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Adds whoami function (#176)
* Adds whoami function * Automatically reformatting code --------- Co-authored-by: Auto-format Bot <[email protected]>
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‎generated/.openapi-generator/FILES

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@@ -13,11 +13,14 @@ docs/ImageQueryTypeEnum.md
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docs/PaginatedDetectorList.md
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docs/PaginatedImageQueryList.md
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docs/ResultTypeEnum.md
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docs/User.md
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docs/UserApi.md
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git_push.sh
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openapi_client/__init__.py
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openapi_client/api/__init__.py
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openapi_client/api/detectors_api.py
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openapi_client/api/image_queries_api.py
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openapi_client/api/user_api.py
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openapi_client/api_client.py
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openapi_client/apis/__init__.py
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openapi_client/configuration.py
@@ -32,6 +35,7 @@ openapi_client/model/image_query_type_enum.py
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openapi_client/model/paginated_detector_list.py
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openapi_client/model/paginated_image_query_list.py
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openapi_client/model/result_type_enum.py
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openapi_client/model/user.py
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openapi_client/model_utils.py
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openapi_client/models/__init__.py
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openapi_client/rest.py

‎generated/README.md

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@@ -103,6 +103,7 @@ Class | Method | HTTP request | Description
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*ImageQueriesApi* | [**get_image_query**](docs/ImageQueriesApi.md#get_image_query) | **GET** /v1/image-queries/{id} |
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*ImageQueriesApi* | [**list_image_queries**](docs/ImageQueriesApi.md#list_image_queries) | **GET** /v1/image-queries |
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*ImageQueriesApi* | [**submit_image_query**](docs/ImageQueriesApi.md#submit_image_query) | **POST** /v1/image-queries |
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*UserApi* | [**who_am_i**](docs/UserApi.md#who_am_i) | **GET** /me |
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## Documentation For Models
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- [PaginatedDetectorList](docs/PaginatedDetectorList.md)
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- [PaginatedImageQueryList](docs/PaginatedImageQueryList.md)
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- [ResultTypeEnum](docs/ResultTypeEnum.md)
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- [User](docs/User.md)
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## Documentation For Authorization

‎generated/docs/Detector.md

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@@ -12,7 +12,7 @@ Name | Type | Description | Notes
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**query** | **str** | A question about the image. | [readonly]
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**group_name** | **str** | Which group should this detector be part of? | [readonly]
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**confidence_threshold** | **float** | If the detector&#39;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
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**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). | [optional]
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**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]
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**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]
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[[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/docs/DetectorCreationInput.md

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@@ -10,7 +10,7 @@ Name | Type | Description | Notes
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**group_name** | **str** | Which group should this detector be part of? | [optional]
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**confidence_threshold** | **float** | If the detector&#39;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
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**pipeline_config** | **str, none_type** | (Advanced usage) Configuration to instantiate a specific prediction pipeline. | [optional]
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**metadata** | **str, none_type** | A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). | [optional]
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**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]
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**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]
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[[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/docs/User.md

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# User
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Spec for serializing a user object in the public API
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## Properties
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Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**username** | **str** | The user&#39;s username. |
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**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]
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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‎generated/docs/UserApi.md

