[feat] change all responses models to custom one

edenai_apis/features/audio/speech_to_text_async/speech_to_text_async_dataclass.py

@@ -1,22 +1,23 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence, Optional
 
 from pydantic import BaseModel, StrictStr, Field
 
 
-class SpeechDiarizationEntry(BaseModel):
+class SpeechDiarizationEntry(NoRaiseBaseModel):
     segment: StrictStr
     start_time: Optional[StrictStr]
     end_time: Optional[StrictStr]
     speaker: int
     confidence: Optional[float]
 
 
-class SpeechDiarization(BaseModel):
+class SpeechDiarization(NoRaiseBaseModel):
     total_speakers: int
     entries: Sequence[SpeechDiarizationEntry] = Field(default_factory=list)
     error_message: Optional[str] = None
 
 
-class SpeechToTextAsyncDataClass(BaseModel):
+class SpeechToTextAsyncDataClass(NoRaiseBaseModel):
     text: StrictStr
     diarization: SpeechDiarization

edenai_apis/features/audio/text_to_speech/text_to_speech_dataclass.py

@@ -1,9 +1,10 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Dict
 
 from pydantic import BaseModel, StrictStr
 
 
-class TextToSpeechDataClass(BaseModel):
+class TextToSpeechDataClass(NoRaiseBaseModel):
     audio: StrictStr
     voice_type: int
     audio_resource_url: StrictStr

edenai_apis/features/audio/text_to_speech_async/text_to_speech_async_dataclass.py

@@ -1,9 +1,10 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Dict
 
 from pydantic import BaseModel, StrictStr
 
 
-class TextToSpeechAsyncDataClass(BaseModel):
+class TextToSpeechAsyncDataClass(NoRaiseBaseModel):
     audio: StrictStr
     voice_type: int
     audio_resource_url: StrictStr

edenai_apis/features/image/anonymization/anonymization_dataclass.py

@@ -1,22 +1,23 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence, Optional
 
 from pydantic import BaseModel, StrictStr, Field
 
 
-class AnonymizationBoundingBox(BaseModel):
+class AnonymizationBoundingBox(NoRaiseBaseModel):
     x_min: Optional[float]
     x_max: Optional[float]
     y_min: Optional[float]
     y_max: Optional[float]
 
 
-class AnonymizationItem(BaseModel):
+class AnonymizationItem(NoRaiseBaseModel):
     kind: StrictStr
     confidence: float
     bounding_boxes: AnonymizationBoundingBox
 
 
-class AnonymizationDataClass(BaseModel):
+class AnonymizationDataClass(NoRaiseBaseModel):
     image: StrictStr
     image_resource_url: StrictStr
     items: Sequence[AnonymizationItem] = Field(default_factory=list)

edenai_apis/features/image/background_removal/background_removal_dataclass.py

@@ -1,3 +1,4 @@
+from utils.parsing import NoRaiseBaseModel
 import base64
 import importlib
 import uuid
@@ -9,7 +10,7 @@
 # from edenai_apis.utils.upload_s3 import upload_file_bytes_to_s3, USER_PROCESS
 
 
-class BackgroundRemovalDataClass(BaseModel):
+class BackgroundRemovalDataClass(NoRaiseBaseModel):
     """
     The response of the background removal API.
 

edenai_apis/features/image/embeddings/embeddings_dataclass.py

@@ -1,11 +1,12 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence
 
 from pydantic import BaseModel, Field
 
 
-class EmbeddingDataClass(BaseModel):
+class EmbeddingDataClass(NoRaiseBaseModel):
     embedding: Sequence[float]
 
 
-class EmbeddingsDataClass(BaseModel):
+class EmbeddingsDataClass(NoRaiseBaseModel):
     items: Sequence[EmbeddingDataClass] = Field(default_factory=list)

edenai_apis/features/image/explicit_content/explicit_content_dataclass.py

@@ -1,3 +1,4 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence, Union
 
 from pydantic import (
@@ -36,7 +37,7 @@
 ]
 
 
-class ExplicitItem(BaseModel):
+class ExplicitItem(NoRaiseBaseModel):
     label: StrictStr
     likelihood: int
     likelihood_score: float
@@ -50,7 +51,7 @@ def serialize_subcategory(self, value: SubCategoryType, _: FieldSerializationInf
         return value.value
 
 
-class ExplicitContentDataClass(BaseModel):
+class ExplicitContentDataClass(NoRaiseBaseModel):
     nsfw_likelihood: int
     nsfw_likelihood_score: float
     items: Sequence[ExplicitItem] = Field(default_factory=list)

edenai_apis/features/image/face_compare/face_compare_dataclass.py

@@ -1,19 +1,20 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Optional, Sequence
 
 from pydantic import BaseModel, Field
 
 
-class FaceCompareBoundingBox(BaseModel):
+class FaceCompareBoundingBox(NoRaiseBaseModel):
     top: Optional[float]
     left: Optional[float]
     height: Optional[float]
     width: Optional[float]
 
