Version 0.12.0 (#120)

* bump version

* Update UNSURE to be UNCLEAR, catch __USURE received from the service (#105)

* ask_async (#102)

* initial commit

* added ask_async to submit_image_query

* Automatically reformatting code

* added ask async method

* Automatically reformatting code

* added integration tests (requires BE merge first)

* Automatically reformatting code

* satisfying mypy

* Automatically reformatting code

* fix comments

* change what type of exception test is catching

* Automatically reformatting code

* fix imports organization issue

* fix implementation - wait must be 0 not None

* Automatically reformatting code

* forgot to make wait=0 in relevant test

* feedback from PR review

* Automatically reformatting code

* ensure want_async is a serializable bool

* add description

* updated sphinx reqs to render some of the dependencies

* updated docstring for ask_async and fixed small sphinx bugs in other folk's docstrings

* Tests aren't passing because I didn't update the autogenerated code to expect a new param

* Revert "Tests aren't passing because I didn't update the autogenerated code to expect a new param"

This reverts commit 2477fd5.

* fix generated

* Automatically reformatting code

* fix lint

* Automatically reformatting code

* Revert "Automatically reformatting code"

This reverts commit cb9359e.

* Revert "fix generated"

This reverts commit 935c036.

* Revert "Revert "Tests aren't passing because I didn't update the autogenerated code to expect a new param""

This reverts commit 07670e3.

* Revert "Tests aren't passing because I didn't update the autogenerated code to expect a new param"

This reverts commit 2477fd5.

* Revert "updated docstring for ask_async and fixed small sphinx bugs in other folk's docstrings"

This reverts commit 67e3edd.

* third time at generated docs is the charm

---------

Co-authored-by: Auto-format Bot <[email protected]>

* Cli polishing (#109)

* Add basic catch if api token isn't specified when cli is called

* Pushes Groundlight class instantiation up until the function is actually called with arguments.
This means that the entire help args are available even if we can't instantiate the class (no api key)

* Fixed misunderstanding with metaprogramming, added tests

* Addressing comments

---------

Co-authored-by: Auto-format Bot <[email protected]>

* Add ask_confident and ask_ml (#99)

* Adding ask_confident and ask_fast

* Fixing ask_ml behavior

* Unhide wait functions, merging logic, fixed iq_is_answered logic

* Rewriting doc strings in Sphinx style

* fixed sphinx docstring return types

* Making iq submission with inspection work with newly optional patience time


---------

Co-authored-by: Auto-format Bot <[email protected]>

* Linting

* fix ask_async docstring

---------

Co-authored-by: brandon <[email protected]>
Co-authored-by: Brandon <[email protected]>
Co-authored-by: Auto-format Bot <[email protected]>

Author: 4 people

.vscode/settings.json

@@ -3,6 +3,17 @@
   "editor.codeActionsOnSave": {
     "source.organizeImports": true
   },
-  "python.analysis.extraPaths": ["./generated"],
-  "python.formatting.provider": "black"
-}
+  "editor.rulers": [
+    100,
+    120
+  ],
+  "python.analysis.extraPaths": [
+    "./generated"
+  ],
+  "python.formatting.provider": "black",
+  "[python]": {
+    "editor.codeActionsOnSave": {
+      "source.organizeImports": false
+    }
+  }
+}

generated/docs/ImageQueriesApi.md

@@ -207,6 +207,7 @@ with openapi_client.ApiClient(configuration) as api_client:
     detector_id = "detector_id_example" # str | Choose a detector by its ID.
     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)
     patience_time = 3.14 # float | How long to wait for a confident response. (optional)
+    want_async = "want_async_example" # str | If \"true\" then submitting an image query returns immediately without a result. The result will be computed asynchronously and can be retrieved later. (optional)
     body = open('@path/to/image.jpeg', 'rb') # file_type |  (optional)
 
     # example passing only required values which don't have defaults set
@@ -219,7 +220,7 @@ with 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, human_review=human_review, patience_time=patience_time, body=body)
+        api_response = api_instance.submit_image_query(detector_id, human_review=human_review, patience_time=patience_time, want_async=want_async, body=body)
         pprint(api_response)
     except openapi_client.ApiException as e:
         print("Exception when calling ImageQueriesApi->submit_image_query: %s\n" % e)
@@ -233,6 +234,7 @@ Name | Type | Description  | Notes
  **detector_id** | **str**| Choose a detector by its ID. |
  **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]
  **patience_time** | **float**| How long to wait for a confident response. | [optional]
+ **want_async** | **str**| If \"true\" then submitting an image query returns immediately without a result. The result will be computed asynchronously and can be retrieved later. | [optional]
  **body** | **file_type**|  | [optional]
 
