Reduce overly long wait times in tests

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)
@@ -859,7 +859,7 @@ def test_binary_detector(gl: Groundlight, detector_name: Callable):
     name = detector_name()
     created_detector = gl.create_binary_detector(name, "Is there a dog", confidence_threshold=0.0)
     assert created_detector is not None
-    binary_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    binary_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg", wait=0)
     assert binary_iq.result.label is not None
 
 
@@ -870,7 +870,7 @@ def test_counting_detector(gl: Groundlight, detector_name: Callable):
     name = detector_name()
     created_detector = gl.create_counting_detector(name, "How many dogs", "dog", confidence_threshold=0.0)
     assert created_detector is not None
-    count_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    count_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg", wait=0)
     assert count_iq.result.count is not None
 
 
@@ -903,7 +903,7 @@ def test_multiclass_detector(gl: Groundlight, detector_name: Callable):
         name, "What kind of dog is this?", class_names=class_names, confidence_threshold=0.0
     )
     assert created_detector is not None
-    mc_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    mc_iq = gl.submit_image_query(created_detector, "test/assets/dog.jpeg", wait=0)
     assert mc_iq.result.label is not None
     assert mc_iq.result.label in class_names
 
@@ -928,7 +928,7 @@ def test_delete_detector(gl: Groundlight, detector_name: Callable):
     # Create another detector to test deletion by ID string and that an attached image query is deleted
     name2 = detector_name("Test delete detector 2")
     detector2 = gl.create_detector(name=name2, query=query, pipeline_config=pipeline_config)
-    gl.submit_image_query(detector2, "test/assets/dog.jpeg")
+    gl.submit_image_query(detector2, "test/assets/dog.jpeg", wait=0)
 
     time.sleep(10)
 

test/unit/test_cli.py

@@ -81,6 +81,8 @@ def test_detector_and_image_queries(detector_name: Callable):
             "submit-image-query",
             det_id_on_create,
             "test/assets/cat.jpeg",
+            "--wait",
+            "0",
         ],
         stdout=subprocess.PIPE,
         stderr=subprocess.PIPE,

test/unit/test_experimental.py

@@ -99,7 +99,7 @@ def test_text_recognition_detector(gl_experimental: ExperimentalApi, detector_na
         name, "What is the date and time?", confidence_threshold=0.0
     )
     assert created_detector is not None
-    mc_iq = gl_experimental.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    mc_iq = gl_experimental.submit_image_query(created_detector, "test/assets/dog.jpeg", wait=0)
     assert mc_iq.result.text is not None
 
 
@@ -112,7 +112,7 @@ def test_bounding_box_detector(gl_experimental: ExperimentalApi, detector_name:
         name, "Draw a bounding box around each dog in the image", "dog", confidence_threshold=0.0
     )
     assert created_detector is not None
-    bbox_iq = gl_experimental.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    bbox_iq = gl_experimental.submit_image_query(created_detector, "test/assets/dog.jpeg", wait=0)
     assert bbox_iq.result.label is not None
     assert bbox_iq.rois is not None
 

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,
     )
 
 

test/unit/test_images.py

@@ -7,6 +7,6 @@
 def test_get_image(gl_experimental: ExperimentalApi):
     name = f"Test {datetime.utcnow()}"
     det = gl_experimental.get_or_create_detector(name, "test_query")
-    iq = gl_experimental.submit_image_query(det, image="test/assets/dog.jpeg", wait=10)
+    iq = gl_experimental.submit_image_query(det, image="test/assets/dog.jpeg", wait=0)
     gl_experimental.get_image(iq.id)
     assert isinstance(PIL.Image.open(gl_experimental.get_image(iq.id)), PIL.Image.Image)

test/unit/test_labels.py

@@ -7,7 +7,7 @@
 def test_binary_labels(gl_experimental: ExperimentalApi):
     name = f"Test binary labels{datetime.utcnow()}"
     det = gl_experimental.create_detector(name, "test_query")
-    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", wait=0)
     gl_experimental.add_label(iq1, "YES")
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.label == "YES"
@@ -24,7 +24,7 @@ def test_binary_labels(gl_experimental: ExperimentalApi):
 def test_counting_labels(gl_experimental: ExperimentalApi):
     name = f"Test binary labels{datetime.utcnow()}"
     det = gl_experimental.create_counting_detector(name, "test_query", "test_object_class")
-    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", wait=0)
 
     gl_experimental.add_label(iq1, 0)
     iq1 = gl_experimental.get_image_query(iq1.id)
@@ -48,7 +48,7 @@ def test_counting_labels(gl_experimental: ExperimentalApi):
 def test_multiclass_labels(gl_experimental: ExperimentalApi):
     name = f"Test binary labels{datetime.utcnow()}"
     det = gl_experimental.create_multiclass_detector(name, "test_query", class_names=["apple", "banana", "cherry"])
-    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", wait=0)
     gl_experimental.add_label(iq1, "apple")
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.label == "apple"
@@ -69,7 +69,7 @@ def test_multiclass_labels(gl_experimental: ExperimentalApi):
 def test_bounding_box_labels(gl_experimental: ExperimentalApi):
     name = f"Test bounding box labels{datetime.utcnow()}"
     det = gl_experimental.create_bounding_box_detector(name, "test_query", "test_class")
-    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", wait=0)
     gl_experimental.add_label(iq1, "NO_OBJECTS")
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.label == "NO_OBJECTS"
@@ -87,7 +87,7 @@ def test_bounding_box_labels(gl_experimental: ExperimentalApi):
 def test_text_recognition_labels(gl_experimental: ExperimentalApi):
     name = f"Test text recognition labels{datetime.utcnow()}"
     det = gl_experimental.create_text_recognition_detector(name, "test_query")
-    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+    iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", wait=0)
     gl_experimental.add_label(iq1, "apple text")
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.text == "apple text"