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test(litellm): Replace mocks with httpx types in embedding tests #5970

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c5b92c8
test(litellm): Remove mocks with httpx types in embedding tests
alexander-alderman-webb Apr 10, 2026
ad16c7f
test(litellm): Replace mocks with httpx types in rate-limit test
alexander-alderman-webb Apr 10, 2026
dda374f
Merge branch 'webb/litellm/remove-mocks' into webb/litellm/embedding-…
alexander-alderman-webb Apr 10, 2026
b622a07
Merge branch 'webb/litellm/embedding-tests' into webb/litellm/error-mock
alexander-alderman-webb Apr 10, 2026
598d6b5
undo merge
alexander-alderman-webb Apr 10, 2026
a8689cd
remove fixture
alexander-alderman-webb Apr 10, 2026
d9cf8b0
Merge branch 'webb/litellm/remove-mocks' into webb/litellm/embedding-…
alexander-alderman-webb Apr 10, 2026
a2b3585
make request headers consistent
alexander-alderman-webb Apr 10, 2026
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19 changes: 19 additions & 0 deletions tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1218,6 +1218,25 @@ def nonstreaming_chat_completions_model_response():
)


@pytest.fixture
def openai_embedding_model_response():
return openai.types.CreateEmbeddingResponse(
data=[
openai.types.Embedding(
embedding=[0.1, 0.2, 0.3],
index=0,
object="embedding",
)
],
model="text-embedding-ada-002",
object="list",
usage=openai.types.create_embedding_response.Usage(
prompt_tokens=5,
total_tokens=5,
),
)


@pytest.fixture
def nonstreaming_responses_model_response():
return openai.types.responses.Response(
Expand Down
141 changes: 76 additions & 65 deletions tests/integrations/litellm/test_litellm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -128,38 +128,6 @@ def __init__(
self.created = 1234567890


class MockEmbeddingData:
def __init__(self, embedding=None):
self.embedding = embedding or [0.1, 0.2, 0.3]
self.index = 0
self.object = "embedding"


class MockEmbeddingResponse:
def __init__(self, model="text-embedding-ada-002", data=None, usage=None):
self.model = model
self.data = data or [MockEmbeddingData()]
self.usage = usage or MockUsage(
prompt_tokens=5, completion_tokens=0, total_tokens=5
)
self.object = "list"

def model_dump(self):
return {
"model": self.model,
"data": [
{"embedding": d.embedding, "index": d.index, "object": d.object}
for d in self.data
],
"usage": {
"prompt_tokens": self.usage.prompt_tokens,
"completion_tokens": self.usage.completion_tokens,
"total_tokens": self.usage.total_tokens,
},
"object": self.object,
}


@pytest.mark.parametrize(
"send_default_pii, include_prompts",
[
Expand Down Expand Up @@ -313,7 +281,13 @@ def test_streaming_chat_completion(
assert span["data"][SPANDATA.GEN_AI_RESPONSE_STREAMING] is True


def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
def test_embeddings_create(
sentry_init,
capture_events,
get_model_response,
openai_embedding_model_response,
clear_litellm_cache,
):
"""
Test that litellm.embedding() calls are properly instrumented.

Expand All @@ -327,20 +301,24 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
)
events = capture_events()

mock_response = MockEmbeddingResponse()
client = OpenAI(api_key="z")

# Mock within the test to ensure proper ordering with cache clearing
with mock.patch(
"litellm.openai_chat_completions.make_sync_openai_embedding_request"
) as mock_http:
# The function returns (headers, response)
mock_http.return_value = ({}, mock_response)
model_response = get_model_response(
openai_embedding_model_response,
serialize_pydantic=True,
request_headers={"X-Stainless-Raw-Response": "true"},
)

with mock.patch.object(
client.embeddings._client._client,
"send",
return_value=model_response,
):
with start_transaction(name="litellm test"):
response = litellm.embedding(
model="text-embedding-ada-002",
input="Hello, world!",
api_key="test-key", # Provide a fake API key to avoid authentication errors
client=client,
)
# Allow time for callbacks to complete (they may run in separate threads)
time.sleep(0.1)
Expand All @@ -351,8 +329,13 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):
(event,) = events

