Changing default confidence threshold for new detectors from 0.9 to 0.75 (#212)

* changing default confidence threshold from 0.9 to 0.75

* removing unneeded file

* bumping version

* bumping version to 0.16.0

---------

Co-authored-by: Tim Huff <tim@groundlight.ai>

Author: timmarkhuff

generated/README.md

@@ -79,7 +79,7 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
         name="name_example",
         query="query_example",
         group_name="group_name_example",
-        confidence_threshold=0.9,
+        confidence_threshold=0.75,
         pipeline_config="pipeline_config_example",
         metadata="metadata_example",
     ) # DetectorCreationInput | 

generated/docs/Detector.md

@@ -11,7 +11,7 @@ Name | Type | Description | Notes
 **name** | **str** | A short, descriptive name for the detector. | 
 **query** | **str** | A question about the image. | [readonly] 
 **group_name** | **str** | Which group should this detector be part of? | [readonly] 
-**confidence_threshold** | **float** | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional]  if omitted the server will use the default value of 0.9
+**confidence_threshold** | **float** | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional]  if omitted the server will use the default value of 0.75
 **metadata** | **{str: (bool, date, datetime, dict, float, int, list, str, none_type)}, none_type** | A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string. | [optional] 
 **any string name** | **bool, date, datetime, dict, float, int, list, str, none_type** | any string name can be used but the value must be the correct type | [optional]
 

generated/docs/DetectorCreationInput.md

@@ -8,7 +8,7 @@ Name | Type | Description | Notes
 **name** | **str** | A short, descriptive name for the detector. | 
 **query** | **str** | A question about the image. | 
 **group_name** | **str** | Which group should this detector be part of? | [optional] 
-**confidence_threshold** | **float** | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional]  if omitted the server will use the default value of 0.9
+**confidence_threshold** | **float** | If the detector's prediction is below this confidence threshold, send the image query for human review. | [optional]  if omitted the server will use the default value of 0.75
 **pipeline_config** | **str, none_type** | (Advanced usage) Configuration to instantiate a specific prediction pipeline. | [optional] 
 **metadata** | **str, none_type** | A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string. | [optional] 
 **any string name** | **bool, date, datetime, dict, float, int, list, str, none_type** | any string name can be used but the value must be the correct type | [optional]

generated/docs/DetectorsApi.md

@@ -52,7 +52,7 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
         name="name_example",
         query="query_example",
         group_name="group_name_example",
-        confidence_threshold=0.9,
+        confidence_threshold=0.75,
         pipeline_config="pipeline_config_example",
         metadata="metadata_example",
     ) # DetectorCreationInput | 

generated/groundlight_openapi_client/model/detector.py

@@ -197,7 +197,7 @@ def _from_openapi_data(cls, id, type, created_at, name, query, group_name, *args
                                 Animal class but this time we won't travel
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
-            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
+            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.75  # noqa: E501
             metadata ({str: (bool, date, datetime, dict, float, int, list, str, none_type)}, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string.. [optional]  # noqa: E501
         """
 
@@ -292,7 +292,7 @@ def __init__(self, name, *args, **kwargs):  # noqa: E501
                                 Animal class but this time we won't travel
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
-            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
+            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.75  # noqa: E501
             metadata ({str: (bool, date, datetime, dict, float, int, list, str, none_type)}, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string.. [optional]  # noqa: E501
         """
 

generated/groundlight_openapi_client/model/detector_creation_input.py

@@ -178,7 +178,7 @@ def _from_openapi_data(cls, name, query, *args, **kwargs):  # noqa: E501
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
             group_name (str): Which group should this detector be part of?. [optional]  # noqa: E501
-            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
+            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.75  # noqa: E501
             pipeline_config (str, none_type): (Advanced usage) Configuration to instantiate a specific prediction pipeline.. [optional]  # noqa: E501
             metadata (str, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string.. [optional]  # noqa: E501
         """
@@ -274,7 +274,7 @@ def __init__(self, name, query, *args, **kwargs):  # noqa: E501
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
             group_name (str): Which group should this detector be part of?. [optional]  # noqa: E501
-            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.9  # noqa: E501
+            confidence_threshold (float): If the detector's prediction is below this confidence threshold, send the image query for human review.. [optional] if omitted the server will use the default value of 0.75  # noqa: E501
             pipeline_config (str, none_type): (Advanced usage) Configuration to instantiate a specific prediction pipeline.. [optional]  # noqa: E501
             metadata (str, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded as a URL-safe, base64-encoded JSON string.. [optional]  # noqa: E501
         """

generated/model.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
 #   filename:  public-api.yaml
-#   timestamp: 2024-04-04T00:11:29+00:00
+#   timestamp: 2024-05-28T18:14:08+00:00
 
 from __future__ import annotations
 
@@ -29,7 +29,7 @@ class DetectorCreationInput(BaseModel):
         None, description="Which group should this detector be part of?"
     )
     confidence_threshold: Optional[confloat(ge=0.0, le=1.0)] = Field(
-        0.9,
+        0.75,
         description=(
             "If the detector's prediction is below this confidence threshold, send the image query for human review."
         ),
@@ -111,7 +111,7 @@ class Detector(BaseModel):
     query: str = Field(..., description="A question about the image.")
     group_name: str = Field(..., description="Which group should this detector be part of?")
     confidence_threshold: Optional[confloat(ge=0.0, le=1.0)] = Field(
-        0.9,
+        0.75,
         description=(
             "If the detector's prediction is below this confidence threshold, send the image query for human review."
         ),

pyproject.toml

@@ -9,7 +9,7 @@ packages = [
     {include = "**/*.py", from = "src"},
 ]
 readme = "README.md"
-version = "0.15.2"
+version = "0.16.0"
 
 [tool.poetry.dependencies]
 # For certifi, use ">=" instead of "^" since it upgrades its "major version" every year, not really following semver

spec/public-api.yaml

@@ -465,7 +465,7 @@ components:
           format: double
           maximum: 1.0
           minimum: 0.0
-          default: 0.9
+          default: 0.75
           description:
             If the detector's prediction is below this confidence threshold,
             send the image query for human review.
@@ -504,7 +504,7 @@ components:
           format: double
           maximum: 1.0
           minimum: 0.0
-          default: 0.9
+          default: 0.75
           description:
             If the detector's prediction is below this confidence threshold,
             send the image query for human review.