Update news_category_similar_news_prediction.py

news_category_similar_news_prediction.py

@@ -76,7 +76,7 @@ def predict_news_category_similar_news(old_news: pd.DataFrame, new_news: pd.Data
             headlines = [*final_df['title']].copy()
             label, prob = inference(headlines, interpreter, label_encoder, tokenizer)
             sent_embs = vectorizer.vectorize_(headlines, sent_model)
-            sim_news = [find_similar_news(search_vec, collection, vectorizer, sent_model, ce_model) for search_vec in sent_embs]
+            sim_news = [find_similar_news(text, search_vec, collection, vectorizer, sent_model, ce_model) for search_vec, text in zip(sent_embs, headlines)]
             final_df['category'] = label
             final_df['pred_proba'] = prob
             final_df['similar_news'] = sim_news
@@ -92,7 +92,7 @@ def predict_news_category_similar_news(old_news: pd.DataFrame, new_news: pd.Data
                 headlines = [*new_news['title']].copy()
                 label, prob = inference(headlines, interpreter, label_encoder, tokenizer)
                 sent_embs = vectorizer.vectorize_(headlines, sent_model)
-                sim_news = [find_similar_news(search_vec, collection, vectorizer, sent_model, ce_model) for search_vec in sent_embs]
+                sim_news = [find_similar_news(text, search_vec, collection, vectorizer, sent_model, ce_model) for search_vec, text in zip(sent_embs, headlines)]
                 new_news['category'] = label
                 new_news['pred_proba'] = prob
                 final_df['similar_news'] = sim_news