From 2b09e7936215208f03682205800d48e0dc4e21f1 Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 19:10:45 +0000
Subject: [PATCH 1/9] fixing flaky test

---
 test/unit/test_http_retries.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/unit/test_http_retries.py b/test/unit/test_http_retries.py
index 42ab0caf..106c871f 100644
--- a/test/unit/test_http_retries.py
+++ b/test/unit/test_http_retries.py
@@ -1,6 +1,7 @@
 from datetime import datetime
 from typing import Any, Callable
 from unittest import mock
+from uuid import uuid4
 
 import pytest
 from groundlight import Groundlight
@@ -9,7 +10,7 @@
 from model import Detector
 
 DEFAULT_CONFIDENCE_THRESHOLD = 0.9
-DETECTOR_NAME = f"test detector_{datetime.utcnow().strftime('%Y=%m-%d %H:%M:%S')}"
+DETECTOR_NAME = f"test detector_{datetime.utcnow().strftime('%Y=%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
 TOTAL_RETRIES = 3
 STATUS_CODES = range(500, 505)
 IMAGE_FILE = "test/assets/dog.jpeg"

From ee49af58db1c8347e96e494d04531ab3a98c9237 Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 21:12:00 +0000
Subject: [PATCH 2/9] applying the fix in more places

---
 test/conftest.py                              | 12 +++--
 test/integration/test_groundlight.py          | 44 +++++++++----------
 .../integration/test_groundlight_expensive.py |  8 ++--
 test/unit/test_cli.py                         |  5 ++-
 test/unit/test_detector_reset.py              |  6 +--
 test/unit/test_experimental.py                | 16 +++----
 test/unit/test_http_retries.py                |  5 +--
 7 files changed, 50 insertions(+), 46 deletions(-)

diff --git a/test/conftest.py b/test/conftest.py
index bde11be8..0bfe06e0 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -1,10 +1,16 @@
 from datetime import datetime
+from uuid import uuid4
 
 import pytest
 from groundlight import ExperimentalApi, Groundlight
 from model import Detector, ImageQuery, ImageQueryTypeEnum, ResultTypeEnum
 
 
+def generate_test_detector_name(prefix: str = "Test") -> str:
+    """Generates a unique detector name with a timestamp and random suffix to avoid collisions in parallel CI."""
+    return f"{prefix} {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
+
+
 def pytest_configure(config):  # pylint: disable=unused-argument
     # Run environment check before tests
     gl = Groundlight()
@@ -25,20 +31,18 @@ def fixture_gl() -> Groundlight:
 @pytest.fixture(name="detector")
 def fixture_detector(gl: Groundlight) -> Detector:
     """Creates a new Test detector."""
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
     query = "Is there a dog?"
     pipeline_config = "never-review"
-    return gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
+    return gl.create_detector(name=generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
 
 
 @pytest.fixture(name="count_detector")
 def fixture_count_detector(gl_experimental: ExperimentalApi) -> Detector:
     """Creates a new Test detector."""
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
     query = "How many dogs?"
     pipeline_config = "never-review-multi"  # always predicts 0
     return gl_experimental.create_counting_detector(
-        name=name, query=query, class_name="dog", pipeline_config=pipeline_config
+        name=generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
     )
 
 
diff --git a/test/integration/test_groundlight.py b/test/integration/test_groundlight.py
index 5d48c1cd..4cbd7f7d 100644
--- a/test/integration/test_groundlight.py
+++ b/test/integration/test_groundlight.py
@@ -5,10 +5,10 @@
 import random
 import string
 import time
-from datetime import datetime
 from typing import Any, Dict, Optional, Union
 
 import pytest
+from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.binary_labels import VALID_DISPLAY_LABELS, Label, convert_internal_label_to_display
 from groundlight.internalapi import ApiException, InternalApiError, NotFoundError
@@ -97,7 +97,7 @@ def test_create_groundlight_with_retries():
 
 
 def test_create_detector(gl: Groundlight):
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name()
     query = "Is there a dog?"
     _detector = gl.create_detector(name=name, query=query)
     assert str(_detector)
@@ -107,12 +107,12 @@ def test_create_detector(gl: Groundlight):
     ), "We expected the default confidence threshold to be used."
 
     # Test creating dectors with other modes
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
-    count_detector = gl.create_detector(name=name, query=query, mode=ModeEnum.COUNT, class_names="dog")
+    count_detector = gl.create_detector(
+        name=generate_test_detector_name(), query=query, mode=ModeEnum.COUNT, class_names="dog"
+    )
     assert str(count_detector)
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
     multiclass_detector = gl.create_detector(
-        name=name, query=query, mode=ModeEnum.MULTI_CLASS, class_names=["dog", "cat"]
+        name=generate_test_detector_name(), query=query, mode=ModeEnum.MULTI_CLASS, class_names=["dog", "cat"]
     )
     assert str(multiclass_detector)
 
@@ -120,7 +120,7 @@ def test_create_detector(gl: Groundlight):
 def test_create_detector_with_pipeline_config(gl: Groundlight):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
-    name = f"Test never-review {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name("Test never-review")
     query = "Is there a dog (always-pass)?"
     pipeline_config = "never-review"
     _detector = gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
@@ -129,7 +129,7 @@ def test_create_detector_with_pipeline_config(gl: Groundlight):
 
 
 def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
-    name = f"Test edge-pipeline-config {datetime.utcnow()}"
+    name = generate_test_detector_name("Test edge-pipeline-config")
     query = "Is there a dog (edge-config)?"
     _detector = gl.create_detector(
         name=name,
@@ -144,7 +144,7 @@ def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
 def test_create_detector_with_confidence_threshold(gl: Groundlight):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
-    name = f"Test with confidence {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name("Test with confidence")
     query = "Is there a dog in the image?"
     pipeline_config = "never-review"
     confidence_threshold = 0.825
@@ -198,7 +198,7 @@ def test_create_detector_with_confidence_threshold(gl: Groundlight):
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
 def test_create_detector_with_everything(gl: Groundlight):
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name()
     query = "Is there a dog?"
     group_name = "Test group"
     confidence_threshold = 0.825
@@ -234,7 +234,7 @@ def test_list_detectors(gl: Groundlight):
 
 def test_get_or_create_detector(gl: Groundlight):
     # With a unique name, we should be creating a new detector.
-    unique_name = f"Unique name {datetime.utcnow()}"
+    unique_name = generate_test_detector_name()
     query = "Is there a dog?"
     detector = gl.get_or_create_detector(name=unique_name, query=query)
     assert str(detector)
@@ -411,7 +411,7 @@ def test_submit_image_query_with_low_request_timeout(gl: Groundlight, detector:
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
 def test_create_detector_with_metadata(gl: Groundlight):
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
     detector = gl.create_detector(name=name, query=query, metadata=metadata)
@@ -423,7 +423,7 @@ def test_create_detector_with_metadata(gl: Groundlight):
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
 def test_get_or_create_detector_with_metadata(gl: Groundlight):
-    unique_name = f"Unique name {datetime.utcnow()}"
+    unique_name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
     detector = gl.get_or_create_detector(name=unique_name, query=query, metadata=metadata)
@@ -444,7 +444,7 @@ def test_get_or_create_detector_with_metadata(gl: Groundlight):
     ],
 )
 def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any):
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name()
     query = "Is there a dog?"
 
