Revert "require class_name for count mode detectors"

This reverts commit 4ed9694.
groundlight · Dec 7, 2024 · 1bda6d3 · 1bda6d3
1 parent 4ed9694
commit 1bda6d3
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Showing 8 changed files with 453 additions and 503 deletions.
diff --git a/generated/docs/CountModeConfiguration.md b/generated/docs/CountModeConfiguration.md
@@ -4,7 +4,6 @@
 ## Properties
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
-**class_name** | **str** |  | 
 **max_count** | **int** |  | [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]
 

diff --git a/generated/docs/ImageQueriesApi.md b/generated/docs/ImageQueriesApi.md
@@ -282,7 +282,6 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
     # Create an instance of the API class
     api_instance = image_queries_api.ImageQueriesApi(api_client)
     detector_id = "detector_id_example" # str | Choose a detector by its ID.
-    confidence_threshold = 0 # float | The confidence threshold for the image query. (optional)
     human_review = "human_review_example" # str | If set to `DEFAULT`, use the regular escalation logic (i.e., send the image query for human review if the ML model is not confident). If set to `ALWAYS`, always send the image query for human review even if the ML model is confident. If set to `NEVER`, never send the image query for human review even if the ML model is not confident. (optional)
     image_query_id = "image_query_id_example" # str | The ID to assign to the created image query. (optional)
     inspection_id = "inspection_id_example" # str | Associate the image query with an inspection. (optional)
@@ -301,7 +300,7 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
     # example passing only required values which don't have defaults set
     # and optional values
     try:
-        api_response = api_instance.submit_image_query(detector_id, confidence_threshold=confidence_threshold, human_review=human_review, image_query_id=image_query_id, inspection_id=inspection_id, metadata=metadata, patience_time=patience_time, want_async=want_async, body=body)
+        api_response = api_instance.submit_image_query(detector_id, human_review=human_review, image_query_id=image_query_id, inspection_id=inspection_id, metadata=metadata, patience_time=patience_time, want_async=want_async, body=body)
         pprint(api_response)
     except groundlight_openapi_client.ApiException as e:
         print("Exception when calling ImageQueriesApi->submit_image_query: %s\n" % e)
@@ -313,7 +312,6 @@ with groundlight_openapi_client.ApiClient(configuration) as api_client:
 Name | Type | Description  | Notes
 ------------- | ------------- | ------------- | -------------
  **detector_id** | **str**| Choose a detector by its ID. |
- **confidence_threshold** | **float**| The confidence threshold for the image query. | [optional]
  **human_review** | **str**| If set to &#x60;DEFAULT&#x60;, use the regular escalation logic (i.e., send the image query for human review if the ML model is not confident). If set to &#x60;ALWAYS&#x60;, always send the image query for human review even if the ML model is confident. If set to &#x60;NEVER&#x60;, never send the image query for human review even if the ML model is not confident. | [optional]
  **image_query_id** | **str**| The ID to assign to the created image query. | [optional]
  **inspection_id** | **str**| Associate the image query with an inspection. | [optional]

diff --git a/generated/groundlight_openapi_client/api/image_queries_api.py b/generated/groundlight_openapi_client/api/image_queries_api.py
@@ -170,7 +170,6 @@ def __init__(self, api_client=None):
             params_map={
                 "all": [
                     "detector_id",
-                    "confidence_threshold",
                     "human_review",
                     "image_query_id",
                     "inspection_id",
@@ -184,21 +183,13 @@ def __init__(self, api_client=None):
                 ],
                 "nullable": [],
                 "enum": [],
-                "validation": [
-                    "confidence_threshold",
-                ],
+                "validation": [],
             },
             root_map={
-                "validations": {
-                    ("confidence_threshold",): {
-                        "inclusive_maximum": 1,
-                        "inclusive_minimum": 0,
-                    },
-                },
+                "validations": {},
                 "allowed_values": {},
                 "openapi_types": {
                     "detector_id": (str,),
-                    "confidence_threshold": (float,),
                     "human_review": (str,),
                     "image_query_id": (str,),
                     "inspection_id": (str,),
@@ -209,7 +200,6 @@ def __init__(self, api_client=None):
                 },
                 "attribute_map": {
                     "detector_id": "detector_id",
-                    "confidence_threshold": "confidence_threshold",
                     "human_review": "human_review",
                     "image_query_id": "image_query_id",
                     "inspection_id": "inspection_id",
@@ -219,7 +209,6 @@ def __init__(self, api_client=None):
                 },
                 "location_map": {
                     "detector_id": "query",
-                    "confidence_threshold": "query",
                     "human_review": "query",
                     "image_query_id": "query",
                     "inspection_id": "query",
@@ -432,7 +421,6 @@ def submit_image_query(self, detector_id, **kwargs):
             detector_id (str): Choose a detector by its ID.
 
