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Running
on
Zero
File size: 3,142 Bytes
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from typing import Dict, List, Optional, Union
from pydantic import Field, validator
from inference.core.entities.requests.inference import (
BaseRequest,
InferenceRequestImage,
)
from inference.core.env import CLIP_VERSION_ID
class ClipInferenceRequest(BaseRequest):
"""Request for CLIP inference.
Attributes:
api_key (Optional[str]): Roboflow API Key.
clip_version_id (Optional[str]): The version ID of CLIP to be used for this request.
"""
clip_version_id: Optional[str] = Field(
default=CLIP_VERSION_ID,
examples=["ViT-B-16"],
description="The version ID of CLIP to be used for this request. Must be one of RN101, RN50, RN50x16, RN50x4, RN50x64, ViT-B-16, ViT-B-32, ViT-L-14-336px, and ViT-L-14.",
)
model_id: Optional[str] = Field(None)
# TODO[pydantic]: We couldn't refactor the `validator`, please replace it by `field_validator` manually.
# Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-validators for more information.
@validator("model_id", always=True)
def validate_model_id(cls, value, values):
if value is not None:
return value
if values.get("clip_version_id") is None:
return None
return f"clip/{values['clip_version_id']}"
class ClipImageEmbeddingRequest(ClipInferenceRequest):
"""Request for CLIP image embedding.
Attributes:
image (Union[List[InferenceRequestImage], InferenceRequestImage]): Image(s) to be embedded.
"""
image: Union[List[InferenceRequestImage], InferenceRequestImage]
class ClipTextEmbeddingRequest(ClipInferenceRequest):
"""Request for CLIP text embedding.
Attributes:
text (Union[List[str], str]): A string or list of strings.
"""
text: Union[List[str], str] = Field(
examples=["The quick brown fox jumps over the lazy dog"],
description="A string or list of strings",
)
class ClipCompareRequest(ClipInferenceRequest):
"""Request for CLIP comparison.
Attributes:
subject (Union[InferenceRequestImage, str]): The type of image data provided, one of 'url' or 'base64'.
subject_type (str): The type of subject, one of 'image' or 'text'.
prompt (Union[List[InferenceRequestImage], InferenceRequestImage, str, List[str], Dict[str, Union[InferenceRequestImage, str]]]): The prompt for comparison.
prompt_type (str): The type of prompt, one of 'image' or 'text'.
"""
subject: Union[InferenceRequestImage, str] = Field(
examples=["url"],
description="The type of image data provided, one of 'url' or 'base64'",
)
subject_type: str = Field(
default="image",
examples=["image"],
description="The type of subject, one of 'image' or 'text'",
)
prompt: Union[
List[InferenceRequestImage],
InferenceRequestImage,
str,
List[str],
Dict[str, Union[InferenceRequestImage, str]],
]
prompt_type: str = Field(
default="text",
examples=["text"],
description="The type of prompt, one of 'image' or 'text'",
)
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