     for metadata in metadata_list:
@@ -629,7 +629,7 @@ def test_list_image_queries(gl: Groundlight):
 
 def test_list_image_queries_with_filter(gl: Groundlight):
     # We want a fresh detector so we know exactly what image queries are associated with it
-    detector = gl.create_detector(name=f"Test {datetime.utcnow()}", query="Is there a dog?")
+    detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     image_query_yes = gl.ask_async(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
     image_query_no = gl.ask_async(detector=detector.id, image="test/assets/cat.jpeg", human_review="NEVER")
     iq_ids = [image_query_yes.id, image_query_no.id]
@@ -859,7 +859,7 @@ def test_binary_detector(gl: Groundlight):
     """
     verify that we can create and submit to a binary detector
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_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")
@@ -870,7 +870,7 @@ def test_counting_detector(gl: Groundlight):
     """
     verify that we can create and submit to a counting detector
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_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")
@@ -881,7 +881,7 @@ def test_counting_detector_async(gl: Groundlight):
     """
     verify that we can create and submit to a counting detector
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_detector_name()
     created_detector = gl.create_counting_detector(name, "How many dogs", "dog", confidence_threshold=0.0)
     assert created_detector is not None
     async_iq = gl.ask_async(created_detector, "test/assets/dog.jpeg")
@@ -900,7 +900,7 @@ def test_multiclass_detector(gl: Groundlight):
     """
     verify that we can create and submit to a multi-class detector
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_detector_name()
     class_names = ["Golden Retriever", "Labrador Retriever", "Poodle"]
     created_detector = gl.create_multiclass_detector(
         name, "What kind of dog is this?", class_names=class_names, confidence_threshold=0.0
@@ -916,7 +916,7 @@ def test_delete_detector(gl: Groundlight):
     Test deleting a detector by both ID and object, and verify proper error handling.
     """
     # Create a detector to delete
-    name = f"Test delete detector {datetime.utcnow()}"
+    name = generate_test_detector_name("Test delete detector")
     query = "Is there a dog to delete?"
     pipeline_config = "never-review"
     detector = gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
@@ -929,7 +929,7 @@ def test_delete_detector(gl: Groundlight):
         gl.get_detector(detector.id)
 
     # Create another detector to test deletion by ID string and that an attached image query is deleted
-    name2 = f"Test delete detector 2 {datetime.utcnow()}"
+    name2 = generate_test_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")
 
@@ -959,7 +959,7 @@ def test_create_detector_with_invalid_priming_group_id(gl: Groundlight):
     Note: PrimingGroup IDs are provided by Groundlight representatives. If you would like to
     use a priming_group_id, please reach out to your Groundlight representative.
     """
-    name = f"Test invalid priming {datetime.utcnow()}"
+    name = generate_test_detector_name("Test invalid priming")
     query = "Is there a dog?"
     pipeline_config = "never-review"
     priming_group_id = "prgrp_nonexistent12345678901234567890"
diff --git a/test/integration/test_groundlight_expensive.py b/test/integration/test_groundlight_expensive.py
index a45888c4..1693c8a3 100644
--- a/test/integration/test_groundlight_expensive.py
+++ b/test/integration/test_groundlight_expensive.py
@@ -7,9 +7,9 @@
 # pylint: disable=wildcard-import,unused-wildcard-import,redefined-outer-name,import-outside-toplevel
 import random
 import time
-from datetime import datetime
 
 import pytest
+from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.internalapi import iq_is_answered, iq_is_confident
 from groundlight.optional_imports import *
@@ -31,7 +31,7 @@ def fixture_gl() -> Groundlight:
 
 @pytest.mark.skip(reason="This test requires a human labeler who does not need to be in the testing loop")
 def test_human_label(gl: Groundlight):
-    detector = gl.create_detector(name=f"Test {datetime.utcnow()}", query="Is there a dog?")
+    detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     img_query = gl.submit_image_query(
         detector=detector.id, image="test/assets/dog.jpeg", wait=60, human_review="ALWAYS"
     )
@@ -61,7 +61,7 @@ def test_detector_improvement(gl: Groundlight):
 
     random.seed(2741)
 
-    name = f"Test test_detector_improvement {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name("Test test_detector_improvement")
     query = "Is there a dog?"
     detector = gl.create_detector(name=name, query=query)
 
@@ -126,7 +126,7 @@ def test_ask_method_quality(gl: Groundlight, detector: Detector):
     # asks for some level of quality on how fast ask_ml is and that we will get a confident result from ask_confident
     fast_always_yes_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert iq_is_answered(fast_always_yes_iq)
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    name = generate_test_detector_name()
     query = "Is there a dog?"
     detector = gl.create_detector(name=name, query=query, confidence_threshold=0.8)
     fast_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
diff --git a/test/unit/test_cli.py b/test/unit/test_cli.py
index 38cc676c..90c368f7 100644
--- a/test/unit/test_cli.py
+++ b/test/unit/test_cli.py
@@ -1,9 +1,10 @@
 import os
 import re
 import subprocess
-from datetime import datetime
 from unittest.mock import patch
 
+from conftest import generate_test_detector_name
+
 
 def test_whoami():
     completed_process = subprocess.run(
@@ -25,7 +26,7 @@ def test_list_detector():
 
 def test_detector_and_image_queries():
     # test creating a detector
-    test_detector_name = f"testdetector {datetime.utcnow()}"
+    test_detector_name = generate_test_detector_name("testdetector")
     completed_process = subprocess.run(
         [
             "groundlight",
diff --git a/test/unit/test_detector_reset.py b/test/unit/test_detector_reset.py
index 67b88514..3be962ce 100644
--- a/test/unit/test_detector_reset.py
+++ b/test/unit/test_detector_reset.py
@@ -1,7 +1,7 @@
 import time
-from datetime import datetime
 
 import pytest
+from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from groundlight_openapi_client.exceptions import NotFoundException
 
@@ -9,7 +9,7 @@
 @pytest.mark.skip(reason="This is an expensive test, reset may take some time")
 def test_reset_retry(gl_experimental: ExperimentalApi):
     # Reset the detector, retrying in case the reset is still ongoing
-    det = gl_experimental.create_detector(f"Test {datetime.utcnow()}", "test_query")
+    det = gl_experimental.create_detector(generate_test_detector_name(), "test_query")
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
     gl_experimental.reset_detector(det.id)
     success = False
@@ -30,7 +30,7 @@ def test_reset_retry(gl_experimental: ExperimentalApi):
 def test_reset_training(gl_experimental: ExperimentalApi):
     # If we reset a detector, we should have low confidence after the reset
     low_confidence_threshold = 0.6
-    det = gl_experimental.create_detector(f"Test {datetime.utcnow()}", "is this a cat")
+    det = gl_experimental.create_detector(generate_test_detector_name(), "is this a cat")
     gl_experimental.reset_detector(det.id)
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", human_review="NEVER")
     assert iq.result.confidence < low_confidence_threshold
diff --git a/test/unit/test_experimental.py b/test/unit/test_experimental.py
index 2b8f55f7..bcb67a56 100644
--- a/test/unit/test_experimental.py
+++ b/test/unit/test_experimental.py
@@ -1,7 +1,7 @@
 import time
-from datetime import datetime, timezone
 
 import pytest
+from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from model import Detector, ImageQuery
 
@@ -10,7 +10,7 @@ def test_detector_groups(gl_experimental: ExperimentalApi):
     """
     verify that we can create a detector group and retrieve it
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_detector_name()
     created_group = gl_experimental.create_detector_group(name)
     all_groups = gl_experimental.list_detector_groups()
     assert created_group in all_groups
@@ -34,7 +34,7 @@ def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detect
     """
     verify that we can update the name of a detector
     """
-    new_name = f"Test {datetime.utcnow()}"
+    new_name = generate_test_detector_name()
     gl_experimental.update_detector_name(detector.id, new_name)
     updated_detector = gl_experimental.get_detector(detector.id)
     assert updated_detector.name == new_name
@@ -44,7 +44,7 @@ def test_update_detector_status(gl_experimental: ExperimentalApi):
     """
     verify that we can update the status of a detector
     """
-    detector = gl_experimental.get_or_create_detector(f"test {datetime.utcnow()}", "Is there a dog?")
+    detector = gl_experimental.get_or_create_detector(generate_test_detector_name(), "Is there a dog?")
     gl_experimental.update_detector_status(detector.id, False)
     updated_detector = gl_experimental.get_detector(detector.id)
     assert updated_detector.status.value == "OFF"
@@ -57,7 +57,7 @@ def test_update_detector_escalation_type(gl_experimental: ExperimentalApi):
     """
     verify that we can update the escalation type of a detector
     """
-    detector = gl_experimental.get_or_create_detector(f"test {datetime.utcnow()}", "Is there a dog?")
+    detector = gl_experimental.get_or_create_detector(generate_test_detector_name(), "Is there a dog?")
     gl_experimental.update_detector_escalation_type(detector.id, "NO_HUMAN_LABELING")
     updated_detector = gl_experimental.get_detector(detector.id)
     updated_detector.escalation_type == "NO_HUMAN_LABELING"
@@ -94,7 +94,7 @@ def test_text_recognition_detector(gl_experimental: ExperimentalApi):
     """
     verify that we can create and submit to a text recognition detector
     """
-    name = f"Test {datetime.utcnow()}"
+    name = generate_test_detector_name()
     created_detector = gl_experimental.create_text_recognition_detector(
         name, "What is the date and time?", confidence_threshold=0.0
     )
@@ -107,7 +107,7 @@ def test_bounding_box_detector(gl_experimental: ExperimentalApi):
     """
     Verify that we can create and submit to a bounding box detector
     """
-    name = f"Test {datetime.now(timezone.utc)}"
+    name = generate_test_detector_name()
     created_detector = gl_experimental.create_bounding_box_detector(
         name, "Draw a bounding box around each dog in the image", "dog", confidence_threshold=0.0
     )
@@ -121,7 +121,7 @@ def test_bounding_box_detector_async(gl_experimental: ExperimentalApi):
     """
     Verify that we can create and submit to a bounding box detector with ask_async
     """
-    name = f"Test {datetime.now(timezone.utc)}"
+    name = generate_test_detector_name()
     created_detector = gl_experimental.create_bounding_box_detector(
         name, "Draw a bounding box around each dog in the image", "dog", confidence_threshold=0.0
     )
diff --git a/test/unit/test_http_retries.py b/test/unit/test_http_retries.py
index 106c871f..e60f12c2 100644
--- a/test/unit/test_http_retries.py
+++ b/test/unit/test_http_retries.py
@@ -1,16 +1,15 @@
-from datetime import datetime
 from typing import Any, Callable
 from unittest import mock
-from uuid import uuid4
 
