionError",
+                            "error_reason": "transient",
+                            "error_detail": "Connection error.",
+                        },
+                    )
+                ]
+            }
+
+    def factory(*, config):
+        return DummyAgent()
+
+    await run_agent(
+        bridge,
+        run_manager,
+        record,
+        ctx=RunContext(checkpointer=None),
+        agent_factory=factory,
+        graph_input={},
+        config={},
+    )
+
+    fetched = await run_manager.get(record.run_id)
+    assert fetched is not None
+    assert fetched.status == RunStatus.error
+    assert fetched.error == "Connection error."
+    bridge.publish_end.assert_awaited_once_with(record.run_id)
+
+
 @pytest.mark.anyio
 async def test_run_agent_defaults_root_run_name_from_assistant_id():
     run_manager = RunManager()
@@ -486,3 +542,133 @@ def test_agent_factory_supports_app_config_returns_false_when_signature_lookup_f
     monkeypatch.setattr("deerflow.runtime.runs.worker.inspect.signature", lambda _obj: (_ for _ in ()).throw(ValueError("boom")))
 
     assert _agent_factory_supports_app_config(BrokenCallable()) is False
+
+
+# ---------------------------------------------------------------------------
+# _extract_llm_error_fallback_message coverage
+# ---------------------------------------------------------------------------
+
+
+def test_try_extract_from_message_finds_fallback_on_message_object():
+    msg = AIMessage(
+        content="fallback",
+        additional_kwargs={
+            "deerflow_error_fallback": True,
+            "error_detail": "Connection error.",
+            "error_reason": "transient",
+        },
+    )
+    assert _try_extract_from_message(msg) == "Connection error."
+
+
+def test_try_extract_from_message_finds_fallback_on_dict():
+    msg = {
+        "content": "fallback",
+        "additional_kwargs": {
+            "deerflow_error_fallback": True,
+            "error_detail": "Quota exceeded.",
+        },
+    }
+    assert _try_extract_from_message(msg) == "Quota exceeded."
+
+
+def test_try_extract_from_message_returns_none_for_normal_message():
+    msg = AIMessage(content="hello")
+    assert _try_extract_from_message(msg) is None
+
+
+def test_extract_llm_error_fallback_message_large_state_chunk_no_fallback():
+    """Normal-size state dict without fallback markers must not raise and should return None."""
+    large_state = {
+        "messages": [
+            AIMessage(content="Hello!"),
+            {"role": "user", "content": "Hi there"},
+        ],
+        "foo": "x" * 10_000,
+        "bar": {"nested": {"deep": {"data": list(range(1000))}}},
+        "baz": [{"id": i, "payload": "y" * 1000} for i in range(500)],
+    }
+    assert _extract_llm_error_fallback_message(large_state) is None
+
+
+def test_extract_llm_error_fallback_message_finds_fallback_in_messages_list():
+    state = {
+        "messages": [
+            AIMessage(content="Hello!"),
+            AIMessage(
+                content="Unavailable.",
+                additional_kwargs={
+                    "deerflow_error_fallback": True,
+                    "error_detail": "Connection error.",
+                },
+            ),
+        ],
+        "other_state": "large_value" * 1000,
+    }
+    assert _extract_llm_error_fallback_message(state) == "Connection error."
+
+
+def test_extract_llm_error_fallback_message_finds_fallback_in_raw_message():
+    msg = AIMessage(
+        content="Unavailable.",
+        additional_kwargs={
+            "deerflow_error_fallback": True,
+            "error_reason": "quota",
+        },
+    )
+    assert _extract_llm_error_fallback_message(msg) == "quota"
+
+
+def test_extract_llm_error_fallback_message_finds_fallback_in_tuple():
+    item = (
+        "messages",
+        AIMessage(
+            content="Unavailable.",
+            additional_kwargs={
+                "deerflow_error_fallback": True,
+                "error_detail": "Circuit open.",
+            },
+        ),
+    )
+    assert _extract_llm_error_fallback_message(item) == "Circuit open."
+
+
+def test_extract_llm_error_fallback_message_returns_none_for_empty_values():
+    assert _extract_llm_error_fallback_message({}) is None
+    assert _extract_llm_error_fallback_message([]) is None
+    assert _extract_llm_error_fallback_message(None) is None
+    assert _extract_llm_error_fallback_message("string") is None
+
+
+def test_extract_llm_error_fallback_message_finds_fallback_in_updates_mode():
+    """stream_mode='updates' yields dicts keyed by node name (e.g. {'call_model': {...}}).
+    Fallback marker is nested inside the node's state update, not at the top level."""
+    update_chunk = {
+        "call_model": {
+            "messages": [
+                AIMessage(
+                    content="Unavailable.",
+                    additional_kwargs={
+                        "deerflow_error_fallback": True,
+                        "error_detail": "Connection error.",
+                    },
+                )
+            ]
+        }
+    }
+    assert _extract_llm_error_fallback_message(update_chunk) == "Connection error."
+
+
+def test_extract_llm_error_fallback_message_updates_mode_no_fallback():
+    """Normal updates chunk without any fallback should return None safely."""
+    update_chunk = {
+        "__interrupt__": [
+            {
+                "value": "ask_human",
+                "resumable": True,
+                "ns": ["agent"],
+                "when": "during",
+            }
+        ]
+    }
+    assert _extract_llm_error_fallback_message(update_chunk) is None