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https://github.com/BerriAI/litellm.git
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fix(responses): skip double exception mapping for already-typed errors
The Responses API bridge wraps litellm.completion(), which already maps provider exceptions to litellm types (BadRequestError, NotFoundError, etc.). The catch-all except blocks in responses/main.py then pass these already-mapped exceptions through exception_type() again unnecessarily. Add an isinstance guard before each exception_type() call in all 12 except blocks so litellm exceptions are re-raised directly, avoiding the redundant trip through the 2000+ line mapping function. Non-litellm exceptions (TypeError, ValueError from transformation code) still go through exception_type() as before. This matches the same guard pattern used inside exception_type() itself (exception_mapping_utils.py lines 240-244). Fixes #22121 (addresses suggested fix 1 of 4)
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Shivaang
parent
bffce842a1
commit
8a9c14cbe4
2 changed files with 182 additions and 0 deletions
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@ -515,6 +515,8 @@ async def aresponses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=model,
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custom_llm_provider=custom_llm_provider,
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@ -776,6 +778,8 @@ def responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=model,
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custom_llm_provider=custom_llm_provider,
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@ -841,6 +845,8 @@ async def adelete_responses(
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response = init_response
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -936,6 +942,8 @@ def delete_responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1015,6 +1023,8 @@ async def aget_responses(
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)
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1124,6 +1134,8 @@ def get_responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1186,6 +1198,8 @@ async def alist_input_items(
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response = init_response
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1271,6 +1285,8 @@ def list_input_items(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1336,6 +1352,8 @@ async def acancel_responses(
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response = init_response
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1431,6 +1449,8 @@ def cancel_responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=None,
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custom_llm_provider=custom_llm_provider,
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@ -1509,6 +1529,8 @@ async def acompact_responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=model,
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custom_llm_provider=custom_llm_provider,
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@ -1644,6 +1666,8 @@ def compact_responses(
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return response
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except Exception as e:
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if any(isinstance(e, exc_type) for exc_type in litellm.LITELLM_EXCEPTION_TYPES):
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raise e
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raise litellm.exception_type(
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model=model,
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custom_llm_provider=custom_llm_provider,
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@ -0,0 +1,158 @@
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"""
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Tests for Responses API exception handling.
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Verifies that exceptions already mapped by litellm.completion() are not
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double-mapped when they propagate through the Responses API bridge.
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Regression tests for https://github.com/BerriAI/litellm/issues/22121
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"""
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import os
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import sys
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from unittest.mock import patch
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import pytest
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sys.path.insert(
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0, os.path.abspath("../../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm.exceptions import (
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BadRequestError,
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NotFoundError,
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RateLimitError,
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)
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class TestResponsesExceptionPreservation:
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"""
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Tests that the Responses API bridge re-raises litellm exceptions
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directly instead of double-mapping them through exception_type().
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"""
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@pytest.mark.asyncio
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async def test_aresponses_preserves_bad_request_error(self):
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"""
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When the completion bridge raises a BadRequestError, aresponses()
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should re-raise it as-is instead of collapsing it into
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APIConnectionError.
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"""
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original_error = BadRequestError(
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message="Invalid model parameter",
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model="test-model",
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llm_provider="openai",
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)
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with patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
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return_value=None,
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), patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
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side_effect=original_error,
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):
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with pytest.raises(BadRequestError) as exc_info:
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await litellm.aresponses(
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model="openai/gpt-4o",
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input="test",
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)
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assert exc_info.value is original_error
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@pytest.mark.asyncio
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async def test_aresponses_preserves_rate_limit_error(self):
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"""
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When the completion bridge raises a RateLimitError, aresponses()
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should re-raise it as-is.
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"""
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original_error = RateLimitError(
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message="Rate limit exceeded",
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model="test-model",
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llm_provider="openai",
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)
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with patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
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return_value=None,
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), patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
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side_effect=original_error,
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):
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with pytest.raises(RateLimitError) as exc_info:
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await litellm.aresponses(
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model="openai/gpt-4o",
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input="test",
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)
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assert exc_info.value is original_error
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@pytest.mark.asyncio
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async def test_aresponses_preserves_not_found_error(self):
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"""
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When the completion bridge raises a NotFoundError, aresponses()
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should re-raise it as-is.
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"""
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original_error = NotFoundError(
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message="Model not found",
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model="test-model",
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llm_provider="openai",
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)
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with patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
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return_value=None,
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), patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
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side_effect=original_error,
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):
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with pytest.raises(NotFoundError) as exc_info:
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await litellm.aresponses(
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model="openai/gpt-4o",
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input="test",
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)
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assert exc_info.value is original_error
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@pytest.mark.asyncio
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async def test_aresponses_still_maps_non_litellm_exceptions(self):
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"""
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Non-litellm exceptions (e.g. ValueError from transformation code)
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should still be mapped through exception_type(). This ensures we
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only skip mapping for already-mapped exceptions.
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"""
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with patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
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return_value=None,
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), patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
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side_effect=ValueError("unexpected transformation error"),
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):
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with pytest.raises(Exception) as exc_info:
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await litellm.aresponses(
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model="openai/gpt-4o",
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input="test",
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)
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# Should NOT be a ValueError -- it should be mapped to a litellm type
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assert not isinstance(exc_info.value, ValueError)
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def test_responses_preserves_bad_request_error_sync(self):
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"""
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Sync variant: when the completion bridge raises a BadRequestError,
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responses() should re-raise it as-is.
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"""
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original_error = BadRequestError(
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message="Invalid model parameter",
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model="test-model",
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llm_provider="openai",
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)
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with patch(
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"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
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return_value=None,
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), patch(
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"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
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side_effect=original_error,
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):
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with pytest.raises(BadRequestError) as exc_info:
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litellm.responses(
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model="openai/gpt-4o",
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input="test",
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)
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assert exc_info.value is original_error
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