Files
litellm/tests/test_end_users.py
T
Mateo Wang 2c733c00f5 chore(ci): modernize model references in tests and configs (#27856)
* test: modernize models used in CircleCI e2e test suites

Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo,
claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current
equivalents across the e2e_openai_endpoints and
proxy_e2e_anthropic_messages_tests CircleCI jobs.

- gpt-4o -> gpt-5.5 (responses API e2e tests)
- gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config)
- gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning,
  still actively fine-tunable)
- gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 /
  gpt-5-mini
- bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001
  (also aligning oai_misc_config model_name with what
  test_bedrock_batches_api.py actually requests)
- bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15)
  -> claude-sonnet-4-5-20250929

* test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5

Greptile/Cursor flagged that after the previous commit, the
bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5
(both pointed to claude-sonnet-4-5-20250929). Rename to
bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID
(us.anthropic.claude-sonnet-4-6, already in the litellm model
registry) so the alias name matches the underlying model version.

* test: modernize models across remaining CI-mounted configs & tests

Expands the modernization sweep to all CircleCI-mounted proxy configs
and to test directories where the model literal is a fixture/route key
(not the test's subject).

Config changes:
- proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 /
  gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename
  gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump
  text-embedding-ada-002 underlying to text-embedding-3-small. User-
  facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.)
  preserved for backward compatibility with tests.
- simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml:
  bump gpt-3.5-turbo underlying to gpt-5-mini.
- pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet /
  claude-3-haiku entries replaced with claude-sonnet-4-5 / claude-
  haiku-4-5 / claude-opus-4-7.
- oai_misc_config.yaml: align alias name with the gpt-5-mini rename.

Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4-
20250514 retire 2026-06-15):
- tests/llm_translation/test_anthropic_completion.py: bump 3 references
  + paired Vertex AI ID to claude-sonnet-4-5.
- tests/llm_translation/test_optional_params.py: bump 2 references.
- tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
  and test_bedrock_anthropic_messages_test.py: bump router fixtures
  using the deprecated model IDs.
- tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py:
  modernize docstring examples.
- tests/test_end_users.py: update references to renamed alias.

* test: modernize placeholder model literals in router_unit_tests

Mass replace_all on fixture/placeholder model literals across the
router_unit_tests/ suite (model name is a routing key / label, not the
test subject). Sub-agent sweep so far — additional commits will follow
for logging_callback_tests/, enterprise/, top-level tests/test_*.py,
and other CI-mounted dirs.

Mappings applied:
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 / claude-3-opus-20240229 /
  claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 ->
  claude-sonnet-4-5-20250929 / claude-opus-4-7 /
  claude-haiku-4-5-20251001 as appropriate

Explicitly preserved:
- gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current
- gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals)
- JSONL batch body literals
- Mock LLM response model fields (must match upstream)
- Fake/mock identifiers

* test: modernize placeholder model literals across remaining CI suites

Sub-agent sweep across logging_callback_tests/, guardrails_tests/,
enterprise/, pass_through_unit_tests/, otel_tests/,
llm_responses_api_testing/, batches_tests/, spend_tracking_tests/,
litellm_utils_tests/, unified_google_tests/, and a few top-level
tests/test_*.py files where the model literal is a fixture or
placeholder (router model_list, mock standard logging payload, mock
callback data) rather than the test's subject.

Mappings applied (see scope notes below):
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5
  is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex
  / gpt-5-mini exist)
- gpt-4o-mini (bare) -> gpt-5-mini
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929
- claude-3-opus-20240229 -> claude-opus-4-7
- claude-3-haiku-20240307 -> claude-haiku-4-5-20251001
- claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929
- claude-3-7-sonnet-20250219 -> claude-sonnet-4-6
- gemini-1.5-flash -> gemini-2.5-flash
- gemini-1.5-pro -> gemini-2.5-pro

Explicitly preserved (not modernized):
- llm_translation/ tests where model is the SUBJECT (provider-specific
  translation/transformation logic). Only the deprecated 20250514
  references were already bumped in a prior commit.
- Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges
  documented by the sub-agent).
- Bedrock model IDs in test_health_check.py path-stripping tests.
- JSONL batch request bodies and mock LLM response bodies (must match
  upstream literal).
- Langfuse expected-request-body JSON fixtures (cost values are exact-
  match-asserted; changing the model would shift response_cost).
- gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI
  equivalent).
- Top-level tests calling the proxy through user-facing aliases
  (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases
  in proxy_server_config.yaml stay; only the underlying model was
  bumped.
- tests/test_gpt5_azure_temperature_support.py (the test's whole point
  is model-name handling).
- Fake / mock / openai/fake identifiers.

Notable side fixes:
- test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what
  spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini),
  resolving a latent inconsistency.
- proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5`
  (bare gpt-5 is not a valid OpenAI alias).
- test_batches_logging_unit_tests.py: explicit_models list entries
  kept distinct (gpt-5-mini + gpt-5.5) after bulk rename.