 ### Return type

generated/docs/ImageQuery.md

@@ -11,7 +11,7 @@ Name | Type | Description | Notes
 **query** | **str** | A question about the image. | [readonly] 
 **detector_id** | **str** | Which detector was used on this image query? | [readonly] 
 **result_type** | **bool, date, datetime, dict, float, int, list, str, none_type** | What type of result are we returning? | [readonly] 
-**result** | **bool, date, datetime, dict, float, int, list, str, none_type** |  | [readonly] 
+**result** | **bool, date, datetime, dict, float, int, list, str, none_type** |  | [optional] [readonly] 
 **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]
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)

generated/model.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
 #   filename:  public-api.yaml
-#   timestamp: 2023-08-09T20:46:11+00:00
+#   timestamp: 2023-10-16T23:29:00+00:00
 
 from __future__ import annotations
 
@@ -69,7 +69,7 @@ class ImageQuery(BaseModel):
     query: str = Field(..., description="A question about the image.")
     detector_id: str = Field(..., description="Which detector was used on this image query?")
     result_type: ResultTypeEnum = Field(..., description="What type of result are we returning?")
-    result: ClassificationResult
+    result: Optional[ClassificationResult] = None
 
 
 class PaginatedDetectorList(BaseModel):

generated/openapi_client/api/image_queries_api.py

@@ -133,6 +133,7 @@ def __init__(self, api_client=None):
                     "detector_id",
                     "human_review",
                     "patience_time",
+                    "want_async",
                     "body",
                 ],
                 "required": [
@@ -149,17 +150,20 @@ def __init__(self, api_client=None):
                     "detector_id": (str,),
                     "human_review": (str,),
                     "patience_time": (float,),
+                    "want_async": (str,),
                     "body": (file_type,),
                 },
                 "attribute_map": {
                     "detector_id": "detector_id",
                     "human_review": "human_review",
                     "patience_time": "patience_time",
+                    "want_async": "want_async",
                 },
                 "location_map": {
                     "detector_id": "query",
                     "human_review": "query",
                     "patience_time": "query",
+                    "want_async": "query",
                     "body": "body",
                 },
                 "collection_format_map": {},
@@ -299,6 +303,7 @@ def submit_image_query(self, detector_id, **kwargs):
         Keyword Args:
             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]
             patience_time (float): How long to wait for a confident response.. [optional]
+            want_async (str): If \"true\" then submitting an image query returns immediately without a result. The result will be computed asynchronously and can be retrieved later.. [optional]
             body (file_type): [optional]
             _return_http_data_only (bool): response data without head status
                 code and headers. Default is True.

generated/openapi_client/model/image_query.py

@@ -168,9 +168,7 @@ def discriminator():
 
     @classmethod
     @convert_js_args_to_python_args
-    def _from_openapi_data(
-        cls, id, type, created_at, query, detector_id, result_type, result, *args, **kwargs
-    ):  # noqa: E501
+    def _from_openapi_data(cls, id, type, created_at, query, detector_id, result_type, *args, **kwargs):  # noqa: E501
         """ImageQuery - a model defined in OpenAPI
 
         Args:
@@ -180,7 +178,6 @@ def _from_openapi_data(
             query (str): A question about the image.
             detector_id (str): Which detector was used on this image query?
             result_type (bool, date, datetime, dict, float, int, list, str, none_type): What type of result are we returning?
-            result (bool, date, datetime, dict, float, int, list, str, none_type):
 
         Keyword Args:
             _check_type (bool): if True, values for parameters in openapi_types
@@ -213,6 +210,7 @@ def _from_openapi_data(
                                 Animal class but this time we won't travel
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
+            result (bool, date, datetime, dict, float, int, list, str, none_type): [optional]  # noqa: E501
         """
 
         _check_type = kwargs.pop("_check_type", True)
@@ -247,7 +245,6 @@ def _from_openapi_data(
         self.query = query
         self.detector_id = detector_id
         self.result_type = result_type
-        self.result = result
         for var_name, var_value in kwargs.items():
             if (
                 var_name not in self.attribute_map
@@ -306,6 +303,7 @@ def __init__(self, *args, **kwargs):  # noqa: E501
                                 Animal class but this time we won't travel
                                 through its discriminator because we passed in
                                 _visited_composed_classes = (Animal,)
+            result (bool, date, datetime, dict, float, int, list, str, none_type): [optional]  # noqa: E501
         """
 
         _check_type = kwargs.pop("_check_type", True)