Create app.py

app.py

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+import spacy
+import streamlit as st
+
+def article_summarizer(article_text, num_sentences=3):
+    nlp = spacy.load("en_core_web_sm")
+    doc = nlp(article_text)
+    sentence_importance = {}
+    for sentence in doc.sents:
+        sentence_tokens = [token for token in sentence if not token.is_stop]
+        sentence_rank = sum(token.rank for token in sentence_tokens)
+        sentence_importance[sentence] = sentence_rank
+    sorted_sentences = sorted(sentence_importance, key=lambda x: sentence_importance[x], reverse=True)
+    summary = " ".join(str(sentence) for sentence in sorted_sentences[:num_sentences])
+    return summary
+
+st.title("Article Summarizer")
+
+article = st.text_area("Enter your article here:")
+num_sentences = st.slider("Select the number of sentences for the summary:", 1, 10, 3)
+
+if st.button("Summarize"):
+    if article:
+        summary = article_summarizer(article, num_sentences)
+        st.subheader("Summary:")
+        st.write(summary)
+    else:
+        st.warning("Please enter an article to summarize.")