 
-class FaceMatch(BaseModel):
+class FaceMatch(NoRaiseBaseModel):
     confidence: Optional[float]
     bounding_box: FaceCompareBoundingBox
 
 
-class FaceCompareDataClass(BaseModel):
+class FaceCompareDataClass(NoRaiseBaseModel):
     items: Sequence[FaceMatch] = Field(default_factory=list)

edenai_apis/features/image/face_detection/face_detection_dataclass.py

@@ -1,9 +1,10 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Optional, Sequence
 
 from pydantic import BaseModel, Field, StrictStr
 
 
-class FaceLandmarks(BaseModel):
+class FaceLandmarks(NoRaiseBaseModel):
     left_eye: Sequence[float] = Field(default_factory=list)
     left_eye_top: Sequence[float] = Field(default_factory=list)
     left_eye_right: Sequence[float] = Field(default_factory=list)
@@ -58,7 +59,7 @@ class FaceLandmarks(BaseModel):
     right_cheek_center: Sequence[float] = Field(default_factory=list)
 
 
-class FaceEmotions(BaseModel):
+class FaceEmotions(NoRaiseBaseModel):
     joy: Optional[int]  # all
     sorrow: Optional[int]  # all
     anger: Optional[int]  # all
@@ -88,12 +89,12 @@ def default() -> "FaceEmotions":
         )
 
 
-class FaceHairColor(BaseModel):
+class FaceHairColor(NoRaiseBaseModel):
     color: StrictStr
     confidence: float
 
 
-class FaceHair(BaseModel):
+class FaceHair(NoRaiseBaseModel):
     hair_color: Sequence[FaceHairColor] = Field(default_factory=list)  # microsoft
     bald: Optional[float]  # microsoft
     invisible: Optional[bool]  # microsoft
@@ -103,7 +104,7 @@ def default() -> "FaceHair":
         return FaceHair(hair_color=[], bald=None, invisible=None)
 
 
-class FaceFacialHair(BaseModel):
+class FaceFacialHair(NoRaiseBaseModel):
     moustache: Optional[float]  # microsoft, amazon
     beard: Optional[float]  # microsoft, amazon
     sideburns: Optional[float]  # microsoft
@@ -113,7 +114,7 @@ def default() -> "FaceFacialHair":
         return FaceFacialHair(moustache=None, beard=None, sideburns=None)
 
 
-class FaceBoundingBox(BaseModel):
+class FaceBoundingBox(NoRaiseBaseModel):
     x_min: Optional[float]
     x_max: Optional[float]
     y_min: Optional[float]
@@ -129,7 +130,7 @@ def default() -> "FaceBoundingBox":
         )
 
 
-class FacePoses(BaseModel):
+class FacePoses(NoRaiseBaseModel):
     pitch: Optional[float]  # all
     roll: Optional[float]  # all
     yaw: Optional[float]  # all
@@ -139,7 +140,7 @@ def default() -> "FacePoses":
         return FacePoses(pitch=None, roll=None, yaw=None)
 
 
-class FaceQuality(BaseModel):
+class FaceQuality(NoRaiseBaseModel):
     noise: Optional[float]  # microsoft
     exposure: Optional[float]  # microsoft
     blur: Optional[float]  # microsoft
@@ -157,7 +158,7 @@ def default() -> "FaceQuality":
         )
 
 
-class FaceMakeup(BaseModel):
+class FaceMakeup(NoRaiseBaseModel):
     eye_make: Optional[bool]  # microsoft
     lip_make: Optional[bool]  # microsoft
 
@@ -166,7 +167,7 @@ def default() -> "FaceMakeup":
         return FaceMakeup(eye_make=None, lip_make=None)
 
 
-class FaceFeatures(BaseModel):
+class FaceFeatures(NoRaiseBaseModel):
     eyes_open: Optional[float]  # amazon
     smile: Optional[float]  # amazon
     mouth_open: Optional[float]  # amazon
@@ -176,7 +177,7 @@ def default() -> "FaceFeatures":
         return FaceFeatures(eyes_open=None, smile=None, mouth_open=None)
 
 
-class FaceAccessories(BaseModel):
+class FaceAccessories(NoRaiseBaseModel):
     sunglasses: Optional[float]  # microsoft, amazon
     reading_glasses: Optional[float]  # microsoft
     swimming_goggles: Optional[float]  # microsoft
@@ -196,7 +197,7 @@ def default() -> "FaceAccessories":
         )
 
 
-class FaceOcclusions(BaseModel):
+class FaceOcclusions(NoRaiseBaseModel):
     eye_occluded: Optional[bool]  # microsoft
     forehead_occluded: Optional[bool]  # microsoft
     mouth_occluded: Optional[bool]  # microsoft
@@ -210,7 +211,7 @@ def default() -> "FaceOcclusions":
         )
 
 
-class FaceItem(BaseModel):
+class FaceItem(NoRaiseBaseModel):
     confidence: float
     landmarks: FaceLandmarks
     emotions: FaceEmotions
@@ -227,5 +228,5 @@ class FaceItem(BaseModel):
     features: FaceFeatures
 
