Merge branch 'master' of github.com:edenai/edenai-apis

README.md

@@ -78,7 +78,7 @@ for item in ibm_res.standardized_response.items:
 
 ### Asynchronous features
 
-If you need to use features like _speech to text_, _object extraction_ from videos, etc. Then you will have to use asynchrounous operations. This means that you will first make a call to launch an asynchrounous job, it will then return a job ID allowing you to make other calls to get the job status or response if the job is finished
+If you need to use features like _speech to text_, _object extraction_ from videos, etc. Then you will have to use asynchronous operations. This means that you will first make a call to launch an asynchronous job, it will then return a job ID allowing you to make other calls to get the job status or response if the job is finished
 
 ```python
 from edenai_apis import Audio

edenai_apis/apis/affinda/client.py

@@ -1,20 +1,20 @@
-#TODO: Add tests for this file
 from enum import Enum
+from http import HTTPStatus
 from io import BufferedReader
 from json import JSONDecodeError
 from typing import Any, Dict, List, Literal, Optional
 from warnings import warn
 
 import requests
-from http import HTTPStatus
 
 from edenai_apis.utils.exception import ProviderException
 from edenai_apis.utils.http import HTTPMethod
-from .models import Document, Organization, Workspace, Collection
 from .document import DocumentState, FileParameter, QueryBuilder, UploadDocumentParams
+from .models import Document, Organization, Workspace, Collection
+
 
 class ExtractorType(Enum):
-    """This class are use to define the type of an extractor
+    """This class are used to define the type of extractor
 
     Actually the affinda api support 6 type of extractor:
         - resume
@@ -478,15 +478,15 @@ def create_document(
                 .add_workspace(self.__current_workspace)
                 .add_collection(self.__current_collection)
                 .build()
-            )
+            ),
         }
 
         files: Optional[Dict[str, BufferedReader]] = None
 
-        if file.type == 'url':
-            payload['url'] = file.file
-        elif file.type == 'file':
-            files = { 'file': open(file.file, 'rb') }
+        if file.type == "url":
+            payload["url"] = file.file
+        elif file.type == "file":
+            files = {"file": open(file.file, "rb")}
 
         return Document(
             **self.__requests(
@@ -499,7 +499,7 @@ def create_document(
         )
 
     def delete_document(self, identifier: str) -> None:
-        """ Delete the document with the given identifier.
+        """Delete the document with the given identifier.
 
         Args:
             identifier (str): The identifier of the document.

edenai_apis/apis/alephalpha/alephalpha_api.py

@@ -1,19 +1,28 @@
 from typing import Dict, Sequence, Optional
 
 import requests
+from aleph_alpha_client import (
+    Client,
+    Prompt,
+    SemanticEmbeddingRequest,
+    Image,
+    SemanticRepresentation,
+    CompletionRequest,
+    Text,
+)
 
 from edenai_apis.features import ProviderInterface, TextInterface, ImageInterface
-from edenai_apis.features.image.embeddings import EmbeddingsDataClass, EmbeddingDataClass
+from edenai_apis.features.image.embeddings import (
+    EmbeddingsDataClass,
+    EmbeddingDataClass,
+)
 from edenai_apis.features.image.question_answer import QuestionAnswerDataClass
 from edenai_apis.features.text import SummarizeDataClass
 from edenai_apis.loaders.data_loader import ProviderDataEnum
 from edenai_apis.loaders.loaders import load_provider
 from edenai_apis.utils.exception import ProviderException
 from edenai_apis.utils.types import ResponseType
 
-from aleph_alpha_client import Client, Prompt, SemanticEmbeddingRequest, QaRequest, Image, SemanticRepresentation, \
-    Document, CompletionRequest, Text
-
 
 class AlephAlphaApi(ProviderInterface, TextInterface, ImageInterface):
     provider_name = "alephalpha"
@@ -27,23 +36,18 @@ def __init__(self, api_keys: Dict = {}):
         self.url_summarise = "https://api.aleph-alpha.com/summarize"
 
     def text__summarize(
-            self,
-            text: str,
-            output_sentences: int,
