janet

ResponseGenerator.py

@@ -84,15 +84,14 @@ class ResponseGenerator:
     def _search_index(self, index_type, db_type, query, multi=False):
         self.index[index_type].add_faiss_index(column="embeddings")
         scores, samples = self.index[index_type].get_nearest_examples(
-            "embeddings", retriever.encode([query]), k=3
+            "embeddings", self.retriever.encode([query]), k=self.num_retrieved
         )
         samples_df = pd.DataFrame.from_dict(samples)
         samples_df["scores"] = scores
         samples_df.sort_values("scores", ascending=False, inplace=True)
-
         if multi:
             return samples_df.reset_index(drop=True)
-        return samples_df.iloc[0].reset_index(drop=True)
+        return samples_df.reset_index(drop=True).iloc[0]
 
 
     def gen_response(self, action, utterance=None, name=None, username=None, vrename=None, state=None, consec_history=None, chitchat_history=None):
@@ -275,8 +274,11 @@ class ResponseGenerator:
                             self.paper = paper
                             break
                     if (entity['entity'] == 'TOPIC'):
-                        self.paper = self._get_matching_topics('paper_db', entity['value'])
+                        cand_paper = self._get_matching_topics('paper_db', entity['value'])
+                        if len(cand_paper) > 0:
+                          self.paper = cand_paper
                 if len(self.paper) == 0:
+                    print(self.paper)
                     return "I cannot seem to find the requested paper. Try again by specifying the title of the paper."
             #implement that
             df = self.db['content_db'][self.db['content_db']['paperid'] == self.paper['id']]

main.py

@@ -209,7 +209,18 @@ if __name__ == "__main__":
     index = vre.get_index()
     db = vre.get_db()
     rg = ResponseGenerator(index,db, rec, generators, retriever)
-
+    del retriever
+    del generators
+    del qa_generator
+    del chat_generator
+    del summ_generator
+    del amb_generator
+    del query_rewriter
+    del intent_classifier
+    del entity_extractor
+    del offensive_classifier
+    del ambig_classifier
+    del coref_resolver 
     threading.Thread(target=vre_fetch, name='updatevre').start()
     threading.Thread(target=clear_inactive, name='clear').start()