 
-class FaceDetectionDataClass(BaseModel):
+class FaceDetectionDataClass(NoRaiseBaseModel):
     items: Sequence[FaceItem] = Field(default_factory=list)

edenai_apis/features/image/face_recognition/add_face/face_recognition_add_face_dataclass.py

@@ -1,7 +1,8 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import List
 
 from pydantic import BaseModel
 
 
-class FaceRecognitionAddFaceDataClass(BaseModel):
+class FaceRecognitionAddFaceDataClass(NoRaiseBaseModel):
     face_ids: List[str]

edenai_apis/features/image/face_recognition/create_collection/face_recognition_create_collection_dataclass.py

@@ -1,5 +1,6 @@
+from utils.parsing import NoRaiseBaseModel
 from pydantic import BaseModel
 
 
-class FaceRecognitionCreateCollectionDataClass(BaseModel):
+class FaceRecognitionCreateCollectionDataClass(NoRaiseBaseModel):
     collection_id: str

edenai_apis/features/image/face_recognition/delete_collection/face_recognition_delete_collection_dataclass.py

@@ -1,5 +1,6 @@
+from utils.parsing import NoRaiseBaseModel
 from pydantic import BaseModel
 
 
-class FaceRecognitionDeleteCollectionDataClass(BaseModel):
+class FaceRecognitionDeleteCollectionDataClass(NoRaiseBaseModel):
     deleted: bool

edenai_apis/features/image/face_recognition/delete_face/face_recognition_delete_face_dataclass.py

@@ -1,5 +1,6 @@
+from utils.parsing import NoRaiseBaseModel
 from pydantic import BaseModel
 
 
-class FaceRecognitionDeleteFaceDataClass(BaseModel):
+class FaceRecognitionDeleteFaceDataClass(NoRaiseBaseModel):
     deleted: bool

edenai_apis/features/image/face_recognition/list_collections/face_recognition_list_collections_dataclass.py

@@ -1,7 +1,8 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import List
 
 from pydantic import BaseModel, Field
 
 
-class FaceRecognitionListCollectionsDataClass(BaseModel):
+class FaceRecognitionListCollectionsDataClass(NoRaiseBaseModel):
     collections: List[str] = Field(default_factory=list)

edenai_apis/features/image/face_recognition/list_faces/face_recognition_list_faces_dataclass.py

@@ -1,7 +1,8 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import List
 
 from pydantic import BaseModel
 
 
-class FaceRecognitionListFacesDataClass(BaseModel):
+class FaceRecognitionListFacesDataClass(NoRaiseBaseModel):
     face_ids: List[str]

edenai_apis/features/image/face_recognition/recognize/face_recognition_recognize_dataclass.py

@@ -1,12 +1,13 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import List
 
 from pydantic import BaseModel, Field
 
 
-class FaceRecognitionRecognizedFaceDataClass(BaseModel):
+class FaceRecognitionRecognizedFaceDataClass(NoRaiseBaseModel):
     confidence: float
     face_id: str
 
 
-class FaceRecognitionRecognizeDataClass(BaseModel):
+class FaceRecognitionRecognizeDataClass(NoRaiseBaseModel):
     items: List[FaceRecognitionRecognizedFaceDataClass] = Field(default_factory=list)

edenai_apis/features/image/generation/generation_dataclass.py

@@ -1,12 +1,13 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence
 
 from pydantic import BaseModel, Field, StrictStr
 
 
-class GeneratedImageDataClass(BaseModel):
+class GeneratedImageDataClass(NoRaiseBaseModel):
     image: str
     image_resource_url: StrictStr
 
 
-class GenerationDataClass(BaseModel):
+class GenerationDataClass(NoRaiseBaseModel):
     items: Sequence[GeneratedImageDataClass] = Field(default_factory=list)

edenai_apis/features/image/landmark_detection/landmark_detection_dataclass.py

@@ -1,28 +1,29 @@
+from utils.parsing import NoRaiseBaseModel
 from typing import Sequence
 
 from pydantic import BaseModel, Field, StrictStr
 
 
-class LandmarkVertice(BaseModel):
+class LandmarkVertice(NoRaiseBaseModel):
     x: int
     y: int
 
 
-class LandmarkLatLng(BaseModel):
+class LandmarkLatLng(NoRaiseBaseModel):
     latitude: float
     longitude: float
 
 
-class LandmarkLocation(BaseModel):
+class LandmarkLocation(NoRaiseBaseModel):
     lat_lng: LandmarkLatLng
 
 
-class LandmarkItem(BaseModel):
+class LandmarkItem(NoRaiseBaseModel):
     description: StrictStr
     confidence: float
     bounding_box: Sequence[LandmarkVertice] = Field(default_factory=list)
     locations: Sequence[LandmarkLocation] = Field(default_factory=list)
 
 
-class LandmarkDetectionDataClass(BaseModel):
+class LandmarkDetectionDataClass(NoRaiseBaseModel):
     items: Sequence[LandmarkItem] = Field(default_factory=list)