fix(streaming): keep OpenAIError for aborts on OpenAI-compatible streams

Streams parsed by the OpenAI streaming handler raised the base exception on an upstream abort, so failure callbacks lost the OpenAIError class they got before. The handler now names its abort error class, and the Bedrock OpenAI-compatible decoder passes it through

litellm/llms/base_llm/base_model_iterator.py

@@ -1,6 +1,6 @@
 import json
 from abc import abstractmethod
-from typing import TYPE_CHECKING, Final, cast
+from typing import TYPE_CHECKING, ClassVar, Final, cast
 
 from pydantic import BaseModel, ConfigDict, ValidationError
 
@@ -100,16 +100,18 @@ class _StreamedChunk(BaseModel):
     choices: tuple[_StreamedChoice, ...] | None = None
 
 
-def raise_on_upstream_abort(chunk: object) -> None:
+def raise_on_upstream_abort(chunk: object, error: type[BaseLLMException] = BaseLLMException) -> None:
     try:
         choices: Final = _StreamedChunk.model_validate(chunk).choices or ()
     except ValidationError:
         return
     if any(choice.finish_reason == "abort" for choice in choices):
-        raise BaseLLMException(status_code=500, message=UPSTREAM_ABORT_MESSAGE)
+        raise error(status_code=500, message=UPSTREAM_ABORT_MESSAGE)
 
 
 class BaseModelResponseIterator:
+    upstream_abort_error: ClassVar[type[BaseLLMException]] = BaseLLMException
+
     def __init__(self, streaming_response, sync_stream: bool, json_mode: bool | None = False):
         self.streaming_response = streaming_response
         self.response_iterator = self.streaming_response
@@ -179,7 +181,7 @@ class BaseModelResponseIterator:
                 tool_use=None,
             )
         elif stripped_json_chunk:
-            raise_on_upstream_abort(stripped_json_chunk)
+            raise_on_upstream_abort(stripped_json_chunk, self.upstream_abort_error)
             return self.chunk_parser(chunk=stripped_json_chunk)
         else:
             return GenericStreamingChunk(

litellm/llms/bedrock/chat/invoke_handler.py

@@ -1022,5 +1022,7 @@ class AmazonOpenAICompatibleStreamDecoder(AWSEventStreamDecoder):
         )
 
     def _chunk_parser(self, chunk_data: dict[str, object]) -> ModelResponseStream:
-        base_model_iterator.raise_on_upstream_abort(chunk_data)
+        base_model_iterator.raise_on_upstream_abort(
+            chunk_data, self.openai_model_response_iterator.upstream_abort_error
+        )
         return self.openai_model_response_iterator.chunk_parser(chunk=chunk_data)

litellm/llms/openai/chat/gpt_transformation.py

@@ -6,7 +6,7 @@ import json
 import os
 from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, cast, overload
+from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, Optional, cast, overload
 from urllib.parse import urlparse
 
 import httpx
@@ -1019,6 +1019,8 @@ class OpenAIUnknownModelConfig(OpenAIGPTConfig):
 
 
 class OpenAIChatCompletionStreamingHandler(BaseModelResponseIterator):
+    upstream_abort_error: ClassVar[type[BaseLLMException]] = OpenAIError
+
     def _map_reasoning_to_reasoning_content(self, choices: list) -> list:
         """
         Map 'reasoning' field to 'reasoning_content' field in delta.

tests/unit/llms/bedrock/chat/test_invoke_handler.py

@@ -29,6 +29,7 @@ from litellm.llms.bedrock.chat.invoke_handler import (
 )
 from litellm.llms.bedrock.common_utils import BedrockError, get_bedrock_stream_event_statuses
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+from litellm.llms.openai.common_utils import OpenAIError
 from litellm.types.llms.bedrock import BedrockInvokeNovaRequest
 from litellm.types.utils import ModelResponseStream
 from tests.unit.llms.bedrock.slow_upstream import (
@@ -1054,6 +1055,22 @@ def test_iter_bytes_raises_when_the_stream_ends_mid_message() -> None:
     assert "first bytes=" not in exc_info.value.message
 
 
+def test_iter_bytes_raises_the_openai_error_when_upstream_aborts() -> None:
+    decoder: Final = AmazonOpenAICompatibleStreamDecoder(model="moonshot.kimi-k2-thinking", sync_stream=True)
+    raw_stream: Final = b"".join(
+        _bedrock_event_stream_frame(chunk)
+        for chunk in (
+            _openai_stream_chunk({"role": "assistant", "content": "Partial answer"}),
+            _openai_stream_chunk({}, "abort"),
+        )
+    )
+
+    with pytest.raises(OpenAIError, match="finish_reason=abort") as exc_info:
+        _chunks: Final = list(decoder.iter_bytes(iter([raw_stream])))
+
+    assert exc_info.value.status_code == 500
+
+
 def test_iter_bytes_yields_a_complete_stream_without_raising() -> None:
     decoder: Final = AmazonOpenAICompatibleStreamDecoder(model="moonshot.kimi-k2-thinking", sync_stream=True)
 

tests/unit/llms/openai/chat/test_openai_gpt_transformation.py

@@ -348,6 +348,17 @@ class TestOpenAIChatCompletionStreamingHandler:
         assert excinfo.value.status_code == 400
         assert "not multimodal" in excinfo.value.message
 
+    def test_stream_ending_in_abort_raises_an_openai_error(self):
+        from litellm.llms.openai.common_utils import OpenAIError
+
+        line = "data: " + json.dumps({"choices": [{"index": 0, "delta": {}, "finish_reason": "abort"}]})
+        handler = OpenAIChatCompletionStreamingHandler(streaming_response=iter((line,)), sync_stream=True)
+
+        with pytest.raises(OpenAIError, match="finish_reason=abort") as excinfo:
+            list(handler)
+
+        assert excinfo.value.status_code == 500
+
     def test_chunk_parser_error_payload_without_usable_code_maps_to_500(self):
         """OpenAI-style error payloads may carry a string code (e.g.
         "invalid_api_key") or none at all; those must map to 500, not crash."""