 import pytest
+from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.binary_labels import Label
 from groundlight.internalapi import InternalApiError
 from model import Detector
 
 DEFAULT_CONFIDENCE_THRESHOLD = 0.9
-DETECTOR_NAME = f"test detector_{datetime.utcnow().strftime('%Y=%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
+DETECTOR_NAME = generate_test_detector_name()
 TOTAL_RETRIES = 3
 STATUS_CODES = range(500, 505)
 IMAGE_FILE = "test/assets/dog.jpeg"

From 4b1ac5f532afcd7eb6aff6db1a4828c84b11b3c4 Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 21:43:55 +0000
Subject: [PATCH 3/9] trying a fixture-based approach

---
 test/conftest.py                              | 14 +++++---
 test/integration/test_groundlight.py          | 35 +++++++++----------
 .../integration/test_groundlight_expensive.py |  8 ++---
 test/unit/test_cli.py                         |  5 ++-
 test/unit/test_detector_reset.py              |  6 ++--
 test/unit/test_experimental.py                | 16 ++++-----
 test/unit/test_http_retries.py                | 27 +++++++-------
 7 files changed, 59 insertions(+), 52 deletions(-)

diff --git a/test/conftest.py b/test/conftest.py
index 0bfe06e0..c36287ce 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -6,11 +6,17 @@
 from model import Detector, ImageQuery, ImageQueryTypeEnum, ResultTypeEnum
 
 
-def generate_test_detector_name(prefix: str = "Test") -> str:
-    """Generates a unique detector name with a timestamp and random suffix to avoid collisions in parallel CI."""
+def _generate_test_detector_name(prefix: str = "Test") -> str:
+    """Generates a detector name with a timestamp and random suffix to ensure uniqueness."""
     return f"{prefix} {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
 
 
+@pytest.fixture(name="generate_test_detector_name")
+def fixture_test_detector_name():
+    """Fixture that provides a callable to generate unique detector names."""
+    return _generate_test_detector_name
+
+
 def pytest_configure(config):  # pylint: disable=unused-argument
     # Run environment check before tests
     gl = Groundlight()
@@ -33,7 +39,7 @@ def fixture_detector(gl: Groundlight) -> Detector:
     """Creates a new Test detector."""
     query = "Is there a dog?"
     pipeline_config = "never-review"
-    return gl.create_detector(name=generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
+    return gl.create_detector(name=_generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
 
 
 @pytest.fixture(name="count_detector")
@@ -42,7 +48,7 @@ def fixture_count_detector(gl_experimental: ExperimentalApi) -> Detector:
     query = "How many dogs?"
     pipeline_config = "never-review-multi"  # always predicts 0
     return gl_experimental.create_counting_detector(
-        name=generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
+        name=_generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
     )
 
 
diff --git a/test/integration/test_groundlight.py b/test/integration/test_groundlight.py
index 4cbd7f7d..ad88f9ad 100644
--- a/test/integration/test_groundlight.py
+++ b/test/integration/test_groundlight.py
@@ -5,10 +5,9 @@
 import random
 import string
 import time
-from typing import Any, Dict, Optional, Union
+from typing import Any, Callable, Dict, Optional, Union
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.binary_labels import VALID_DISPLAY_LABELS, Label, convert_internal_label_to_display
 from groundlight.internalapi import ApiException, InternalApiError, NotFoundError
@@ -96,7 +95,7 @@ def test_create_groundlight_with_retries():
     assert gl.api_client.configuration.retries.total == retries.total
 
 
-def test_create_detector(gl: Groundlight):
+def test_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     _detector = gl.create_detector(name=name, query=query)
@@ -117,7 +116,7 @@ def test_create_detector(gl: Groundlight):
     assert str(multiclass_detector)
 
 
-def test_create_detector_with_pipeline_config(gl: Groundlight):
+def test_create_detector_with_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
     name = generate_test_detector_name("Test never-review")
@@ -128,7 +127,7 @@ def test_create_detector_with_pipeline_config(gl: Groundlight):
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
+def test_create_detector_with_edge_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name("Test edge-pipeline-config")
     query = "Is there a dog (edge-config)?"
     _detector = gl.create_detector(
@@ -141,7 +140,7 @@ def test_create_detector_with_edge_pipeline_config(gl: Groundlight):
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_confidence_threshold(gl: Groundlight):
+def test_create_detector_with_confidence_threshold(gl: Groundlight, generate_test_detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
     name = generate_test_detector_name("Test with confidence")
@@ -197,7 +196,7 @@ def test_create_detector_with_confidence_threshold(gl: Groundlight):
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_everything(gl: Groundlight):
+def test_create_detector_with_everything(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     group_name = "Test group"
@@ -232,7 +231,7 @@ def test_list_detectors(gl: Groundlight):
     assert isinstance(detectors, PaginatedDetectorList)
 
 
-def test_get_or_create_detector(gl: Groundlight):
+def test_get_or_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
     # With a unique name, we should be creating a new detector.
     unique_name = generate_test_detector_name()
     query = "Is there a dog?"
@@ -410,7 +409,7 @@ def test_submit_image_query_with_low_request_timeout(gl: Groundlight, detector:
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_metadata(gl: Groundlight):
+def test_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
@@ -422,7 +421,7 @@ def test_create_detector_with_metadata(gl: Groundlight):
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_get_or_create_detector_with_metadata(gl: Groundlight):
+def test_get_or_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
     unique_name = generate_test_detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
@@ -443,7 +442,7 @@ def test_get_or_create_detector_with_metadata(gl: Groundlight):
         [""],
     ],
 )
-def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any):
+def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any, generate_test_detector_name: Callable):
     name = generate_test_detector_name()
     query = "Is there a dog?"
 
