fix(langgraph): Ignore GraphBubbleUp exceptions

sentry_sdk/integrations/langchain.py

@@ -210,6 +210,8 @@ class LangchainIntegration(Integration):
     identifier = "langchain"
     origin = f"auto.ai.{identifier}"
 
+    _ignored_exceptions: "set[type[Exception]]" = set()
+
     def __init__(
         self: "LangchainIntegration",
         include_prompts: bool = True,
@@ -262,17 +264,22 @@ def gc_span_map(self) -> None:
                 self._exit_span(span, run_id)
 
     def _handle_error(self, run_id: "UUID", error: "Any") -> None:
+        is_ignored = isinstance(error, tuple(LangchainIntegration._ignored_exceptions))
+
         with capture_internal_exceptions():
             if not run_id or run_id not in self.span_map:
                 return
 
             span = self.span_map[run_id]
 
-            sentry_sdk.capture_exception(
-                error, span._scope if isinstance(span, StreamedSpan) else span.scope
-            )
+            if is_ignored:
+                span.__exit__(None, None, None)
+            else:
+                sentry_sdk.capture_exception(
+                    error, span._scope if isinstance(span, StreamedSpan) else span.scope
+                )
+                span.__exit__(type(error), error, error.__traceback__)
 
-            span.__exit__(type(error), error, error.__traceback__)
             del self.span_map[run_id]
 
     def _normalize_langchain_message(self, message: "BaseMessage") -> "Any":

sentry_sdk/integrations/langgraph.py

@@ -10,6 +10,9 @@
 )
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations import DidNotEnable, Integration
+
+# This is fine because langgraph depends on langchain-base, and LangchainIntegration only imports from langchain-base.
+from sentry_sdk.integrations.langchain import LangchainIntegration
 from sentry_sdk.scope import should_send_default_pii
 from sentry_sdk.traces import StreamedSpan
 from sentry_sdk.tracing_utils import (
@@ -19,6 +22,7 @@
 from sentry_sdk.utils import safe_serialize
 
 try:
+    from langgraph.errors import GraphBubbleUp
     from langgraph.graph import StateGraph
     from langgraph.pregel import Pregel
 except ImportError:
@@ -34,6 +38,7 @@ def __init__(self: "LanggraphIntegration", include_prompts: bool = True) -> None
 
     @staticmethod
     def setup_once() -> None:
+        LangchainIntegration._ignored_exceptions.add(GraphBubbleUp)
         # LangGraph lets users create agents using a StateGraph or the Functional API.
         # StateGraphs are then compiled to a CompiledStateGraph. Both CompiledStateGraph and
         # the functional API execute on a Pregel instance. Pregel is the runtime for the graph

tests/integrations/langgraph/test_langgraph.py

@@ -3,6 +3,10 @@
 from unittest.mock import MagicMock, patch
 
 import pytest
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_core.messages import HumanMessage
+from langchain_core.outputs import ChatResult
+from langgraph.errors import GraphBubbleUp
 
 import sentry_sdk
 from sentry_sdk import start_transaction
@@ -125,6 +129,15 @@ async def ainvoke(self, state, config=None):
         return {"messages": [MockMessage("Async Pregel response")]}
 
 
+class InterruptingChatModel(BaseChatModel):
+    @property
+    def _llm_type(self) -> str:
+        return "interrupting-chat-model"
+
+    def _generate(self, messages, stop=None, run_manager=None, **kwargs) -> ChatResult:
+        raise GraphBubbleUp("interrupt")
+
+
 def test_langgraph_integration_init():
     """Test LanggraphIntegration initialization with different parameters."""
     integration = LanggraphIntegration()
@@ -2104,3 +2117,17 @@ def original_invoke(self, *args, **kwargs):
     assert len(parsed_messages) == 1
     assert "small message 5" in str(parsed_messages[0])
     assert tx["_meta"]["spans"]["0"]["data"]["gen_ai.request.messages"][""]["len"] == 5
+
+
+def test_graph_bubble_up_ignored(sentry_init, capture_items):
+    sentry_init(
+        integrations=[LanggraphIntegration()],
+    )
+
+    events = capture_items("event")
+
+    model = InterruptingChatModel()
+    with pytest.raises(GraphBubbleUp):
+        model.invoke([HumanMessage(content="hi")])
+
+    assert len(events) == 0