Create pipeline.py

pipeline.py

@@ -0,0 +1,25 @@
+import json
+from typing import Any, Dict, List
+
+import sklearn
+import os
+import joblib
+import numpy as np
+import whatlies
+
+
+
+class PreTrainedPipeline():
+    def __init__(self, path: str):
+        # load the model
+        self.model = joblib.load(os.path.join(path, "model.pkl"))
+
+    def __call__(self, inputs):
+        predictions = self.model.predict_proba([inputs])
+        labels = []
+        for cls in predictions[0]:
+          labels.append({
+                  "label": f"LABEL_{cls}",
+                  "score": predictions[0][cls],
+              })
+        return labels