Исправлен вывод.

app.py

@@ -1,7 +1,9 @@
 import streamlit as st
 
 st.markdown("""### TL;DR: give me the keywords!
-Here you can get the keywords and topic of the article based on it's title or abstract.""")
+Here you can get the keywords and topic of the article based on it's title or abstract.
+
+The only supported language is English.""")
 
 st.markdown("<p style=\"text-align:center\"><img width=700px src='https://c.tenor.com/IKt-6tAk9CUAAAAd/thats-a-lot-of-words-lots-of-words.gif'></p>", unsafe_allow_html=True)
 
@@ -13,6 +15,16 @@ st.markdown("<p style=\"text-align:center\"><img width=700px src='https://c.teno
 title = st.text_area("Title:")
 abstract = st.text_area("abstract:")
 
+from transformers import AutoModel, AutoTokenizer
+#from tqdm import tqdm as tqdm
+
+import transformers
+transformers.utils.logging.disable_progress_bar()
+
+model_name = "distilroberta-base"
+main_model = AutoModel.from_pretrained(model_name)
+main_tokenizer = AutoTokenizer.from_pretrained(model_name)
+
 
 from utils.utils import *
 import spacy
@@ -26,11 +38,10 @@ os.system("python3 -m spacy download en")
 main_nlp = spacy.load('en_core_web_sm')
 
 text = title + abstract
-#text = preprocess(text)
-
-keywords = get_candidates(text, main_nlp)
 
-if not keywords is None and len(keywords) > 0:
+if not text is None and len(text) > 0:
+    #keywords = get_candidates(text, main_nlp)
+    keywords = get_keywords(summaries[0], main_nlp, main_model, main_tokenizer)
     st.markdown(f"{keywords}")
 else:
     st.markdown("Please, try to enter something.")