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- from typing import Any, Dict, Optional, Union
- from huggingface_hub.inference._common import RequestParameters, _as_dict
- from ._common import BaseConversationalTask, InferenceProviderMapping, TaskProviderHelper, filter_none
- class ScalewayConversationalTask(BaseConversationalTask):
- def __init__(self):
- super().__init__(provider="scaleway", base_url="https://api.scaleway.ai")
- class ScalewayFeatureExtractionTask(TaskProviderHelper):
- def __init__(self):
- super().__init__(provider="scaleway", base_url="https://api.scaleway.ai", task="feature-extraction")
- def _prepare_route(self, mapped_model: str, api_key: str) -> str:
- return "/v1/embeddings"
- def _prepare_payload_as_dict(
- self, inputs: Any, parameters: Dict, provider_mapping_info: InferenceProviderMapping
- ) -> Optional[Dict]:
- parameters = filter_none(parameters)
- return {"input": inputs, "model": provider_mapping_info.provider_id, **parameters}
- def get_response(self, response: Union[bytes, Dict], request_params: Optional[RequestParameters] = None) -> Any:
- embeddings = _as_dict(response)["data"]
- return [embedding["embedding"] for embedding in embeddings]
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