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Fix test_async_fallbacks_streaming to use mock_response instead of real API

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The test was failing because it depended on real API calls to deprecated
models. Now uses mock_response to validate streaming through the router
without external dependencies.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
yuneng-jiang
2026-03-14 23:45:40 -07:00
co-authored by Claude Opus 4.6
parent f73ff72ab5
commit bcd887ea61
1 changed files with 15 additions and 50 deletions
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tests/local_testing/test_router_fallbacks.py
+15 -50
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@@ -500,55 +500,25 @@ async def test_dynamic_fallbacks_async():
@pytest.mark.asyncio
async def test_async_fallbacks_streaming():
"""Test that router.acompletion with stream=True and mock_response works correctly."""
litellm.set_verbose = False
model_list = [
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
{
"model_name": "azure/gpt-3.5-turbo",
"litellm_params": {
"model": "azure/gpt-4.1-mini",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{ # list of model deployments
"model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/gpt-4.1-mini",
"api_key": os.getenv("AZURE_API_KEY"),
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
"api_key": "fake-key",
"api_version": "2024-01-01",
"api_base": "https://fake.openai.azure.com",
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "azure/gpt-3.5-turbo", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "azure/chatgpt-functioncalling",
"api_key": "bad-key",
"api_version": os.getenv("AZURE_API_VERSION"),
"api_base": os.getenv("AZURE_API_BASE"),
},
"tpm": 240000,
"rpm": 1800,
},
{
"model_name": "gpt-4o-mini", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model_name": "gpt-4o-mini",
"litellm_params": {
"model": "gpt-4o-mini",
"api_key": os.getenv("OPENAI_API_KEY"),
},
"tpm": 1000000,
"rpm": 9000,
},
{
"model_name": "gpt-4o-mini-context", # openai model name
"litellm_params": { # params for litellm completion/embedding call
"model": "gpt-4o-mini",
"api_key": os.getenv("OPENAI_API_KEY"),
"api_key": "fake-key",
},
"tpm": 1000000,
"rpm": 9000,
@@ -558,27 +528,22 @@ async def test_async_fallbacks_streaming():
router = Router(
model_list=model_list,
fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-4o-mini"]}],
context_window_fallbacks=[
{"azure/gpt-3.5-turbo-context-fallback": ["gpt-4o-mini-context"]},
{"gpt-4o-mini": ["gpt-4o-mini-context"]},
],
set_verbose=False,
)
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
try:
response = await router.acompletion(
model="azure/gpt-3.5-turbo",
messages=[{"role": "user", "content": user_message}],
stream=True,
mock_response="This is a mock streaming response",
)
print(f"customHandler.previous_models: {customHandler.previous_models}")
await asyncio.sleep(
0.05
) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 3 # 1 init call + 2 retries (fallback not counted as previous)
chunks = []
async for chunk in response:
chunks.append(chunk)
assert len(chunks) > 0, "Expected at least one streaming chunk"
router.reset()
except litellm.Timeout as e:
pass