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chore(recorder): update mocks to be closer to non-mock environment (#3442)

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# What does this PR do?

the @required_args decorator in openai-python is masking the async
nature of the {AsyncCompletions,chat.AsyncCompletions}.create method.
see https://github.com/openai/openai-python/issues/996

this means two things -

 0. we cannot use iscoroutine in the recorder to detect async vs non
 1. our mocks are inappropriately introducing identifiable async

for (0), we update the iscoroutine check w/ detection of /v1/models,
which is the only non-async function we mock & record.

for (1), we could leave everything as is and assume (0) will catch
errors. to be defensive, we update the unit tests to mock below create
methods, allowing the true openai-python create() methods to be tested.
This commit is contained in:
Matthew Farrellee 2025-09-15 15:25:53 -04:00 • committed by GitHub
parent b6cb817897
commit 01bdcce4d2
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2 changed files with 113 additions and 109 deletions
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14
llama_stack/testing/inference_recorder.py
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@ -7,7 +7,6 @@
from __future__ import annotations # for forward references
import hashlib
import inspect
import json
import os
from collections.abc import Generator
@ -243,11 +242,10 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
global _current_mode, _current_storage
if _current_mode == InferenceMode.LIVE or _current_storage is None:
# Normal operation
if inspect.iscoroutinefunction(original_method):
return await original_method(self, *args, **kwargs)
else:
if endpoint == "/v1/models":
return original_method(self, *args, **kwargs)
else:
return await original_method(self, *args, **kwargs)
# Get base URL based on client type
if client_type == "openai":
@ -298,10 +296,10 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
)
elif _current_mode == InferenceMode.RECORD:
if inspect.iscoroutinefunction(original_method):
response = await original_method(self, *args, **kwargs)
else:
if endpoint == "/v1/models":
response = original_method(self, *args, **kwargs)
else:
response = await original_method(self, *args, **kwargs)
# we want to store the result of the iterator, not the iterator itself
if endpoint == "/v1/models":