@@ -627,7 +626,7 @@ def test_list_image_queries(gl: Groundlight):
             assert is_valid_display_result(image_query.result)
 
 
-def test_list_image_queries_with_filter(gl: Groundlight):
+def test_list_image_queries_with_filter(gl: Groundlight, generate_test_detector_name: Callable):
     # We want a fresh detector so we know exactly what image queries are associated with it
     detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     image_query_yes = gl.ask_async(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
@@ -855,7 +854,7 @@ def test_submit_image_query_with_empty_inspection_id(gl: Groundlight, detector:
     )
 
 
-def test_binary_detector(gl: Groundlight):
+def test_binary_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a binary detector
     """
@@ -866,7 +865,7 @@ def test_binary_detector(gl: Groundlight):
     assert binary_iq.result.label is not None
 
 
-def test_counting_detector(gl: Groundlight):
+def test_counting_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
@@ -877,7 +876,7 @@ def test_counting_detector(gl: Groundlight):
     assert count_iq.result.count is not None
 
 
-def test_counting_detector_async(gl: Groundlight):
+def test_counting_detector_async(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
@@ -896,7 +895,7 @@ def test_counting_detector_async(gl: Groundlight):
     assert _image_query.result is not None
 
 
-def test_multiclass_detector(gl: Groundlight):
+def test_multiclass_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a multi-class detector
     """
@@ -911,7 +910,7 @@ def test_multiclass_detector(gl: Groundlight):
     assert mc_iq.result.label in class_names
 
 
-def test_delete_detector(gl: Groundlight):
+def test_delete_detector(gl: Groundlight, generate_test_detector_name: Callable):
     """
     Test deleting a detector by both ID and object, and verify proper error handling.
     """
@@ -952,7 +951,7 @@ def test_delete_detector(gl: Groundlight):
         gl.delete_detector(fake_detector_id)  # type: ignore
 
 
-def test_create_detector_with_invalid_priming_group_id(gl: Groundlight):
+def test_create_detector_with_invalid_priming_group_id(gl: Groundlight, generate_test_detector_name: Callable):
     """
     Test that creating a detector with a non-existent priming_group_id returns an appropriate error.
 
diff --git a/test/integration/test_groundlight_expensive.py b/test/integration/test_groundlight_expensive.py
index 1693c8a3..bd25450c 100644
--- a/test/integration/test_groundlight_expensive.py
+++ b/test/integration/test_groundlight_expensive.py
@@ -7,9 +7,9 @@
 # pylint: disable=wildcard-import,unused-wildcard-import,redefined-outer-name,import-outside-toplevel
 import random
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.internalapi import iq_is_answered, iq_is_confident
 from groundlight.optional_imports import *
@@ -30,7 +30,7 @@ def fixture_gl() -> Groundlight:
 
 
 @pytest.mark.skip(reason="This test requires a human labeler who does not need to be in the testing loop")
-def test_human_label(gl: Groundlight):
+def test_human_label(gl: Groundlight, generate_test_detector_name: Callable):
     detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
     img_query = gl.submit_image_query(
         detector=detector.id, image="test/assets/dog.jpeg", wait=60, human_review="ALWAYS"
@@ -52,7 +52,7 @@ def test_human_label(gl: Groundlight):
 
 @pytest.mark.skip(reason="This test can block development depending on the state of the service")
 @pytest.mark.skipif(MISSING_PIL, reason="Needs pillow")  # type: ignore
-def test_detector_improvement(gl: Groundlight):
+def test_detector_improvement(gl: Groundlight, generate_test_detector_name: Callable):
     # test that we get confidence improvement after sending images in
     # Pass two of each type of image in
     import time
@@ -122,7 +122,7 @@ def submit_noisy_image(image, label=None):
 @pytest.mark.skip(
     reason="We don't yet have an SLA level to test ask_confident against, and the test is flakey as a result"
 )
-def test_ask_method_quality(gl: Groundlight, detector: Detector):
+def test_ask_method_quality(gl: Groundlight, detector: Detector, generate_test_detector_name: Callable):
     # asks for some level of quality on how fast ask_ml is and that we will get a confident result from ask_confident
     fast_always_yes_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert iq_is_answered(fast_always_yes_iq)
diff --git a/test/unit/test_cli.py b/test/unit/test_cli.py
index 90c368f7..b9335dc1 100644
--- a/test/unit/test_cli.py
+++ b/test/unit/test_cli.py
@@ -1,10 +1,9 @@
 import os
 import re
 import subprocess
+from typing import Callable
 from unittest.mock import patch
 
-from conftest import generate_test_detector_name
-
 
 def test_whoami():
     completed_process = subprocess.run(
@@ -24,7 +23,7 @@ def test_list_detector():
     assert completed_process.returncode == 0
 
 
-def test_detector_and_image_queries():
+def test_detector_and_image_queries(generate_test_detector_name: Callable):
     # test creating a detector
     test_detector_name = generate_test_detector_name("testdetector")
     completed_process = subprocess.run(
diff --git a/test/unit/test_detector_reset.py b/test/unit/test_detector_reset.py
index 3be962ce..bf41fe5f 100644
--- a/test/unit/test_detector_reset.py
+++ b/test/unit/test_detector_reset.py
@@ -1,13 +1,13 @@
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from groundlight_openapi_client.exceptions import NotFoundException
 
 
 @pytest.mark.skip(reason="This is an expensive test, reset may take some time")
-def test_reset_retry(gl_experimental: ExperimentalApi):
+def test_reset_retry(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     # Reset the detector, retrying in case the reset is still ongoing
     det = gl_experimental.create_detector(generate_test_detector_name(), "test_query")
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
@@ -27,7 +27,7 @@ def test_reset_retry(gl_experimental: ExperimentalApi):
 
 
 @pytest.mark.skip(reason="This test does not work with strong 0 shot models, enabled by default based on your account")
-def test_reset_training(gl_experimental: ExperimentalApi):
+def test_reset_training(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     # If we reset a detector, we should have low confidence after the reset
     low_confidence_threshold = 0.6
     det = gl_experimental.create_detector(generate_test_detector_name(), "is this a cat")
diff --git a/test/unit/test_experimental.py b/test/unit/test_experimental.py
index bcb67a56..c78b74cc 100644
--- a/test/unit/test_experimental.py
+++ b/test/unit/test_experimental.py
@@ -1,12 +1,12 @@
 import time
+from typing import Callable
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import ExperimentalApi
 from model import Detector, ImageQuery
 
 
-def test_detector_groups(gl_experimental: ExperimentalApi):
+def test_detector_groups(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can create a detector group and retrieve it
     """
@@ -30,7 +30,7 @@ def test_update_detector_confidence_threshold(gl_experimental: ExperimentalApi,
     assert updated_detector.confidence_threshold == newer_confidence
 
 
-def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector):
+def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector, generate_test_detector_name: Callable):
     """
     verify that we can update the name of a detector
     """
@@ -40,7 +40,7 @@ def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detect
     assert updated_detector.name == new_name
 
 
-def test_update_detector_status(gl_experimental: ExperimentalApi):
+def test_update_detector_status(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can update the status of a detector
     """
@@ -53,7 +53,7 @@ def test_update_detector_status(gl_experimental: ExperimentalApi):
     assert updated_detector.status.value == "ON"
 
 
-def test_update_detector_escalation_type(gl_experimental: ExperimentalApi):
+def test_update_detector_escalation_type(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can update the escalation type of a detector
     """
@@ -90,7 +90,7 @@ def test_submit_multiple_rois(gl_experimental: ExperimentalApi, image_query_one:
     gl_experimental.add_label(image_query_one, 3, [roi] * 3)
 
 
-def test_text_recognition_detector(gl_experimental: ExperimentalApi):
+def test_text_recognition_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     verify that we can create and submit to a text recognition detector
     """
@@ -103,7 +103,7 @@ def test_text_recognition_detector(gl_experimental: ExperimentalApi):
     assert mc_iq.result.text is not None
 
 
-def test_bounding_box_detector(gl_experimental: ExperimentalApi):
+def test_bounding_box_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector
     """
@@ -117,7 +117,7 @@ def test_bounding_box_detector(gl_experimental: ExperimentalApi):
     assert bbox_iq.rois is not None
 
 
-def test_bounding_box_detector_async(gl_experimental: ExperimentalApi):
+def test_bounding_box_detector_async(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector with ask_async
     """
diff --git a/test/unit/test_http_retries.py b/test/unit/test_http_retries.py
index e60f12c2..694c20e7 100644
--- a/test/unit/test_http_retries.py
+++ b/test/unit/test_http_retries.py
@@ -2,14 +2,12 @@
 from unittest import mock
 
 import pytest
-from conftest import generate_test_detector_name
 from groundlight import Groundlight
 from groundlight.binary_labels import Label
 from groundlight.internalapi import InternalApiError
 from model import Detector
 
 DEFAULT_CONFIDENCE_THRESHOLD = 0.9
-DETECTOR_NAME = generate_test_detector_name()
 TOTAL_RETRIES = 3
 STATUS_CODES = range(500, 505)
 IMAGE_FILE = "test/assets/dog.jpeg"
@@ -22,30 +20,35 @@ def groundlight_fixture() -> Groundlight:
     return gl
 