-            language: str,
-            model: str,
+        self,
+        text: str,
+        output_sentences: int,
+        language: str,
+        model: str,
     ) -> ResponseType[SummarizeDataClass]:
         headers = {
             "Content-Type": "application/json",
             "Accept": "application/json",
-            "Authorization": f"Bearer {self.api_key}"
-        }
-        payload = {
-            "model": model,
-            "document": {
-                "text": text
-            }
+            "Authorization": f"Bearer {self.api_key}",
         }
+        payload = {"model": model, "document": {"text": text}}
         response = requests.post(url=self.url_summarise, headers=headers, json=payload)
         if response.status_code != 200:
             raise ProviderException(response.text, code=response.status_code)
@@ -57,7 +61,11 @@ def text__summarize(
         )
 
     def image__embeddings(
-            self, file: str, model: str, representation: str, file_url: str = "",
+        self,
+        file: str,
+        model: str,
+        representation: str,
+        file_url: str = "",
     ) -> ResponseType[EmbeddingsDataClass]:
         if representation == "symmetric":
             representation_client = SemanticRepresentation.Symmetric
@@ -67,47 +75,54 @@ def image__embeddings(
             representation_client = SemanticRepresentation.Query
         client = Client(self.api_key)
         prompt = Prompt.from_image(Image.from_file(file))
-        request = SemanticEmbeddingRequest(prompt=prompt, representation=representation_client)
+        request = SemanticEmbeddingRequest(
+            prompt=prompt, representation=representation_client
+        )
         try:
             response = client.semantic_embed(request=request, model=model)
-        except:
-            raise ProviderException(response.message)
-        if response.message:
-            raise ProviderException(response.message)
+        except Exception as exc:
+            raise ProviderException(message=str(exc)) from exc
+
         original_response = response._asdict()
-        items: Sequence[EmbeddingDataClass] = [EmbeddingDataClass(embedding=response.embedding)]
+        items: Sequence[EmbeddingDataClass] = [
+            EmbeddingDataClass(embedding=response.embedding)
+        ]
         standardized_response = EmbeddingsDataClass(items=items)
         return ResponseType[EmbeddingsDataClass](
             original_response=original_response,
-            standardized_response=standardized_response
+            standardized_response=standardized_response,
         )
 
     def image__question_answer(
-            self,
-            file: str,
-            temperature: float,
-            max_tokens: int,
-            file_url: str = "",
-            model: Optional[str] = None,
-            question: Optional[str] = None
+        self,
+        file: str,
+        temperature: float,
+        max_tokens: int,
+        file_url: str = "",
+        model: Optional[str] = None,
+        question: Optional[str] = None,
     ) -> ResponseType[QuestionAnswerDataClass]:
         client = Client(self.api_key)
         if question:
             prompts = Prompt([Text.from_text(question), Image.from_file(file)])
         else:
             prompts = Prompt([Image.from_file(file)])
-        request = CompletionRequest(prompt=prompts, maximum_tokens=max_tokens, temperature=temperature, tokens=True)
+        request = CompletionRequest(
+            prompt=prompts,
+            maximum_tokens=max_tokens,
+            temperature=temperature,
+            tokens=True,
+        )
         try:
             response = client.complete(request=request, model=model)
         except Exception as error:
-            raise ProviderException(str(error))
+            raise ProviderException(str(error)) from error
         original_response = response._asdict()
         answers = []
         for answer in response.completions:
             answers.append(answer.completion)
         standardized_response = QuestionAnswerDataClass(answers=answers)
         return ResponseType[QuestionAnswerDataClass](
             original_response=original_response,
