[feat] remove some unused providers

edenai_apis/apis/__init__.py

@@ -9,7 +9,6 @@
 from .base64 import Base64Api
 from .clarifai import ClarifaiApi
 from .cohere import CohereApi
-from .connexun import ConnexunApi
 from .corticalio import CorticalioApi
 from .dataleon import DataleonApi
 from .deepai import DeepAIApi
@@ -24,37 +23,29 @@
 from .gladia import GladiaApi
 from .google import GoogleApi
 from .hireability import HireabilityApi
-from .ibm import IbmApi
 from .klippa import KlippaApi
-from .lettria import LettriaApi
 from .lovoai import LovoaiApi
 from .meaningcloud import MeaningcloudApi
 from .meta import MetaApi
 from .microsoft import MicrosoftApi
 from .mindee import MindeeApi
 from .mistral import MistralApi
 from .modernmt import ModernmtApi
-from .neuralspace import NeuralSpaceApi
-from .nlpcloud import NlpCloudApi
 from .nyckel import NyckelApi
 from .oneai import OneaiApi
 from .openai import OpenaiApi
 from .originalityai import OriginalityaiApi
 from .perplexityai import PerplexityApi
-from .phedone import PhedoneApi
 from .photoroom import PhotoroomApi
-from .picpurify import PicpurifyApi
 from .privateai import PrivateaiApi
 from .prowritingaid import ProWritingAidApi
 from .readyredact import ReadyRedactApi
 from .replicate import ReplicateApi
-from .revai import RevAIApi
 from .rossum import RossumApi
 from .sapling import SaplingApi
 from .senseloaf import SenseloafApi
 from .sentisight import SentiSightApi
 from .sightengine import SightEngineApi
-from .skybiometry import SkybiometryApi
 from .smartclick import SmartClickApi
 from .speechmatics import SpeechmaticsApi
 from .stabilityai import StabilityAIApi

edenai_apis/apis/clarifai/clarifai_api.py

@@ -56,7 +56,7 @@
 from .clarifai_helpers import explicit_content_likelihood, get_formatted_language
 
 
-class ClarifaiApi(ProviderInterface, OcrInterface, ImageInterface, TextInterface):
+class ClarifaiApi(ProviderInterface, OcrInterface, ImageInterface):
     provider_name = "clarifai"
 
     def __init__(self, api_keys: Dict = {}) -> None:
@@ -71,81 +71,6 @@ def __init__(self, api_keys: Dict = {}) -> None:
         self.text_moderation_code = "moderation-multilingual-text-classification"
         self.text_generation_code = "mistral-7B-Instruct"
 
-    def text__generation(
-        self, text: str, temperature: float, max_tokens: int, model: str
-    ) -> ResponseType[GenerationDataClass]:
-        raise ProviderException(
-            message="This provider is deprecated. You won't be charged for your call.",
-            code=500,
-        )
-
-    def text__moderation(
-        self, text: str, language: str
-    ) -> ResponseType[ModerationDataClass]:
-        channel = ClarifaiChannel.get_grpc_channel()
-        stub = service_pb2_grpc.V2Stub(channel)
-
-        metadata = (("authorization", self.key),)
-        user_data_object = resources_pb2.UserAppIDSet(user_id="clarifai", app_id="main")
-
-        post_model_outputs_response = stub.PostModelOutputs(
-            service_pb2.PostModelOutputsRequest(
-                # The userDataObject is created in the overview and is required when using a PAT
-                user_app_id=user_data_object,
-                model_id=self.text_moderation_code,
-                inputs=[
-                    resources_pb2.Input(
-                        data=resources_pb2.Data(text=resources_pb2.Text(raw=text))
-                    )
-                ],
-            ),
-            metadata=metadata,
-        )
-
-        if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
-            raise ProviderException(
-                post_model_outputs_response.status.description,
-                code=post_model_outputs_response.status.code,
-            )
-
-        response = MessageToDict(
-            post_model_outputs_response, preserving_proto_field_name=True
-        )
-        output = response.get("outputs", [])
-        if len(output) == 0:
-            raise ProviderException(
-                "Clarifai returned an empty response!",
-                code=post_model_outputs_response.status.code,
-            )
-
-        original_response = output[0].get("data", {}) or {}
-
-        classification: Sequence[TextModerationItem] = []
-        for concept in original_response.get("concepts", []) or []:
-            classificator = CategoryType.choose_category_subcategory(concept["name"])
-            classification.append(
-                TextModerationItem(
-                    label=concept["name"],
-                    category=classificator["category"],
-                    subcategory=classificator["subcategory"],
-                    likelihood_score=concept["value"],
-                    likelihood=standardized_confidence_score(concept["value"]),
-                )
-            )
-        standardized_response: ModerationDataClass = ModerationDataClass(
-            nsfw_likelihood=ModerationDataClass.calculate_nsfw_likelihood(
-                classification
-            ),
-            nsfw_likelihood_score=ModerationDataClass.calculate_nsfw_likelihood_score(
-                classification
-            ),
-            items=classification,
-        )
-        return ResponseType[ModerationDataClass](
-            original_response=original_response,
-            standardized_response=standardized_response,
-        )
-
     def ocr__ocr(
         self,
         file: str,