 
+@pytest.fixture(name="detector_name")
+def detector_name_fixture(generate_test_detector_name) -> str:
+    return generate_test_detector_name("test detector")
+
+
 @pytest.fixture(name="detector")
-def detector_fixture(gl: Groundlight) -> Detector:
+def detector_fixture(gl: Groundlight, detector_name: str) -> Detector:
     return gl.get_or_create_detector(
-        name=DETECTOR_NAME, query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
+        name=detector_name, query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
     )
 
 
-def test_create_detector_attempts_retries(gl: Groundlight):
+def test_create_detector_attempts_retries(gl: Groundlight, detector_name: str):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=DETECTOR_NAME,
+        name=detector_name,
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
 
 
-def test_get_or_create_detector_attempts_retries(gl: Groundlight):
+def test_get_or_create_detector_attempts_retries(gl: Groundlight, detector_name: str):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_or_create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=DETECTOR_NAME,
+        name=detector_name,
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
@@ -60,12 +63,12 @@ def test_get_detector_attempts_retries(gl: Groundlight, detector: Detector):
     )
 
 
-def test_get_detector_by_name_attempts_retries(gl: Groundlight):
+def test_get_detector_by_name_attempts_retries(gl: Groundlight, detector_name: str):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_detector_by_name,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=DETECTOR_NAME,
+        name=detector_name,
     )
 
 
@@ -75,12 +78,12 @@ def test_list_detectors_attempts_retries(gl: Groundlight):
     )
 
 
-def test_submit_image_query_attempts_retries(gl: Groundlight):
+def test_submit_image_query_attempts_retries(gl: Groundlight, detector_name: str):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.submit_image_query,
         expected_call_counts=TOTAL_RETRIES + 1,
-        detector=DETECTOR_NAME,
+        detector=detector_name,
         image=IMAGE_FILE,
         wait=1,
     )

From a2cae395490af3b118aa8ba2e72a698281ef01b4 Mon Sep 17 00:00:00 2001
From: Auto-format Bot <autoformatbot@groundlight.ai>
Date: Wed, 18 Mar 2026 21:44:34 +0000
Subject: [PATCH 4/9] Automatically reformatting code

---
 test/integration/test_groundlight.py | 4 +++-
 test/unit/test_experimental.py       | 4 +++-
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/test/integration/test_groundlight.py b/test/integration/test_groundlight.py
index ad88f9ad..7d6dd6ee 100644
--- a/test/integration/test_groundlight.py
+++ b/test/integration/test_groundlight.py
@@ -442,7 +442,9 @@ def test_get_or_create_detector_with_metadata(gl: Groundlight, generate_test_det
         [""],
     ],
 )
-def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any, generate_test_detector_name: Callable):
+def test_create_detector_with_invalid_metadata(
+    gl: Groundlight, metadata_list: Any, generate_test_detector_name: Callable
+):
     name = generate_test_detector_name()
     query = "Is there a dog?"
 
diff --git a/test/unit/test_experimental.py b/test/unit/test_experimental.py
index c78b74cc..312c4394 100644
--- a/test/unit/test_experimental.py
+++ b/test/unit/test_experimental.py
@@ -30,7 +30,9 @@ def test_update_detector_confidence_threshold(gl_experimental: ExperimentalApi,
     assert updated_detector.confidence_threshold == newer_confidence
 
 
-def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector, generate_test_detector_name: Callable):
+def test_update_detector_name(
+    gl_experimental: ExperimentalApi, detector: Detector, generate_test_detector_name: Callable
+):
     """
     verify that we can update the name of a detector
     """

From 9781a0a4b891690d2909a9157f1f6e093c4d625f Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 21:53:29 +0000
Subject: [PATCH 5/9] renaming fixture

---
 test/conftest.py                              | 12 ++--
 test/integration/test_groundlight.py          | 70 +++++++++----------
 .../integration/test_groundlight_expensive.py | 12 ++--
 test/unit/test_cli.py                         |  4 +-
 test/unit/test_detector_reset.py              |  8 +--
 test/unit/test_experimental.py                | 28 ++++----
 test/unit/test_http_retries.py                | 26 +++----
 7 files changed, 80 insertions(+), 80 deletions(-)

diff --git a/test/conftest.py b/test/conftest.py
index c36287ce..408b55e6 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -6,15 +6,15 @@
 from model import Detector, ImageQuery, ImageQueryTypeEnum, ResultTypeEnum
 
 
-def _generate_test_detector_name(prefix: str = "Test") -> str:
+def _generate_unique_detector_name(prefix: str = "Test") -> str:
     """Generates a detector name with a timestamp and random suffix to ensure uniqueness."""
     return f"{prefix} {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')}_{uuid4().hex[:8]}"
 
 
-@pytest.fixture(name="generate_test_detector_name")
-def fixture_test_detector_name():
+@pytest.fixture(name="detector_name")
+def fixture_detector_name():
     """Fixture that provides a callable to generate unique detector names."""
-    return _generate_test_detector_name
+    return _generate_unique_detector_name
 
 
 def pytest_configure(config):  # pylint: disable=unused-argument
@@ -39,7 +39,7 @@ def fixture_detector(gl: Groundlight) -> Detector:
     """Creates a new Test detector."""
     query = "Is there a dog?"
     pipeline_config = "never-review"
-    return gl.create_detector(name=_generate_test_detector_name(), query=query, pipeline_config=pipeline_config)
+    return gl.create_detector(name=_generate_unique_detector_name(), query=query, pipeline_config=pipeline_config)
 
 
 @pytest.fixture(name="count_detector")
@@ -48,7 +48,7 @@ def fixture_count_detector(gl_experimental: ExperimentalApi) -> Detector:
     query = "How many dogs?"
     pipeline_config = "never-review-multi"  # always predicts 0
     return gl_experimental.create_counting_detector(
-        name=_generate_test_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
+        name=_generate_unique_detector_name(), query=query, class_name="dog", pipeline_config=pipeline_config
     )
 
 
diff --git a/test/integration/test_groundlight.py b/test/integration/test_groundlight.py
index ad88f9ad..1567f7c5 100644
--- a/test/integration/test_groundlight.py
+++ b/test/integration/test_groundlight.py
@@ -95,8 +95,8 @@ def test_create_groundlight_with_retries():
     assert gl.api_client.configuration.retries.total == retries.total
 
 
-def test_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
-    name = generate_test_detector_name()
+def test_create_detector(gl: Groundlight, detector_name: Callable):
+    name = detector_name()
     query = "Is there a dog?"
     _detector = gl.create_detector(name=name, query=query)
     assert str(_detector)
@@ -107,19 +107,19 @@ def test_create_detector(gl: Groundlight, generate_test_detector_name: Callable)
 
     # Test creating dectors with other modes
     count_detector = gl.create_detector(
-        name=generate_test_detector_name(), query=query, mode=ModeEnum.COUNT, class_names="dog"
+        name=detector_name(), query=query, mode=ModeEnum.COUNT, class_names="dog"
     )
     assert str(count_detector)
     multiclass_detector = gl.create_detector(
-        name=generate_test_detector_name(), query=query, mode=ModeEnum.MULTI_CLASS, class_names=["dog", "cat"]
+        name=detector_name(), query=query, mode=ModeEnum.MULTI_CLASS, class_names=["dog", "cat"]
     )
     assert str(multiclass_detector)
 
 
-def test_create_detector_with_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
+def test_create_detector_with_pipeline_config(gl: Groundlight, detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
-    name = generate_test_detector_name("Test never-review")
+    name = detector_name("Test never-review")
     query = "Is there a dog (always-pass)?"
     pipeline_config = "never-review"
     _detector = gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
@@ -127,8 +127,8 @@ def test_create_detector_with_pipeline_config(gl: Groundlight, generate_test_det
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_edge_pipeline_config(gl: Groundlight, generate_test_detector_name: Callable):
-    name = generate_test_detector_name("Test edge-pipeline-config")
+def test_create_detector_with_edge_pipeline_config(gl: Groundlight, detector_name: Callable):
+    name = detector_name("Test edge-pipeline-config")
     query = "Is there a dog (edge-config)?"
     _detector = gl.create_detector(
         name=name,
@@ -140,10 +140,10 @@ def test_create_detector_with_edge_pipeline_config(gl: Groundlight, generate_tes
     assert isinstance(_detector, Detector)
 
