fix(utils): stop clobbering litellm.num_retries global after a completion exception

This commit is contained in:
Devin AI 2026-07-14 22:14:43 +00:00
parent 477ef3a7e2
commit 3b73dbc0b0
2 changed files with 25 additions and 26 deletions

View file

@ -1501,18 +1501,7 @@ def client(original_function):
except Exception as e:
call_type = original_function.__name__
if call_type == CallTypes.completion.value:
num_retries = kwargs.get("num_retries", None) or litellm.num_retries or None
if kwargs.get("retry_policy", None):
get_num_retries_from_retry_policy = getattr(
sys.modules[__name__], "get_num_retries_from_retry_policy"
)
reset_retry_policy = getattr(sys.modules[__name__], "reset_retry_policy")
num_retries = get_num_retries_from_retry_policy(
exception=e,
retry_policy=kwargs.get("retry_policy"),
)
kwargs["retry_policy"] = reset_retry_policy() # prevent infinite loops
litellm.num_retries = None # set retries to None to prevent infinite loops
num_retries, kwargs = _get_wrapper_num_retries(kwargs=kwargs, exception=e)
context_window_fallback_dict = kwargs.get("context_window_fallback_dict", {})
_is_litellm_router_call = "model_group" in (
@ -1540,18 +1529,7 @@ def client(original_function):
kwargs["model"] = context_window_fallback_dict[model]
return original_function(*args, **kwargs)
elif call_type == CallTypes.responses.value:
num_retries = kwargs.get("num_retries", None) or litellm.num_retries or None
if kwargs.get("retry_policy", None):
get_num_retries_from_retry_policy = getattr(
sys.modules[__name__], "get_num_retries_from_retry_policy"
)
reset_retry_policy = getattr(sys.modules[__name__], "reset_retry_policy")
num_retries = get_num_retries_from_retry_policy(
exception=e,
retry_policy=kwargs.get("retry_policy"),
)
kwargs["retry_policy"] = reset_retry_policy() # prevent infinite loops
litellm.num_retries = None # set retries to None to prevent infinite loops
num_retries, kwargs = _get_wrapper_num_retries(kwargs=kwargs, exception=e)
_is_litellm_router_call = "model_group" in (
kwargs.get("metadata") or {}
@ -1822,7 +1800,6 @@ def client(original_function):
num_retries and not _is_litellm_router_call
): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying
try:
litellm.num_retries = None # set retries to None to prevent infinite loops
kwargs["num_retries"] = num_retries
kwargs["original_function"] = original_function
if isinstance(e, openai.RateLimitError): # rate limiting specific error
@ -1852,7 +1829,6 @@ def client(original_function):
num_retries and not _is_litellm_router_call
): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying
try:
litellm.num_retries = None # set retries to None to prevent infinite loops
kwargs["num_retries"] = num_retries
kwargs["original_function"] = original_function
if isinstance(e, openai.RateLimitError): # rate limiting specific error

View file

@ -4737,3 +4737,26 @@ def test_gemini_image_models_do_not_support_reasoning(
f"{model} incorrectly classified as reasoning-capable. "
"Add 'supports_reasoning: false' to its model_cost entry."
)
def test_completion_exception_preserves_global_num_retries(monkeypatch):
monkeypatch.setattr(litellm, "num_retries", 2)
with pytest.raises(litellm.RateLimitError):
litellm.completion(
model="gpt-4o-mini",
messages=[{"role": "user", "content": "hi"}],
mock_response="litellm.RateLimitError",
)
assert litellm.num_retries == 2
@pytest.mark.asyncio
async def test_acompletion_exception_preserves_global_num_retries(monkeypatch):
monkeypatch.setattr(litellm, "num_retries", 2)
with pytest.raises(litellm.RateLimitError):
await litellm.acompletion(
model="gpt-4o-mini",
messages=[{"role": "user", "content": "hi"}],
mock_response="litellm.RateLimitError",
)
assert litellm.num_retries == 2