Merge pull request #39197 from BerriAI/litellm_e2e_reliability_retry_context_window

test(e2e): cover retry-on-timeout and the context-window fallback
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ryan-crabbe-berri 2026-09-01 15:51:01 -07:00 committed by GitHub
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4 changed files with 141 additions and 0 deletions

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@ -806,6 +806,7 @@ class LiteLLMParamsBody(BaseModel):
mock_response: str | None = None
timeout: float | None = None
tpm: int | None = None
weight: int | None = None
ModelMode = Literal["batch", "realtime", "image_generation"]
@ -820,6 +821,7 @@ class ModelInfoBody(BaseModel):
mode: ModelMode | None = None
access_groups: list[str] | None = None
team_id: str | None = None
allowed_fails_policy: dict[str, int] | None = None
class ModelNewBody(BaseModel):

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@ -19,6 +19,8 @@ from models import (
ChatMessage,
ChatResponse,
LiteLLMParamsBody,
ModelInfoBody,
ModelNewBody,
ReliabilityChatBody,
RouterSettingsOverride,
)
@ -26,6 +28,18 @@ from models import (
REAL_MODEL = "openai/gpt-5.5"
REAL_KEY = "os.environ/OPENAI_API_KEY"
# The smallest-context chat model OpenAI still serves (16385 tokens). A prompt
# past that limit comes back as a real `context_length_exceeded` 400, which is
# what litellm maps to ContextWindowExceededError.
SMALL_CONTEXT_MODEL = "openai/gpt-3.5-turbo"
SMALL_CONTEXT_LIMIT_TOKENS = 16385
def oversized_prompt(marker: str) -> str:
"""A prompt comfortably past SMALL_CONTEXT_MODEL's context limit, so the
provider refuses it on length rather than answering a truncated version."""
return f"{marker} " + ("token " * (SMALL_CONTEXT_LIMIT_TOKENS + 4000))
def create_bad_base_deployment(proxy: ProxyClient, name: str) -> str:
"""Register a deployment pointing at an unreachable base, so every call to it
@ -40,6 +54,38 @@ def create_timeout_deployment(proxy: ProxyClient, name: str) -> str:
return proxy.create_model(name, LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001))
def create_small_context_deployment(proxy: ProxyClient, name: str) -> str:
"""Register a deployment on the smallest-context model OpenAI still serves, so an
oversized prompt earns a real context-window refusal from the provider."""
return proxy.create_model(name, LiteLLMParamsBody(model=SMALL_CONTEXT_MODEL, api_key=REAL_KEY))
def create_always_timing_out_deployment(proxy: ProxyClient, name: str) -> str:
"""The always-picked half of a retry pair: a 1ms deadline the backend always
exceeds, all of the model group's shuffle weight, and a cooldown policy that
benches it on its first Timeout so the retry cannot land on it again."""
return proxy.register_model(
ModelNewBody(
model_name=name,
litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001, weight=1),
model_info=ModelInfoBody(allowed_fails_policy={"TimeoutErrorAllowedFails": 0}),
)
)
def create_zero_weight_backup_deployment(proxy: ProxyClient, name: str) -> str:
"""The other half of a retry pair: healthy, but weight 0, so the weighted shuffle
never opens on it. It is reachable only once its sibling is benched and the
weighted pick falls through to a uniform one over what is left."""
return proxy.register_model(
ModelNewBody(
model_name=name,
litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, weight=0),
model_info=ModelInfoBody(),
)
)
def chat_override(
proxy: ProxyClient,
key: str,