 
-def test_create_detector_with_confidence_threshold(gl: Groundlight, generate_test_detector_name: Callable):
+def test_create_detector_with_confidence_threshold(gl: Groundlight, detector_name: Callable):
     # "never-review" is a special model that always returns the same result with 100% confidence.
     # It's useful for testing.
-    name = generate_test_detector_name("Test with confidence")
+    name = detector_name("Test with confidence")
     query = "Is there a dog in the image?"
     pipeline_config = "never-review"
     confidence_threshold = 0.825
@@ -196,8 +196,8 @@ def test_create_detector_with_confidence_threshold(gl: Groundlight, generate_tes
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_everything(gl: Groundlight, generate_test_detector_name: Callable):
-    name = generate_test_detector_name()
+def test_create_detector_with_everything(gl: Groundlight, detector_name: Callable):
+    name = detector_name()
     query = "Is there a dog?"
     group_name = "Test group"
     confidence_threshold = 0.825
@@ -231,9 +231,9 @@ def test_list_detectors(gl: Groundlight):
     assert isinstance(detectors, PaginatedDetectorList)
 
 
-def test_get_or_create_detector(gl: Groundlight, generate_test_detector_name: Callable):
+def test_get_or_create_detector(gl: Groundlight, detector_name: Callable):
     # With a unique name, we should be creating a new detector.
-    unique_name = generate_test_detector_name()
+    unique_name = detector_name()
     query = "Is there a dog?"
     detector = gl.get_or_create_detector(name=unique_name, query=query)
     assert str(detector)
@@ -409,8 +409,8 @@ def test_submit_image_query_with_low_request_timeout(gl: Groundlight, detector:
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
-    name = generate_test_detector_name()
+def test_create_detector_with_metadata(gl: Groundlight, detector_name: Callable):
+    name = detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
     detector = gl.create_detector(name=name, query=query, metadata=metadata)
@@ -421,8 +421,8 @@ def test_create_detector_with_metadata(gl: Groundlight, generate_test_detector_n
 
 
 @pytest.mark.skip_for_edge_endpoint(reason="The edge-endpoint does not support passing detector metadata.")
-def test_get_or_create_detector_with_metadata(gl: Groundlight, generate_test_detector_name: Callable):
-    unique_name = generate_test_detector_name()
+def test_get_or_create_detector_with_metadata(gl: Groundlight, detector_name: Callable):
+    unique_name = detector_name()
     query = "Is there a dog?"
     metadata = generate_random_dict(target_size_bytes=200)
     detector = gl.get_or_create_detector(name=unique_name, query=query, metadata=metadata)
@@ -442,8 +442,8 @@ def test_get_or_create_detector_with_metadata(gl: Groundlight, generate_test_det
         [""],
     ],
 )
-def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any, generate_test_detector_name: Callable):
-    name = generate_test_detector_name()
+def test_create_detector_with_invalid_metadata(gl: Groundlight, metadata_list: Any, detector_name: Callable):
+    name = detector_name()
     query = "Is there a dog?"
 
     for metadata in metadata_list:
@@ -626,9 +626,9 @@ def test_list_image_queries(gl: Groundlight):
             assert is_valid_display_result(image_query.result)
 
 
-def test_list_image_queries_with_filter(gl: Groundlight, generate_test_detector_name: Callable):
+def test_list_image_queries_with_filter(gl: Groundlight, detector_name: Callable):
     # We want a fresh detector so we know exactly what image queries are associated with it
-    detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
+    detector = gl.create_detector(name=detector_name(), query="Is there a dog?")
     image_query_yes = gl.ask_async(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
     image_query_no = gl.ask_async(detector=detector.id, image="test/assets/cat.jpeg", human_review="NEVER")
     iq_ids = [image_query_yes.id, image_query_no.id]
@@ -854,33 +854,33 @@ def test_submit_image_query_with_empty_inspection_id(gl: Groundlight, detector:
     )
 
 
-def test_binary_detector(gl: Groundlight, generate_test_detector_name: Callable):
+def test_binary_detector(gl: Groundlight, detector_name: Callable):
     """
     verify that we can create and submit to a binary detector
     """
-    name = generate_test_detector_name()
+    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")
     assert binary_iq.result.label is not None
 
 
-def test_counting_detector(gl: Groundlight, generate_test_detector_name: Callable):
+def test_counting_detector(gl: Groundlight, detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
-    name = generate_test_detector_name()
+    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")
     assert count_iq.result.count is not None
 
 
-def test_counting_detector_async(gl: Groundlight, generate_test_detector_name: Callable):
+def test_counting_detector_async(gl: Groundlight, detector_name: Callable):
     """
     verify that we can create and submit to a counting detector
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     created_detector = gl.create_counting_detector(name, "How many dogs", "dog", confidence_threshold=0.0)
     assert created_detector is not None
     async_iq = gl.ask_async(created_detector, "test/assets/dog.jpeg")
@@ -895,11 +895,11 @@ def test_counting_detector_async(gl: Groundlight, generate_test_detector_name: C
     assert _image_query.result is not None
 
 
-def test_multiclass_detector(gl: Groundlight, generate_test_detector_name: Callable):
+def test_multiclass_detector(gl: Groundlight, detector_name: Callable):
     """
     verify that we can create and submit to a multi-class detector
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     class_names = ["Golden Retriever", "Labrador Retriever", "Poodle"]
     created_detector = gl.create_multiclass_detector(
         name, "What kind of dog is this?", class_names=class_names, confidence_threshold=0.0
@@ -910,12 +910,12 @@ def test_multiclass_detector(gl: Groundlight, generate_test_detector_name: Calla
     assert mc_iq.result.label in class_names
 
 
-def test_delete_detector(gl: Groundlight, generate_test_detector_name: Callable):
+def test_delete_detector(gl: Groundlight, detector_name: Callable):
     """
     Test deleting a detector by both ID and object, and verify proper error handling.
     """
     # Create a detector to delete
-    name = generate_test_detector_name("Test delete detector")
+    name = detector_name("Test delete detector")
     query = "Is there a dog to delete?"
     pipeline_config = "never-review"
     detector = gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
@@ -928,7 +928,7 @@ def test_delete_detector(gl: Groundlight, generate_test_detector_name: Callable)
         gl.get_detector(detector.id)
 
     # Create another detector to test deletion by ID string and that an attached image query is deleted
-    name2 = generate_test_detector_name("Test delete detector 2")
+    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")
 
@@ -951,14 +951,14 @@ def test_delete_detector(gl: Groundlight, generate_test_detector_name: Callable)
         gl.delete_detector(fake_detector_id)  # type: ignore
 
 
-def test_create_detector_with_invalid_priming_group_id(gl: Groundlight, generate_test_detector_name: Callable):
+def test_create_detector_with_invalid_priming_group_id(gl: Groundlight, detector_name: Callable):
     """
     Test that creating a detector with a non-existent priming_group_id returns an appropriate error.
 
     Note: PrimingGroup IDs are provided by Groundlight representatives. If you would like to
     use a priming_group_id, please reach out to your Groundlight representative.
     """
-    name = generate_test_detector_name("Test invalid priming")
+    name = detector_name("Test invalid priming")
     query = "Is there a dog?"
     pipeline_config = "never-review"
     priming_group_id = "prgrp_nonexistent12345678901234567890"
diff --git a/test/integration/test_groundlight_expensive.py b/test/integration/test_groundlight_expensive.py
index bd25450c..27529ac2 100644
--- a/test/integration/test_groundlight_expensive.py
+++ b/test/integration/test_groundlight_expensive.py
@@ -30,8 +30,8 @@ def fixture_gl() -> Groundlight:
 
 
 @pytest.mark.skip(reason="This test requires a human labeler who does not need to be in the testing loop")
-def test_human_label(gl: Groundlight, generate_test_detector_name: Callable):
-    detector = gl.create_detector(name=generate_test_detector_name(), query="Is there a dog?")
+def test_human_label(gl: Groundlight, detector_name: Callable):
+    detector = gl.create_detector(name=detector_name(), query="Is there a dog?")
     img_query = gl.submit_image_query(
         detector=detector.id, image="test/assets/dog.jpeg", wait=60, human_review="ALWAYS"
     )
@@ -52,7 +52,7 @@ def test_human_label(gl: Groundlight, generate_test_detector_name: Callable):
 