         Keyword Args:
-            confidence_threshold (float): The confidence threshold for the image query.. [optional]
             human_review (str): If set to `DEFAULT`, use the regular escalation logic (i.e., send the image query for human review if the ML model is not confident). If set to `ALWAYS`, always send the image query for human review even if the ML model is confident. If set to `NEVER`, never send the image query for human review even if the ML model is not confident.. [optional]
             image_query_id (str): The ID to assign to the created image query.. [optional]
             inspection_id (str): Associate the image query with an inspection.. [optional]

diff --git a/generated/groundlight_openapi_client/model/count_mode_configuration.py b/generated/groundlight_openapi_client/model/count_mode_configuration.py
@@ -93,7 +93,6 @@ def openapi_types():
                 and the value is attribute type.
         """
         return {
-            "class_name": (str,),  # noqa: E501
             "max_count": (int,),  # noqa: E501
         }
 
@@ -102,7 +101,6 @@ def discriminator():
         return None
 
     attribute_map = {
-        "class_name": "class_name",  # noqa: E501
         "max_count": "max_count",  # noqa: E501
     }
 
@@ -112,12 +110,9 @@ def discriminator():
 
     @classmethod
     @convert_js_args_to_python_args
-    def _from_openapi_data(cls, class_name, *args, **kwargs):  # noqa: E501
+    def _from_openapi_data(cls, *args, **kwargs):  # noqa: E501
         """CountModeConfiguration - a model defined in OpenAPI
 
-        Args:
-            class_name (str):
-
         Keyword Args:
             _check_type (bool): if True, values for parameters in openapi_types
                                 will be type checked and a TypeError will be
@@ -178,7 +173,6 @@ def _from_openapi_data(cls, class_name, *args, **kwargs):  # noqa: E501
         self._configuration = _configuration
         self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
 
-        self.class_name = class_name
         for var_name, var_value in kwargs.items():
             if (
                 var_name not in self.attribute_map
@@ -201,12 +195,9 @@ def _from_openapi_data(cls, class_name, *args, **kwargs):  # noqa: E501
     ])
 
     @convert_js_args_to_python_args
-    def __init__(self, class_name, *args, **kwargs):  # noqa: E501
+    def __init__(self, *args, **kwargs):  # noqa: E501
         """CountModeConfiguration - a model defined in OpenAPI
 
-        Args:
-            class_name (str):
-
         Keyword Args:
             _check_type (bool): if True, values for parameters in openapi_types
                                 will be type checked and a TypeError will be
@@ -265,7 +256,6 @@ def __init__(self, class_name, *args, **kwargs):  # noqa: E501
         self._configuration = _configuration
         self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
 
-        self.class_name = class_name
         for var_name, var_value in kwargs.items():
             if (
                 var_name not in self.attribute_map

diff --git a/generated/groundlight_openapi_client/model/counting_result.py b/generated/groundlight_openapi_client/model/counting_result.py
@@ -64,9 +64,6 @@ class CountingResult(ModelNormal):
     }
 
     validations = {
-        ("count",): {
-            "inclusive_minimum": 0,
-        },
         ("confidence",): {
             "inclusive_maximum": 1.0,
             "inclusive_minimum": 0.0,

diff --git a/generated/model.py b/generated/model.py
@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
 #   filename:  public-api.yaml
-#   timestamp: 2024-12-07T00:51:02+00:00
+#   timestamp: 2024-12-05T21:27:07+00:00
 
 from __future__ import annotations
 
@@ -200,7 +200,7 @@ class BinaryClassificationResult(BaseModel):
 class CountingResult(BaseModel):
     confidence: Optional[confloat(ge=0.0, le=1.0)] = None
     source: Optional[Source] = None
-    count: conint(ge=0)
+    count: int
     greater_than_max: Optional[bool] = None
 
 
@@ -212,7 +212,6 @@ class MultiClassificationResult(BaseModel):
 
 class CountModeConfiguration(BaseModel):
     max_count: Optional[conint(ge=1, le=50)] = None
-    class_name: str
 
 
 class MultiClassModeConfiguration(BaseModel):