refining the tests

Author: timmarkhuff

test/conftest.py

@@ -6,6 +6,10 @@
 from groundlight import ExperimentalApi, Groundlight
 from model import Detector, ImageQuery, ImageQueryTypeEnum, ResultTypeEnum
 
+# No test in the suite expects a human review answer, and the server already blocks ~6s
+# for ML inference before returning. Client-side polling adds no value.
+TEST_IQ_SUBMISSION_WAIT = 0.0
+
 
 def _generate_unique_detector_name(prefix: str = "Test") -> str:
     """Generates a detector name with a timestamp and random suffix to ensure uniqueness."""
@@ -31,7 +35,7 @@ def pytest_configure(config):  # pylint: disable=unused-argument
 def fixture_gl() -> Groundlight:
     """Creates a Groundlight client object for testing."""
     _gl = Groundlight()
-    _gl.DEFAULT_WAIT = 10
+    _gl.DEFAULT_WAIT = TEST_IQ_SUBMISSION_WAIT
     return _gl
 
 
@@ -84,7 +88,7 @@ def fixture_image_query_zero(gl_experimental: Groundlight, count_detector: Detec
 @pytest.fixture(name="gl_experimental")
 def fixture_gl_experimental() -> ExperimentalApi:
     _gl = ExperimentalApi()
-    _gl.DEFAULT_WAIT = 10
+    _gl.DEFAULT_WAIT = TEST_IQ_SUBMISSION_WAIT
     return _gl
 
 

test/integration/test_groundlight.py

@@ -274,14 +274,14 @@ def test_get_detector_by_name(gl: Groundlight, detector: Detector):
 
 
 def test_ask_confident(gl: Groundlight, detector: Detector):
-    _image_query = gl.ask_confident(detector=detector.id, image="test/assets/dog.jpeg", wait=10)
+    _image_query = gl.ask_confident(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert str(_image_query)
     assert isinstance(_image_query, ImageQuery)
     assert is_valid_display_result(_image_query.result)
 
 
 def test_ask_ml(gl: Groundlight, detector: Detector):
-    _image_query = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=10)
+    _image_query = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert str(_image_query)
     assert isinstance(_image_query, ImageQuery)
     assert is_valid_display_result(_image_query.result)
@@ -294,29 +294,29 @@ def validate_image_query(_image_query: ImageQuery):
         assert is_valid_display_result(_image_query.result)
 
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=10, human_review="NEVER"
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, human_review="NEVER"
     )
     validate_image_query(_image_query)
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=3, human_review="NEVER"
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, human_review="NEVER"
     )
     validate_image_query(_image_query)
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=10, patience_time=20, human_review="NEVER"
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, patience_time=20, human_review="NEVER"
     )
     validate_image_query(_image_query)
     _image_query = gl.submit_image_query(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
     validate_image_query(_image_query)
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=180, confidence_threshold=0.75, human_review="NEVER"
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, confidence_threshold=0.75, human_review="NEVER"
     )
     validate_image_query(_image_query)
     assert _image_query.result.confidence >= IQ_IMPROVEMENT_THRESHOLD
 
 
 def test_submit_image_query_blocking(gl: Groundlight, detector: Detector):
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=10, human_review="NEVER"
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, human_review="NEVER"
     )
     assert str(_image_query)
     assert isinstance(_image_query, ImageQuery)
@@ -326,7 +326,7 @@ def test_submit_image_query_blocking(gl: Groundlight, detector: Detector):
 def test_submit_image_query_returns_yes(gl: Groundlight):
     # We use the "never-review" pipeline to guarantee a confident "yes" answer.
     detector = gl.get_or_create_detector(name="Always a dog", query="Is there a dog?", pipeline_config="never-review")
-    image_query = gl.submit_image_query(detector=detector, image="test/assets/dog.jpeg", wait=10, human_review="NEVER")
+    image_query = gl.submit_image_query(detector=detector, image="test/assets/dog.jpeg", wait=0, human_review="NEVER")
     assert image_query.result.label == Label.YES
 
 
@@ -335,7 +335,7 @@ def test_submit_image_query_returns_text(gl: Groundlight):
     detector = gl.get_or_create_detector(
         name="Always same text", query="Is there a dog?", pipeline_config="constant-text-pred"
     )
-    image_query = gl.submit_image_query(detector=detector, image="test/assets/dog.jpeg", wait=10, human_review="NEVER")
+    image_query = gl.submit_image_query(detector=detector, image="test/assets/dog.jpeg", wait=0, human_review="NEVER")
     assert isinstance(image_query.text, str)
 
 
@@ -358,7 +358,7 @@ def test_submit_image_query_with_confidence_threshold(gl: Groundlight, detector:
     _image_query = gl.submit_image_query(
         detector=detector.id,
         image="test/assets/dog.jpeg",
-        wait=10,
+        wait=0,
         confidence_threshold=confidence_threshold,
         human_review="NEVER",
     )
@@ -370,7 +370,7 @@ def test_submit_image_query_with_id(gl: Groundlight, detector: Detector):
     # submit_image_query
     id = f"iq_{KsuidMs()}"
     _image_query = gl.submit_image_query(
-        detector=detector.id, image="test/assets/dog.jpeg", wait=10, human_review="NEVER", image_query_id=id
+        detector=detector.id, image="test/assets/dog.jpeg", wait=0, human_review="NEVER", image_query_id=id
     )
     assert str(_image_query)
     assert isinstance(_image_query, ImageQuery)

test/unit/test_http_retries.py

@@ -80,7 +80,7 @@ def test_submit_image_query_attempts_retries(gl: Groundlight, detector_name: Cal
         expected_call_counts=TOTAL_RETRIES + 1,
         detector=detector_name(),
         image=IMAGE_FILE,
-        wait=1,
+        wait=0,
     )