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benoit.model/client.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ad3930f607d8db8eb34b552addced3924fb10130edc40bc23706882221700176
+size 7625

benoit.model/server.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:36d2998857e92d970e887bdbbe6860d5d72bc1a43373d1db5b04e51263d70aa0
+size 4370

benoit.model/versions.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:fee531e8b9857b9b7a601f6cf472f81da7b54d909f797f265b0975a35db81462
+size 79

handler.py

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+from typing import Dict, List, Any
+import numpy as np
+from concrete.ml.deployment import FHEModelServer
+
+
+class EndpointHandler:
+    def __init__(self, path):
+
+        # For server
+        self.fhemodel_server = FHEModelServer(path)
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+         data args:
+              inputs (:obj: `str`)
+              date (:obj: `str`)
+        Return:
+              A :obj:`list` | `dict`: will be serialized and returned
+        """
+
+        # Get inputs
+        encrypted_inputs = data.pop("encrypted_inputs", data)
+
+        # Get keys
+        evaluation_keys = data.pop("evaluation_keys", data)
+
+        # Run CML prediction
+        encrypted_prediction = self.fhemodel_server.run(encrypted_inputs, evaluation_keys)
+
+        return encrypted_prediction