* test: fix CI failures from model modernization sweep

CI surfaced 4 categories of regression from the bulk modernization:

1. Azure deployment names are customer-specific. Reverted:
   - tests/litellm_utils_tests/test_health_check.py: azure/text-
     embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure
     account does not have a text-embedding-3-small deployment).
   - tests/logging_callback_tests/test_custom_callback_router.py:
     same revert for two router fixtures driving aembedding.

2. gpt-5 family does not accept temperature != 1. Tests that pass a
   custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern
   non-reasoning OpenAI mini that still accepts temperature/logprobs):
   - tests/logging_callback_tests/test_datadog.py
   - tests/logging_callback_tests/test_langsmith_unit_test.py
   - tests/logging_callback_tests/test_otel_logging.py

3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to
   gpt-5.5 (a reasoning model that rejects logprobs). The proxy test
   tests/test_openai_endpoints.py::test_chat_completion_streaming
   exercises logprobs/top_logprobs through that alias. Bumped the
   underlying model to gpt-4.1 (non-reasoning, still modern).

4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a
   pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with
   hardcoded model="gpt-4o" and a model-specific spend value. Reverted
   the litellm.acompletion calls in the test to model="gpt-4o" so the
   fixture's exact-match assertions still hold.

5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:
   anthropic.messages.create routing to openai/gpt-5-mini returned an
   empty content[0] with max_tokens=100 (reasoning-token consumption).
   Swapped to openai/gpt-4.1-mini.

* test: fix Assistants API model + 2 cursor[bot] review nits

1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5
   isn't accepted by the /v1/assistants endpoint
   ("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants-
   API-supported, non-reasoning).

2. example_config_yaml/pass_through_config.yaml: the previous sweep
   bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a
   tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the
   Sonnet tier intact. (Cursor bugbot review.)

3. example_config_yaml/simple_config.yaml: model_name was left as
   gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which
   muddles the "simple" example. Make both sides gpt-5-mini so the
   most basic example is a straight 1:1 mapping again. (Cursor bugbot
   review.)

* fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models

tests/test_openai_endpoints.py::test_completion calls the proxy alias
"gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with
custom temperature / logprobs / the legacy /v1/completions endpoint.
The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini,
which are reasoning models that reject temperature != 1 and don't
expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini
(modern non-reasoning OpenAI models) instead — keeps user-facing
aliases preserved while picking a current underlying that still
supports the parameters/endpoints the tests exercise.
2026-05-15 15:44:28 -07:00

