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test(langchain): Replace mocks with httpx types #5724

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a4ed760
test(langchain): Replace mocks with httpx types
alexander-alderman-webb Mar 20, 2026
f8d42e9
different function
alexander-alderman-webb Mar 20, 2026
258e72e
Merge branch 'webb/langchain/span-origin' into webb/langchain/remove-…
alexander-alderman-webb Mar 20, 2026
ae4f8d3
remove unused variable
alexander-alderman-webb Mar 20, 2026
b693ad2
fix undefined global
alexander-alderman-webb Mar 20, 2026
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8 changes: 6 additions & 2 deletions tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1018,10 +1018,14 @@ async def inner(values):

@pytest.fixture
def server_side_event_chunks():
def inner(events):
def inner(events, include_event_type=True):
for event in events:
payload = event.model_dump()
chunk = f"event: {payload['type']}\ndata: {json.dumps(payload)}\n\n"
chunk = (
f"event: {payload['type']}\ndata: {json.dumps(payload)}\n\n"
if include_event_type
else f"data: {json.dumps(payload)}\n\n"
)
yield chunk.encode("utf-8")

return inner
Expand Down
285 changes: 204 additions & 81 deletions tests/integrations/langchain/test_langchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,21 @@
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder


from openai.types.chat.chat_completion_chunk import (
ChatCompletionChunk,
Choice,
ChoiceDelta,
ChoiceDeltaToolCall,
ChoiceDeltaToolCallFunction,
)

from openai.types.completion_usage import (
CompletionTokensDetails,
CompletionUsage,
PromptTokensDetails,
)


@tool
def get_word_length(word: str) -> int:
"""Returns the length of a word."""
Expand Down Expand Up @@ -67,12 +82,12 @@ def _llm_type(self) -> str:


@pytest.mark.parametrize(
"send_default_pii, include_prompts, use_unknown_llm_type",
"send_default_pii, include_prompts",
[
(True, True, False),
(True, False, False),
(False, True, False),
(False, False, True),
(True, True),
(True, False),
(False, True),
(False, False),
],
)
@pytest.mark.parametrize(
Expand All @@ -92,13 +107,11 @@ def test_langchain_agent(
capture_events,
send_default_pii,
include_prompts,
use_unknown_llm_type,
system_instructions_content,
request,
get_model_response,
server_side_event_chunks,
):
global llm_type
llm_type = "acme-llm" if use_unknown_llm_type else "openai-chat"

sentry_init(
integrations=[
LangchainIntegration(
Expand All @@ -120,87 +133,189 @@ def test_langchain_agent(
MessagesPlaceholder(variable_name="agent_scratchpad"),
]
)
global stream_result_mock
stream_result_mock = Mock(
side_effect=[

tool_response = get_model_response(
server_side_event_chunks(
[
ChatGenerationChunk(
type="ChatGenerationChunk",
message=AIMessageChunk(
content="",
additional_kwargs={
"tool_calls": [
{
"index": 0,
"id": "call_BbeyNhCKa6kYLYzrD40NGm3b",
"function": {
"arguments": "",
"name": "get_word_length",
},
"type": "function",
}
]
},
),
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(role="assistant"),
finish_reason=None,
),
],
),
ChatGenerationChunk(
type="ChatGenerationChunk",
message=AIMessageChunk(
content="",
additional_kwargs={
"tool_calls": [
{
"index": 0,
"id": None,
"function": {
"arguments": '{"word": "eudca"}',
"name": None,
},
"type": None,
}
]
},
),
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(
tool_calls=[
ChoiceDeltaToolCall(
index=0,
id="call_BbeyNhCKa6kYLYzrD40NGm3b",
type="function",
function=ChoiceDeltaToolCallFunction(
name="get_word_length",
arguments="",
),
),
],
),
finish_reason=None,
),
],
),
ChatGenerationChunk(
type="ChatGenerationChunk",
message=AIMessageChunk(
content="5",
usage_metadata={
"input_tokens": 142,
"output_tokens": 50,
"total_tokens": 192,
"input_token_details": {"audio": 0, "cache_read": 0},
"output_token_details": {"audio": 0, "reasoning": 0},
},
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(
tool_calls=[
ChoiceDeltaToolCall(
index=0,
function=ChoiceDeltaToolCallFunction(
arguments='{"word": "eudca"}',
),
),
],
),
finish_reason=None,
),
],
),
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(content="5"),
finish_reason=None,
),
],
),
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(),
finish_reason="function_call",
),
],
),
ChatCompletionChunk(
id="chatcmpl-turn-1",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[],
usage=CompletionUsage(
prompt_tokens=142,
completion_tokens=50,
total_tokens=192,
prompt_tokens_details=PromptTokensDetails(
audio_tokens=0,
cached_tokens=0,
),
completion_tokens_details=CompletionTokensDetails(
audio_tokens=0,
reasoning_tokens=0,
),
),
generation_info={"finish_reason": "function_call"},
),
],
include_event_type=False,
)
)

final_response = get_model_response(
server_side_event_chunks(
[
ChatGenerationChunk(
text="The word eudca has 5 letters.",
type="ChatGenerationChunk",
message=AIMessageChunk(
content="The word eudca has 5 letters.",
usage_metadata={
"input_tokens": 89,
"output_tokens": 28,
"total_tokens": 117,
"input_token_details": {"audio": 0, "cache_read": 0},
"output_token_details": {"audio": 0, "reasoning": 0},
},
),
ChatCompletionChunk(
id="chatcmpl-turn-2",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(role="assistant"),
finish_reason=None,
),
],
),
ChatGenerationChunk(
type="ChatGenerationChunk",
generation_info={"finish_reason": "stop"},
message=AIMessageChunk(content=""),
ChatCompletionChunk(
id="chatcmpl-turn-2",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(content="The word eudca has 5 letters."),
finish_reason=None,
),
],
),
ChatCompletionChunk(
id="chatcmpl-turn-2",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[
Choice(
index=0,
delta=ChoiceDelta(),
finish_reason="stop",
),
],
),
ChatCompletionChunk(
id="chatcmpl-turn-2",
object="chat.completion.chunk",
created=10000000,
model="gpt-3.5-turbo",
choices=[],
usage=CompletionUsage(
prompt_tokens=89,
completion_tokens=28,
total_tokens=117,
prompt_tokens_details=PromptTokensDetails(
audio_tokens=0,
cached_tokens=0,
),
completion_tokens_details=CompletionTokensDetails(
audio_tokens=0,
reasoning_tokens=0,
),
),
),
],
]
include_event_type=False,
)
)
llm = MockOpenAI(

llm = ChatOpenAI(
model_name="gpt-3.5-turbo",
temperature=0,
openai_api_key="badkey",
Expand All @@ -209,8 +324,13 @@ def test_langchain_agent(

agent_executor = AgentExecutor(agent=agent, tools=[get_word_length], verbose=True)

with start_transaction():
list(agent_executor.stream({"input": "How many letters in the word eudca"}))
with patch.object(
llm.client._client._client,
"send",
side_effect=[tool_response, final_response],
) as _:
with start_transaction():
list(agent_executor.stream({"input": "How many letters in the word eudca"}))

tx = events[0]
assert tx["type"] == "transaction"
Expand Down Expand Up @@ -316,6 +436,9 @@ def test_langchain_agent(


def test_langchain_error(sentry_init, capture_events):
global llm_type
llm_type = "acme-llm"

sentry_init(
integrations=[LangchainIntegration(include_prompts=True)],
traces_sample_rate=1.0,
Expand Down
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