Update pipeline.py

pipeline.py

@@ -7,30 +7,24 @@ import fasttext.util
 class PreTrainedPipeline():
 
     def __init__(self, path=""):
-
         """
-
         Initialize model
-
         """
 
         self.model = fasttext.load_model(os.path.join(path, 'debate2vec.bin'))
 
-    def __call__(self, inputs: str) -> List[float]:
-
+    def __call__(self, inputs: str) -> List[List[Dict[str, float]]]:
         """
-
         Args:
-
             inputs (:obj:`str`):
-
-                a string to get the features of.
-
+                a string containing some text
         Return:
-
-            A :obj:`list` of floats: The features computed by the model.
-
+            A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing :
+                - "label": A string representing what the label/class is. There can be multiple labels.
+                - "score": A score between 0 and 1 describing how confident the model is for this label/class.
         """
-
-        return self.model.get_sentence_vector(inputs).tolist()
-
+        preds = self.model.get_nearest_neighbors("dog", k=10)
+        result = []
+        for distance, word in preds:
+            result.append({"label": word, "score": distance})
+        return [result]