fix

generateDistractors/senseToVec.py

@@ -1,5 +1,4 @@
 from sense2vec import Sense2Vec
-from fastapi import FastAPI
 from sentence_transformers import SentenceTransformer
 import wget
 import os
@@ -30,29 +29,27 @@ class S2V:
     return answer_embedding,distractor_embeddings
   
   def execute(self, originalword):
-    word = originalword.lower()
-    word = word.replace(" ", "_")
-    # Find the best-matching sense for a given word based on the available senses and frequency counts. 
-    sense = self.s2v.get_best_sense(word)
-    # Get the most similar entries in the table
-    most_similar = self.s2v.most_similar(sense, n=20)
-    #remove duplicates
-    distractors = self.removeDuplicates(most_similar, originalword)
-    distractors.insert(0,originalword)
-    # encode distractors and answer
-    answer_embedd, distractor_embedds = self.get_answer_and_distractor_embeddings(originalword,distractors)
-    #Maximal Marginal Relevance origin: https://maartengr.github.io/KeyBERT/api/mmr.html
-    final_distractors = mmr(answer_embedd,distractor_embedds,distractors,5)
-    filtered_distractors = []
-
-    for dist in final_distractors:
-      filtered_distractors.append(dist[0])
+    try:
+      word = originalword.lower()
+      word = word.replace(" ", "_")
+      # Find the best-matching sense for a given word based on the available senses and frequency counts. 
+      sense = self.s2v.get_best_sense(word)
+      # Get the most similar entries in the table
+      most_similar = self.s2v.most_similar(sense, n=20)
+      #remove duplicates
+      distractors = self.removeDuplicates(most_similar, originalword)
+      distractors.insert(0,originalword)
+      # encode distractors and answer
+      answer_embedd, distractor_embedds = self.get_answer_and_distractor_embeddings(originalword,distractors)
+      #Maximal Marginal Relevance origin: https://maartengr.github.io/KeyBERT/api/mmr.html
+      final_distractors = mmr(answer_embedd,distractor_embedds,distractors,5)
+      filtered_distractors = []
 
-    Answer = filtered_distractors[0]
-    Filtered_Distractors =  filtered_distractors[1:]
-    return {
-      "answer": Answer,
-      "distractors": Filtered_Distractors
-    }
+      for dist in final_distractors:
+        filtered_distractors.append(dist[0])
 
-sense2Vec = S2V()
+      #Answer = filtered_distractors[0]
+      Filtered_Distractors =  filtered_distractors[1:]
+      return Filtered_Distractors
+    except:
+      return []

questionGeneration/questionGeneration.py

@@ -32,5 +32,3 @@ class QuestionGeneration:
         Question = dec[0].replace("question:","")
         Question= Question.strip()
         return Question
-
-Question = QuestionGeneration()

summarizer/summarizer.py

@@ -65,6 +65,3 @@ class Summarizer:
         summary= summary.strip()
 
         return summary
-
-Summary = Summarizer()
-