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@ -9,6 +9,10 @@ in the x-litellm-attempted-fallbacks header. Empty content is accepted only when
`finish_reason == "length"` and the response billed completion tokens, since
gpt-5.5 counts reasoning against max_tokens and can consume the whole budget
before emitting any text; a fallback that produced nothing at all still fails.
The context-window case is a different reroute from a plain failure: the provider
refuses the prompt on length, and `context_window_fallbacks` is the setting that
reroutes it, not `fallbacks`.
"""
from __future__ import annotations
@ -25,8 +29,10 @@ from reliability_support import (
completion_tokens_of,
content_of,
create_bad_base_deployment,
create_small_context_deployment,
create_timeout_deployment,
finish_reason_of,
oversized_prompt,
reasoning_tokens_of,
)
@ -82,3 +88,17 @@ class TestReliabilityFallbacks:
override=RouterSettingsOverride(fallbacks=[{primary: ["gpt-5.5"]}]),
)
_assert_served_by_fallback(resp)
@pytest.mark.covers("reliability.fallback.context_window.routes_to_fallback")
def test_context_window_routes_to_fallback(
self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
) -> None:
primary = f"reliability-ctxfail-{unique_marker()}"
model_id = create_small_context_deployment(client.proxy, primary)
resources.defer(lambda: client.proxy.delete_model(model_id))
resp = chat_override(
client.proxy, scoped_key, primary, oversized_prompt(unique_marker()),
override=RouterSettingsOverride(context_window_fallbacks=[{primary: ["gpt-5.5"]}]),
)
_assert_served_by_fallback(resp)

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@ -0,0 +1,73 @@
"""Live e2e: a request that fails on its first deployment is retried inside its own
model group and still comes back a completion.
The model group is a pair: an always-timing-out deployment that holds all of the
group's shuffle weight, and a healthy backup at weight 0. The weighted pick always
opens on the timing-out one, its first Timeout benches it (an
`allowed_fails_policy` of `TimeoutErrorAllowedFails: 0`), and the retry falls
through to the only deployment left. So the customer sees a completion and the
proxy reports that it took a retry to get there, with no random first pick in the
middle of it.
"""
from __future__ import annotations
import pytest
from complexity_router_client import ComplexityRouterClient
from e2e_config import unique_marker
from lifecycle import ResourceManager
from models import RouterSettingsOverride
from reliability_support import (
chat_override,
completion_tokens_of,
content_of,
create_always_timing_out_deployment,
create_zero_weight_backup_deployment,
finish_reason_of,
)
pytestmark = pytest.mark.e2e
class TestReliabilityRetries:
@pytest.mark.covers("reliability.retry.timeout.succeeds_within_retries")
def test_timeout_on_first_deployment_succeeds_on_retry(
self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
) -> None:
group = f"reliability-retry-{unique_marker()}"
timing_out = create_always_timing_out_deployment(client.proxy, group)
resources.defer(lambda: client.proxy.delete_model(timing_out))
backup = create_zero_weight_backup_deployment(client.proxy, group)
resources.defer(lambda: client.proxy.delete_model(backup))
resp = chat_override(
client.proxy,
scoped_key,
group,
f"say hi {unique_marker()}",
override=RouterSettingsOverride(num_retries=2),
)
assert resp.status_code == 200, (
f"the retry should have landed on the healthy backup, got {resp.status_code}: {resp.body[:300]}"
)
attempted = resp.headers.get("x-litellm-attempted-retries")
assert attempted is not None, "response is missing the x-litellm-attempted-retries header"
assert int(attempted) >= 1, (
f"x-litellm-attempted-retries is {attempted!r}; a 200 with no retry means the request never "
"opened on the timing-out deployment, so this proves nothing about retries"
)
content = content_of(resp)
finish_reason = finish_reason_of(resp)
completion_tokens = completion_tokens_of(resp) or 0
assert isinstance(content, str), (
f"the retry should have returned a completion body, got content {content!r} (body={resp.body[:300]})"
)
assert content or (finish_reason == "length" and completion_tokens > 0), (
f"the retry returned empty content with finish_reason={finish_reason!r}, "
f"completion_tokens={completion_tokens}; empty content is only acceptable when the budget "
f"was spent on non-visible reasoning (body={resp.body[:300]})"
)