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# openapi_client.UserApi
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All URIs are relative to *https://api.groundlight.ai/device-api*
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Method | HTTP request | Description
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------------- | ------------- | -------------
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[**who_am_i**](UserApi.md#who_am_i) | **GET** /me |
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# **who_am_i**
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> User who_am_i()
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Retrieve the current user.
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### Example
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* Api Key Authentication (ApiToken):
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```python
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import time
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import openapi_client
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from openapi_client.api import user_api
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from openapi_client.model.user import User
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from pprint import pprint
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# Defining the host is optional and defaults to https://api.groundlight.ai/device-api
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# See configuration.py for a list of all supported configuration parameters.
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configuration = openapi_client.Configuration(
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host = "https://api.groundlight.ai/device-api"
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)
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# The client must configure the authentication and authorization parameters
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# in accordance with the API server security policy.
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# Examples for each auth method are provided below, use the example that
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# satisfies your auth use case.
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# Configure API key authorization: ApiToken
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configuration.api_key['ApiToken'] = 'YOUR_API_KEY'
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# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
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# configuration.api_key_prefix['ApiToken'] = 'Bearer'
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# Enter a context with an instance of the API client
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with openapi_client.ApiClient(configuration) as api_client:
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# Create an instance of the API class
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api_instance = user_api.UserApi(api_client)
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# example, this endpoint has no required or optional parameters
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try:
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api_response = api_instance.who_am_i()
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pprint(api_response)
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except openapi_client.ApiException as e:
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print("Exception when calling UserApi->who_am_i: %s\n" % e)
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```
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### Parameters
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This endpoint does not need any parameter.
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### Return type
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[**User**](User.md)
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### Authorization
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[ApiToken](../README.md#ApiToken)
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### HTTP request headers
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- **Content-Type**: Not defined
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- **Accept**: application/json
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### HTTP response details
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| Status code | Description | Response headers |
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|-------------|-------------|------------------|
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**200** | | - |
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[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)
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‎generated/model.py

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# generated by datamodel-codegen:
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# filename: public-api.yaml
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# timestamp: 2024-01-16T18:09:48+00:00
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# timestamp: 2024-02-19T17:48:07+00:00
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from __future__ import annotations
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from pydantic import AnyUrl, BaseModel, Field, confloat, constr
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class User(BaseModel):
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username: str = Field(..., description="The user's username.")
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class ClassificationResult(BaseModel):
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confidence: Optional[confloat(ge=0.0, le=1.0)] = Field(
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None, description="On a scale of 0 to 1, how confident are we in the predicted label?"
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None, description="(Advanced usage) Configuration to instantiate a specific prediction pipeline."
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)
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metadata: Optional[str] = Field(
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None, description="A dictionary of custom key/value metadata to associate with the detector (limited to 1KB)."
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None,
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description=(
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"A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded"
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" as a URL-safe, base64-encoded JSON string."
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),
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)
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),
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)
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metadata: Optional[Dict[str, Any]] = Field(
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None, description="A dictionary of custom key/value metadata to associate with the detector (limited to 1KB)."
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None,
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description=(
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"A dictionary of custom key/value metadata to associate with the detector (limited to 1KB). This is encoded"
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" as a URL-safe, base64-encoded JSON string."
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),
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)
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‎generated/openapi_client/api/user_api.py