 @pytest.mark.skip(reason="This test can block development depending on the state of the service")
 @pytest.mark.skipif(MISSING_PIL, reason="Needs pillow")  # type: ignore
-def test_detector_improvement(gl: Groundlight, generate_test_detector_name: Callable):
+def test_detector_improvement(gl: Groundlight, detector_name: Callable):
     # test that we get confidence improvement after sending images in
     # Pass two of each type of image in
     import time
@@ -61,7 +61,7 @@ def test_detector_improvement(gl: Groundlight, generate_test_detector_name: Call
 
     random.seed(2741)
 
-    name = generate_test_detector_name("Test test_detector_improvement")
+    name = detector_name("Test test_detector_improvement")
     query = "Is there a dog?"
     detector = gl.create_detector(name=name, query=query)
 
@@ -122,11 +122,11 @@ def submit_noisy_image(image, label=None):
 @pytest.mark.skip(
     reason="We don't yet have an SLA level to test ask_confident against, and the test is flakey as a result"
 )
-def test_ask_method_quality(gl: Groundlight, detector: Detector, generate_test_detector_name: Callable):
+def test_ask_method_quality(gl: Groundlight, detector: Detector, detector_name: Callable):
     # asks for some level of quality on how fast ask_ml is and that we will get a confident result from ask_confident
     fast_always_yes_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
     assert iq_is_answered(fast_always_yes_iq)
-    name = generate_test_detector_name()
+    name = detector_name()
     query = "Is there a dog?"
     detector = gl.create_detector(name=name, query=query, confidence_threshold=0.8)
     fast_iq = gl.ask_ml(detector=detector.id, image="test/assets/dog.jpeg", wait=0)
diff --git a/test/unit/test_cli.py b/test/unit/test_cli.py
index b9335dc1..609fd8d6 100644
--- a/test/unit/test_cli.py
+++ b/test/unit/test_cli.py
@@ -23,9 +23,9 @@ def test_list_detector():
     assert completed_process.returncode == 0
 
 
-def test_detector_and_image_queries(generate_test_detector_name: Callable):
+def test_detector_and_image_queries(detector_name: Callable):
     # test creating a detector
-    test_detector_name = generate_test_detector_name("testdetector")
+    test_detector_name = detector_name("testdetector")
     completed_process = subprocess.run(
         [
             "groundlight",
diff --git a/test/unit/test_detector_reset.py b/test/unit/test_detector_reset.py
index bf41fe5f..ccead3b7 100644
--- a/test/unit/test_detector_reset.py
+++ b/test/unit/test_detector_reset.py
@@ -7,9 +7,9 @@
 
 
 @pytest.mark.skip(reason="This is an expensive test, reset may take some time")
-def test_reset_retry(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_reset_retry(gl_experimental: ExperimentalApi, detector_name: Callable):
     # Reset the detector, retrying in case the reset is still ongoing
-    det = gl_experimental.create_detector(generate_test_detector_name(), "test_query")
+    det = gl_experimental.create_detector(detector_name(), "test_query")
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
     gl_experimental.reset_detector(det.id)
     success = False
@@ -27,10 +27,10 @@ def test_reset_retry(gl_experimental: ExperimentalApi, generate_test_detector_na
 
 
 @pytest.mark.skip(reason="This test does not work with strong 0 shot models, enabled by default based on your account")
-def test_reset_training(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_reset_training(gl_experimental: ExperimentalApi, detector_name: Callable):
     # If we reset a detector, we should have low confidence after the reset
     low_confidence_threshold = 0.6
-    det = gl_experimental.create_detector(generate_test_detector_name(), "is this a cat")
+    det = gl_experimental.create_detector(detector_name(), "is this a cat")
     gl_experimental.reset_detector(det.id)
     iq = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg", human_review="NEVER")
     assert iq.result.confidence < low_confidence_threshold
diff --git a/test/unit/test_experimental.py b/test/unit/test_experimental.py
index c78b74cc..9c2237e5 100644
--- a/test/unit/test_experimental.py
+++ b/test/unit/test_experimental.py
@@ -6,11 +6,11 @@
 from model import Detector, ImageQuery
 
 
-def test_detector_groups(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_detector_groups(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     verify that we can create a detector group and retrieve it
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     created_group = gl_experimental.create_detector_group(name)
     all_groups = gl_experimental.list_detector_groups()
     assert created_group in all_groups
@@ -30,21 +30,21 @@ def test_update_detector_confidence_threshold(gl_experimental: ExperimentalApi,
     assert updated_detector.confidence_threshold == newer_confidence
 
 
-def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector, generate_test_detector_name: Callable):
+def test_update_detector_name(gl_experimental: ExperimentalApi, detector: Detector, detector_name: Callable):
     """
     verify that we can update the name of a detector
     """
-    new_name = generate_test_detector_name()
+    new_name = detector_name()
     gl_experimental.update_detector_name(detector.id, new_name)
     updated_detector = gl_experimental.get_detector(detector.id)
     assert updated_detector.name == new_name
 
 
-def test_update_detector_status(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_update_detector_status(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     verify that we can update the status of a detector
     """
-    detector = gl_experimental.get_or_create_detector(generate_test_detector_name(), "Is there a dog?")
+    detector = gl_experimental.get_or_create_detector(detector_name(), "Is there a dog?")
     gl_experimental.update_detector_status(detector.id, False)
     updated_detector = gl_experimental.get_detector(detector.id)
     assert updated_detector.status.value == "OFF"
@@ -53,11 +53,11 @@ def test_update_detector_status(gl_experimental: ExperimentalApi, generate_test_
     assert updated_detector.status.value == "ON"
 
 
-def test_update_detector_escalation_type(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_update_detector_escalation_type(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     verify that we can update the escalation type of a detector
     """
-    detector = gl_experimental.get_or_create_detector(generate_test_detector_name(), "Is there a dog?")
+    detector = gl_experimental.get_or_create_detector(detector_name(), "Is there a dog?")
     gl_experimental.update_detector_escalation_type(detector.id, "NO_HUMAN_LABELING")
     updated_detector = gl_experimental.get_detector(detector.id)
     updated_detector.escalation_type == "NO_HUMAN_LABELING"
@@ -90,11 +90,11 @@ def test_submit_multiple_rois(gl_experimental: ExperimentalApi, image_query_one:
     gl_experimental.add_label(image_query_one, 3, [roi] * 3)
 
 
-def test_text_recognition_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_text_recognition_detector(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     verify that we can create and submit to a text recognition detector
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     created_detector = gl_experimental.create_text_recognition_detector(
         name, "What is the date and time?", confidence_threshold=0.0
     )
@@ -103,11 +103,11 @@ def test_text_recognition_detector(gl_experimental: ExperimentalApi, generate_te
     assert mc_iq.result.text is not None
 
 
-def test_bounding_box_detector(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_bounding_box_detector(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     created_detector = gl_experimental.create_bounding_box_detector(
         name, "Draw a bounding box around each dog in the image", "dog", confidence_threshold=0.0
     )
@@ -117,11 +117,11 @@ def test_bounding_box_detector(gl_experimental: ExperimentalApi, generate_test_d
     assert bbox_iq.rois is not None
 
 
-def test_bounding_box_detector_async(gl_experimental: ExperimentalApi, generate_test_detector_name: Callable):
+def test_bounding_box_detector_async(gl_experimental: ExperimentalApi, detector_name: Callable):
     """
     Verify that we can create and submit to a bounding box detector with ask_async
     """
-    name = generate_test_detector_name()
+    name = detector_name()
     created_detector = gl_experimental.create_bounding_box_detector(
         name, "Draw a bounding box around each dog in the image", "dog", confidence_threshold=0.0
     )
diff --git a/test/unit/test_http_retries.py b/test/unit/test_http_retries.py
index 694c20e7..c838af74 100644
--- a/test/unit/test_http_retries.py
+++ b/test/unit/test_http_retries.py
@@ -20,35 +20,35 @@ def groundlight_fixture() -> Groundlight:
     return gl
 
 
-@pytest.fixture(name="detector_name")
-def detector_name_fixture(generate_test_detector_name) -> str:
-    return generate_test_detector_name("test detector")
+@pytest.fixture(name="retry_detector_name")
+def retry_detector_name_fixture(detector_name) -> str:
+    return detector_name("test detector")
 