-            standardized_response=standardized_response
+            standardized_response=standardized_response,
         )
-

edenai_apis/apis/winstonai/config.py

@@ -1,3 +1 @@
-TOKEN_BEARER = "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImRkZ3NzdXRyaHpya2xsc3RnbGRiIiwicm9sZSI6ImFub24iLCJpYXQiOjE2ODY2ODc5MjMsImV4cCI6MjAwMjI2MzkyM30.bwSe1TrFMhcosgqFSlGIhMIv9fxohzLG0eyBEs7wUo8"
-
 WINSTON_AI_API_URL = "https://api.gowinston.ai/functions/v1"

edenai_apis/apis/winstonai/info.json

@@ -1,18 +1,19 @@
 {
     "text": {
       "ai_detection":{
-        "version" : "v1",
+        "version" : "v2",
         "constraints": {
           "languages": [
               "en",
               "fr",
               "es",
-              "de"
+              "de",
+              "pt"
           ]
       }
     },
       "plagia_detection":{
-        "version" : "v1"
+        "version" : "v2"
     }
   }
 }

edenai_apis/apis/winstonai/outputs/text/ai_detection_output.json

@@ -30,40 +30,41 @@
     ],
     "length": 2,
     "credits_used": 338,
-    "credits_remaining": 9829
+    "credits_remaining": 99999662
   },
   "standardized_response": {
     "ai_score": 0.0001,
     "items": [
       {
         "text": "The panther, also known as the black panther, is a magnificent and enigmatic creature that captivates the imagination of many. It is not a distinct species itself, but rather a melanistic variant of leopards and jaguars. The mesmerizing black coat of the panther is a result of a genetic mutation that increases the production of dark pigment, melanin.",
-        "prediction": "original",
-        "ai_score": 0.0032
+        "prediction": "ai-generated",
+        "ai_score": 0.32
       },
       {
         "text": "Panthers are highly adaptable predators, found primarily in dense forests and jungles across Africa, Asia, and the Americas. Their stealthy nature and exceptional agility make them formidable hunters. They are solitary creatures, preferring to roam alone in their vast territories, which can span over a hundred square miles.",
-        "prediction": "original",
-        "ai_score": 0.0003
+        "prediction": "ai-generated",
+        "ai_score": 0.03
       },
       {
         "text": "Equipped with incredible strength and sharp retractable claws, panthers are skilled climbers and swimmers. Their keen senses, including sharp vision and acute hearing, aid them in locating prey, often stalking their victims from the cover of trees or thick underbrush before launching a precise and powerful attack. The diet of a panther consists mainly of deer, wild boar, and smaller mammals.",
-        "prediction": "original",
-        "ai_score": 0.0002
+        "prediction": "ai-generated",
+        "ai_score": 0.02
       },
       {
         "text": "However, they are opportunistic hunters and can also target livestock and domestic animals in areas where their habitats overlap with human settlements. Unfortunately, this sometimes leads to conflicts with humans, resulting in the panther being perceived as a threat.",
-        "prediction": "original",
-        "ai_score": 0.0006
+        "prediction": "ai-generated",
+        "ai_score": 0.06
       },
       {
         "text": "Despite their association with darkness and mystery, panthers play a vital role in maintaining the balance of ecosystems. As apex predators, they help control populations of herbivores, preventing overgrazing and maintaining healthy prey dynamics. Conservation efforts are crucial to the survival of panther populations worldwide.",
-        "prediction": "original",
-        "ai_score": 0.0001
+        "prediction": "ai-generated",
+        "ai_score": 0.01
       },
       {
         "text": "Habitat loss, poaching, and illegal wildlife trade pose significant threats to their existence. Various organizations and governments are working tirelessly to protect these magnificent creatures through initiatives such as establishing protected areas, promoting sustainable land use practices, and raising awareness about their importance in the natural world.",
-        "prediction": "original",
-        "ai_score": 0.0001
+        "prediction": "ai-generated",
+        "ai_score": 0.01
+
       }
     ]
   }