assert event["type"] == "transaction"
assert len(event["spans"]) == 1
(span,) = event["spans"]
spans = list(
x
for x in event["spans"]
if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
)
assert len(spans) == 1
span = spans[0]

assert span["op"] == OP.GEN_AI_EMBEDDINGS
assert span["description"] == "embeddings text-embedding-ada-002"
Expand All @@ -365,7 +348,11 @@ def test_embeddings_create(sentry_init, capture_events, clear_litellm_cache):


def test_embeddings_create_with_list_input(
sentry_init, capture_events, clear_litellm_cache
sentry_init,
capture_events,
get_model_response,
openai_embedding_model_response,
clear_litellm_cache,
):
"""Test embedding with list input."""
sentry_init(
Expand All @@ -375,20 +362,24 @@ def test_embeddings_create_with_list_input(
)
events = capture_events()

mock_response = MockEmbeddingResponse()
client = OpenAI(api_key="z")

# Mock within the test to ensure proper ordering with cache clearing
with mock.patch(
"litellm.openai_chat_completions.make_sync_openai_embedding_request"
) as mock_http:
# The function returns (headers, response)
mock_http.return_value = ({}, mock_response)
model_response = get_model_response(
openai_embedding_model_response,
serialize_pydantic=True,
request_headers={"X-Stainless-Raw-Response": "true"},
)

with mock.patch.object(
client.embeddings._client._client,
"send",
return_value=model_response,
):
with start_transaction(name="litellm test"):
response = litellm.embedding(
model="text-embedding-ada-002",
input=["First text", "Second text", "Third text"],
api_key="test-key", # Provide a fake API key to avoid authentication errors
client=client,
)
# Allow time for callbacks to complete (they may run in separate threads)
time.sleep(0.1)
Expand All @@ -399,8 +390,13 @@ def test_embeddings_create_with_list_input(
(event,) = events

assert event["type"] == "transaction"
assert len(event["spans"]) == 1
(span,) = event["spans"]
spans = list(
x
for x in event["spans"]
if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
)
assert len(spans) == 1
span = spans[0]

assert span["op"] == OP.GEN_AI_EMBEDDINGS
assert span["data"][SPANDATA.GEN_AI_OPERATION_NAME] == "embeddings"
Expand All @@ -413,7 +409,13 @@ def test_embeddings_create_with_list_input(
]


def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
def test_embeddings_no_pii(
sentry_init,
capture_events,
get_model_response,
openai_embedding_model_response,
clear_litellm_cache,
):
"""Test that PII is not captured when disabled."""
sentry_init(
integrations=[LiteLLMIntegration(include_prompts=True)],
Expand All @@ -422,20 +424,24 @@ def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
)
events = capture_events()

mock_response = MockEmbeddingResponse()
client = OpenAI(api_key="z")

# Mock within the test to ensure proper ordering with cache clearing
with mock.patch(
"litellm.openai_chat_completions.make_sync_openai_embedding_request"
) as mock_http:
# The function returns (headers, response)
mock_http.return_value = ({}, mock_response)
model_response = get_model_response(
openai_embedding_model_response,
serialize_pydantic=True,
request_headers={"X-Stainless-Raw-Response": "true"},
)

with mock.patch.object(
client.embeddings._client._client,
"send",
return_value=model_response,
):
with start_transaction(name="litellm test"):
response = litellm.embedding(
model="text-embedding-ada-002",
input="Hello, world!",
api_key="test-key", # Provide a fake API key to avoid authentication errors
client=client,
)
# Allow time for callbacks to complete (they may run in separate threads)
time.sleep(0.1)
Expand All @@ -446,8 +452,13 @@ def test_embeddings_no_pii(sentry_init, capture_events, clear_litellm_cache):
(event,) = events

assert event["type"] == "transaction"
assert len(event["spans"]) == 1
(span,) = event["spans"]
spans = list(
x
for x in event["spans"]
if x["op"] == OP.GEN_AI_EMBEDDINGS and x["origin"] == "auto.ai.litellm"
)
assert len(spans) == 1
span = spans[0]

assert span["op"] == OP.GEN_AI_EMBEDDINGS
# Check that embeddings input is NOT captured when PII is disabled
Expand Down
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