 
 @pytest.fixture(name="detector")
-def detector_fixture(gl: Groundlight, detector_name: str) -> Detector:
+def detector_fixture(gl: Groundlight, retry_detector_name: str) -> Detector:
     return gl.get_or_create_detector(
-        name=detector_name, query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
+        name=retry_detector_name, query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
     )
 
 
-def test_create_detector_attempts_retries(gl: Groundlight, detector_name: str):
+def test_create_detector_attempts_retries(gl: Groundlight, retry_detector_name: str):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=detector_name,
+        name=retry_detector_name,
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
 
 
-def test_get_or_create_detector_attempts_retries(gl: Groundlight, detector_name: str):
+def test_get_or_create_detector_attempts_retries(gl: Groundlight, retry_detector_name: str):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_or_create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=detector_name,
+        name=retry_detector_name,
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
@@ -63,12 +63,12 @@ def test_get_detector_attempts_retries(gl: Groundlight, detector: Detector):
     )
 
 
-def test_get_detector_by_name_attempts_retries(gl: Groundlight, detector_name: str):
+def test_get_detector_by_name_attempts_retries(gl: Groundlight, retry_detector_name: str):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_detector_by_name,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=detector_name,
+        name=retry_detector_name,
     )
 
 
@@ -78,12 +78,12 @@ def test_list_detectors_attempts_retries(gl: Groundlight):
     )
 
 
-def test_submit_image_query_attempts_retries(gl: Groundlight, detector_name: str):
+def test_submit_image_query_attempts_retries(gl: Groundlight, retry_detector_name: str):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.submit_image_query,
         expected_call_counts=TOTAL_RETRIES + 1,
-        detector=detector_name,
+        detector=retry_detector_name,
         image=IMAGE_FILE,
         wait=1,
     )

From e60fad9bbdaca351ebcda9cd385d07b00dd66bf4 Mon Sep 17 00:00:00 2001
From: Auto-format Bot <autoformatbot@groundlight.ai>
Date: Wed, 18 Mar 2026 21:55:14 +0000
Subject: [PATCH 6/9] Automatically reformatting code

---
 test/integration/test_groundlight.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/test/integration/test_groundlight.py b/test/integration/test_groundlight.py
index 1567f7c5..6d69bb63 100644
--- a/test/integration/test_groundlight.py
+++ b/test/integration/test_groundlight.py
@@ -106,9 +106,7 @@ def test_create_detector(gl: Groundlight, detector_name: Callable):
     ), "We expected the default confidence threshold to be used."
 
     # Test creating dectors with other modes
-    count_detector = gl.create_detector(
-        name=detector_name(), query=query, mode=ModeEnum.COUNT, class_names="dog"
-    )
+    count_detector = gl.create_detector(name=detector_name(), query=query, mode=ModeEnum.COUNT, class_names="dog")
     assert str(count_detector)
     multiclass_detector = gl.create_detector(
         name=detector_name(), query=query, mode=ModeEnum.MULTI_CLASS, class_names=["dog", "cat"]

From 3c5b58683548ed73affee57422270c04d3e408f4 Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 22:01:20 +0000
Subject: [PATCH 7/9] code cleanup

---
 test/unit/test_http_retries.py | 25 ++++++++++---------------
 1 file changed, 10 insertions(+), 15 deletions(-)

diff --git a/test/unit/test_http_retries.py b/test/unit/test_http_retries.py
index c838af74..04b75393 100644
--- a/test/unit/test_http_retries.py
+++ b/test/unit/test_http_retries.py
@@ -20,35 +20,30 @@ def groundlight_fixture() -> Groundlight:
     return gl
 
 
-@pytest.fixture(name="retry_detector_name")
-def retry_detector_name_fixture(detector_name) -> str:
-    return detector_name("test detector")
-
-
 @pytest.fixture(name="detector")
-def detector_fixture(gl: Groundlight, retry_detector_name: str) -> Detector:
+def detector_fixture(gl: Groundlight, detector_name: Callable) -> Detector:
     return gl.get_or_create_detector(
-        name=retry_detector_name, query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
+        name=detector_name(), query="Is there a dog?", confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD
     )
 
 
-def test_create_detector_attempts_retries(gl: Groundlight, retry_detector_name: str):
+def test_create_detector_attempts_retries(gl: Groundlight, detector_name: Callable):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=retry_detector_name,
+        name=detector_name(),
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
 
 
-def test_get_or_create_detector_attempts_retries(gl: Groundlight, retry_detector_name: str):
+def test_get_or_create_detector_attempts_retries(gl: Groundlight, detector_name: Callable):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_or_create_detector,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=retry_detector_name,
+        name=detector_name(),
         query="Is there a dog?",
         confidence_threshold=DEFAULT_CONFIDENCE_THRESHOLD,
     )
@@ -63,12 +58,12 @@ def test_get_detector_attempts_retries(gl: Groundlight, detector: Detector):
     )
 
 
-def test_get_detector_by_name_attempts_retries(gl: Groundlight, retry_detector_name: str):
+def test_get_detector_by_name_attempts_retries(gl: Groundlight, detector_name: Callable):
     run_test(
         mocked_call="requests.request",
         api_method=gl.get_detector_by_name,
         expected_call_counts=TOTAL_RETRIES + 1,
-        name=retry_detector_name,
+        name=detector_name(),
     )
 
 
@@ -78,12 +73,12 @@ def test_list_detectors_attempts_retries(gl: Groundlight):
     )
 
 
-def test_submit_image_query_attempts_retries(gl: Groundlight, retry_detector_name: str):
+def test_submit_image_query_attempts_retries(gl: Groundlight, detector_name: Callable):
     run_test(
         mocked_call="urllib3.PoolManager.request",
         api_method=gl.submit_image_query,
         expected_call_counts=TOTAL_RETRIES + 1,
-        detector=retry_detector_name,
+        detector=detector_name(),
         image=IMAGE_FILE,
         wait=1,
     )

From bb836e7b7a22a9af2c36c82cf7ea919c5f78087e Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 22:08:02 +0000
Subject: [PATCH 8/9] adding type hint

---
 test/conftest.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/conftest.py b/test/conftest.py
index 408b55e6..a3160457 100644
--- a/test/conftest.py
+++ b/test/conftest.py
@@ -1,4 +1,5 @@
 from datetime import datetime
+from typing import Callable
 from uuid import uuid4
 
 import pytest
@@ -12,7 +13,7 @@ def _generate_unique_detector_name(prefix: str = "Test") -> str:
 
 
 @pytest.fixture(name="detector_name")
-def fixture_detector_name():
+def fixture_detector_name() -> Callable[..., str]:
     """Fixture that provides a callable to generate unique detector names."""
     return _generate_unique_detector_name
 

From 8375191557e7afd8c5594fd85fa4f24fd79102ac Mon Sep 17 00:00:00 2001
From: Tim Huff <timmarkhuff@gmail.com>
Date: Wed, 18 Mar 2026 22:18:34 +0000
Subject: [PATCH 9/9] fixing linter error

---
 test/unit/test_cli.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/test/unit/test_cli.py b/test/unit/test_cli.py
index 609fd8d6..47911b70 100644
--- a/test/unit/test_cli.py
+++ b/test/unit/test_cli.py
@@ -41,7 +41,9 @@ def test_detector_and_image_queries(detector_name: Callable):
         check=False,
     )
     assert completed_process.returncode == 0
-    det_id_on_create = re.search("id='([^']+)'", completed_process.stdout).group(1)
+    match = re.search("id='([^']+)'", completed_process.stdout)
+    assert match is not None
+    det_id_on_create = match.group(1)
     # The output of the create-detector command looks something like:
     # id='det_abc123'
     # type=<DetectorTypeEnum.detector: 'detector'>
@@ -59,7 +61,9 @@ def test_detector_and_image_queries(detector_name: Callable):
         check=False,
     )
     assert completed_process.returncode == 0
-    det_id_on_get = re.search("id='([^']+)'", completed_process.stdout).group(1)
+    match = re.search("id='([^']+)'", completed_process.stdout)
+    assert match is not None
+    det_id_on_get = match.group(1)
     assert det_id_on_create == det_id_on_get
     completed_process = subprocess.run(
         ["groundlight", "get-detector", det_id_on_create],