291 lines
8.2 KiB
Python

# What is this?
## Unit tests for the /end_users/* endpoints
import pytest
import asyncio
import aiohttp
import time
from litellm._uuid import uuid
from openai import AsyncOpenAI
from typing import Optional
"""
- `/end_user/new`
- `/end_user/info`
"""
async def chat_completion_with_headers(session, key, model="gpt-4"):
url = "http://0.0.0.0:4000/chat/completions"
headers = {
"Authorization": f"Bearer {key}",
"Content-Type": "application/json",
}
data = {
"model": model,
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
}
async with session.post(url, headers=headers, json=data) as response:
status = response.status
response_text = await response.text()
print(response_text)
print()
if status != 200:
raise Exception(f"Request did not return a 200 status code: {status}")
response_header_check(
response
) # calling the function to check response headers
raw_headers = response.raw_headers
raw_headers_json = {}
for (
item
) in (
response.raw_headers
): # ((b'date', b'Fri, 19 Apr 2024 21:17:29 GMT'), (), )
raw_headers_json[item[0].decode("utf-8")] = item[1].decode("utf-8")
return raw_headers_json
async def generate_key(
session,
i,
budget=None,
budget_duration=None,
models=["azure-models", "gpt-4", "dall-e-3"],
max_parallel_requests: Optional[int] = None,
user_id: Optional[str] = None,
team_id: Optional[str] = None,
calling_key="sk-1234",
):
url = "http://0.0.0.0:4000/key/generate"
headers = {
"Authorization": f"Bearer {calling_key}",
"Content-Type": "application/json",
}
data = {
"models": models,
"aliases": {"mistral-7b": "gpt-3.5-turbo"},
"duration": None,
"max_budget": budget,
"budget_duration": budget_duration,
"max_parallel_requests": max_parallel_requests,
"user_id": user_id,
"team_id": team_id,
}
print(f"data: {data}")
async with session.post(url, headers=headers, json=data) as response:
status = response.status
response_text = await response.text()
print(f"Response {i} (Status code: {status}):")
print(response_text)
print()
if status != 200:
raise Exception(f"Request {i} did not return a 200 status code: {status}")
return await response.json()
async def new_end_user(
session,
i,
user_id=str(uuid.uuid4()),
model_region=None,
default_model=None,
budget_id=None,
):
url = "http://0.0.0.0:4000/end_user/new"
headers = {"Authorization": "Bearer sk-1234", "Content-Type": "application/json"}
data = {
"user_id": user_id,
"allowed_model_region": model_region,
"default_model": default_model,
}
if budget_id is not None:
data["budget_id"] = budget_id
print("end user data: {}".format(data))
async with session.post(url, headers=headers, json=data) as response:
status = response.status
response_text = await response.text()
print(f"Response {i} (Status code: {status}):")
print(response_text)
print()
if status != 200:
raise Exception(f"Request {i} did not return a 200 status code: {status}")
return await response.json()
async def new_budget(session, i, budget_id=None):
url = "http://0.0.0.0:4000/budget/new"
headers = {"Authorization": "Bearer sk-1234", "Content-Type": "application/json"}
data = {
"budget_id": budget_id,
"tpm_limit": 2,
}
async with session.post(url, headers=headers, json=data) as response:
status = response.status
response_text = await response.text()
print(f"Response {i} (Status code: {status}):")
print(response_text)
print()
@pytest.mark.asyncio
async def test_end_user_new():
"""
Make 20 parallel calls to /user/new. Assert all worked.
"""
async with aiohttp.ClientSession() as session:
tasks = [new_end_user(session, i, str(uuid.uuid4())) for i in range(1, 11)]
await asyncio.gather(*tasks)
@pytest.mark.asyncio
async def test_aaaend_user_specific_region():
"""
- Specify region user can make calls in
- Make a generic call
- assert returned api base is for model in region
Repeat 3 times
"""
key: str = ""
## CREATE USER ##
async with aiohttp.ClientSession() as session:
end_user_obj = await new_end_user(
session=session,
i=0,
user_id=str(uuid.uuid4()),
model_region="eu",
)
## MAKE CALL ##
key_gen = await generate_key(
session=session, i=0, models=["gpt-5-mini-end-user-test"]
)
key = key_gen["key"]
for _ in range(3):
client = AsyncOpenAI(api_key=key, base_url="http://0.0.0.0:4000", max_retries=0)
print("SENDING USER PARAM - {}".format(end_user_obj["user_id"]))
result = await client.chat.completions.with_raw_response.create(
model="gpt-5-mini-end-user-test",
messages=[{"role": "user", "content": "Hey!"}],
user=end_user_obj["user_id"],
)
assert result.headers.get("x-litellm-model-region") == "eu"
@pytest.mark.asyncio
async def test_enduser_tpm_limits_non_master_key():
"""
1. budget_id = Create Budget with tpm_limit = 10
2. create end_user with budget_id
3. Make /chat/completions calls
4. Sleep 1 second
4. Make /chat/completions call -> expect this to fail because rate limit hit
"""
async with aiohttp.ClientSession() as session:
# create a budget with budget_id = "free-tier"
budget_id = f"free-tier-{uuid.uuid4()}"
await new_budget(session, 0, budget_id=budget_id)
await asyncio.sleep(2)
end_user_id = str(uuid.uuid4())
await new_end_user(
session=session, i=0, user_id=end_user_id, budget_id=budget_id
)
## MAKE CALL ##
key_gen = await generate_key(session=session, i=0, models=[])
key = key_gen["key"]
# chat completion 1
client = AsyncOpenAI(api_key=key, base_url="http://0.0.0.0:4000", max_retries=0)
# chat completion 2
passed = 0
for _ in range(10):
try:
result = await client.chat.completions.create(
model="fake-openai-endpoint",
messages=[{"role": "user", "content": "Hey!"}],
user=end_user_id,
)
passed += 1
except Exception:
pass
print("Passed requests=", passed)
assert (
passed < 5
), f"Sent 10 requests and end-user has tpm_limit of 2. Number requests passed: {passed}. Expected less than 5 to pass"
@pytest.mark.asyncio
async def test_enduser_tpm_limits_with_master_key():
"""
1. budget_id = Create Budget with tpm_limit = 10
2. create end_user with budget_id
3. Make /chat/completions calls
4. Sleep 1 second
4. Make /chat/completions call -> expect this to fail because rate limit hit
"""
async with aiohttp.ClientSession() as session:
# create a budget with budget_id = "free-tier"
budget_id = f"free-tier-{uuid.uuid4()}"
await new_budget(session, 0, budget_id=budget_id)
end_user_id = str(uuid.uuid4())
await new_end_user(
session=session, i=0, user_id=end_user_id, budget_id=budget_id
)
# chat completion 1
client = AsyncOpenAI(
api_key="sk-1234", base_url="http://0.0.0.0:4000", max_retries=0
)
# chat completion 2
passed = 0
for _ in range(10):
try:
result = await client.chat.completions.create(
model="fake-openai-endpoint",
messages=[{"role": "user", "content": "Hey!"}],
user=end_user_id,
)
passed += 1
except Exception:
pass
print("Passed requests=", passed)
assert (
passed < 5
), f"Sent 10 requests and end-user has tpm_limit of 2. Number requests passed: {passed}. Expected less than 5 to pass"