Create app.py

app.py

@@ -0,0 +1,16 @@
+import pytextrank
+import spacy
+import streamlit as st
+nlp = spacy.load("en_core_web_sm")
+nlp.add_pipe("textrank")
+input= st.text_area("Input text to summarize")
+user_limit=int(len(input.split("."))/5)
+doc=nlp(input)
+output=""
+if st.button("Summarize"):
+    for i in doc._.textrank.summary(limit_sentences=user_limit):
+        a=i.text
+        output=output+a
+    st.markdown(output)
+    st.text("Length of Article="+str(len(input.split()))+" words")
+    st.text("Length of summary="+str(len(output.split()))+" words")