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"""
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Groundlight API
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Easy Computer Vision powered by Natural Language # noqa: E501
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The version of the OpenAPI document: 0.6.0
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Contact: [email protected]
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Generated by: https://openapi-generator.tech
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"""
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import re # noqa: F401
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import sys # noqa: F401
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from openapi_client.api_client import ApiClient, Endpoint as _Endpoint
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from openapi_client.model_utils import ( # noqa: F401
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check_allowed_values,
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check_validations,
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date,
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datetime,
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file_type,
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none_type,
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validate_and_convert_types,
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)
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from openapi_client.model.user import User
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class UserApi(object):
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"""NOTE: This class is auto generated by OpenAPI Generator
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Ref: https://openapi-generator.tech
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Do not edit the class manually.
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"""
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def __init__(self, api_client=None):
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if api_client is None:
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api_client = ApiClient()
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self.api_client = api_client
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self.who_am_i_endpoint = _Endpoint(
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settings={
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"response_type": (User,),
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"auth": ["ApiToken"],
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"endpoint_path": "/me",
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"operation_id": "who_am_i",
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"http_method": "GET",
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"servers": None,
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},
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params_map={"all": [], "required": [], "nullable": [], "enum": [], "validation": []},
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root_map={
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"validations": {},
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"allowed_values": {},
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"openapi_types": {},
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"attribute_map": {},
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"location_map": {},
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"collection_format_map": {},
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},
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headers_map={
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"accept": ["application/json"],
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"content_type": [],
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},
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api_client=api_client,
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)
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def who_am_i(self, **kwargs):
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"""who_am_i # noqa: E501
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Retrieve the current user. # noqa: E501
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This method makes a synchronous HTTP request by default. To make an
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asynchronous HTTP request, please pass async_req=True
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>>> thread = api.who_am_i(async_req=True)
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>>> result = thread.get()
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Keyword Args:
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_return_http_data_only (bool): response data without head status
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code and headers. Default is True.
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_preload_content (bool): if False, the urllib3.HTTPResponse object
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will be returned without reading/decoding response data.
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Default is True.
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_request_timeout (int/float/tuple): timeout setting for this request. If
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one number provided, it will be total request timeout. It can also
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be a pair (tuple) of (connection, read) timeouts.
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Default is None.
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_check_input_type (bool): specifies if type checking
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should be done one the data sent to the server.
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Default is True.
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_check_return_type (bool): specifies if type checking
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should be done one the data received from the server.
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Default is True.
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_spec_property_naming (bool): True if the variable names in the input data
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are serialized names, as specified in the OpenAPI document.
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False if the variable names in the input data
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are pythonic names, e.g. snake case (default)
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_content_type (str/None): force body content-type.
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Default is None and content-type will be predicted by allowed
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content-types and body.
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_host_index (int/None): specifies the index of the server
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that we want to use.
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Default is read from the configuration.
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async_req (bool): execute request asynchronously
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Returns:
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User
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If the method is called asynchronously, returns the request
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thread.
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"""
108+
kwargs["async_req"] = kwargs.get("async_req", False)
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kwargs["_return_http_data_only"] = kwargs.get("_return_http_data_only", True)
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kwargs["_preload_content"] = kwargs.get("_preload_content", True)
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kwargs["_request_timeout"] = kwargs.get("_request_timeout", None)
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kwargs["_check_input_type"] = kwargs.get("_check_input_type", True)
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kwargs["_check_return_type"] = kwargs.get("_check_return_type", True)
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kwargs["_spec_property_naming"] = kwargs.get("_spec_property_naming", False)
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kwargs["_content_type"] = kwargs.get("_content_type")
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kwargs["_host_index"] = kwargs.get("_host_index")
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return self.who_am_i_endpoint.call_with_http_info(**kwargs)

‎generated/openapi_client/apis/__init__.py

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# Import APIs into API package:
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from openapi_client.api.detectors_api import DetectorsApi
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from openapi_client.api.image_queries_api import ImageQueriesApi
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from openapi_client.api.user_api import UserApi

‎generated/openapi_client/model/detector.py

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through its discriminator because we passed in
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_visited_composed_classes = (Animal,)
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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
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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).. [optional] # noqa: E501
201+
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
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"""
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204204
_check_type = kwargs.pop("_check_type", True)
@@ -293,7 +293,7 @@ def __init__(self, name, *args, **kwargs): # noqa: E501
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through its discriminator because we passed in
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_visited_composed_classes = (Animal,)
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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
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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).. [optional] # noqa: E501
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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
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"""
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_check_type = kwargs.pop("_check_type", True)

‎generated/openapi_client/model/detector_creation_input.py

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group_name (str): Which group should this detector be part of?. [optional] # noqa: E501
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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
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pipeline_config (str, none_type): (Advanced usage) Configuration to instantiate a specific prediction pipeline.. [optional] # noqa: E501
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metadata (str, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB).. [optional] # noqa: E501
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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
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"""
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_check_type = kwargs.pop("_check_type", True)
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group_name (str): Which group should this detector be part of?. [optional] # noqa: E501
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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
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pipeline_config (str, none_type): (Advanced usage) Configuration to instantiate a specific prediction pipeline.. [optional] # noqa: E501
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metadata (str, none_type): A dictionary of custom key/value metadata to associate with the detector (limited to 1KB).. [optional] # noqa: E501
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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
280280
"""
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282282
_check_type = kwargs.pop("_check_type", True)

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