Text Summarizer using TextRank (NLP)

Text Summarization (NLP)/readme.txt

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+Text Summarization using TextRank (sumy)
+
+This Python script takes a longer piece of text as input and generates a concise summary using the TextRank algorithm from the `sumy` library. TextRank is an extractive text summarization algorithm that identifies important sentences based on the connections between words.
+
+Requirements:
+
+pip install sumy

Text Summarization (NLP)/script.py

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+from sumy.parsers.plaintext import PlaintextParser
+from sumy.nlp.tokenizers import Tokenizer
+from sumy.summarizers.text_rank import TextRankSummarizer
+from sumy.utils import get_stop_words
+
+def summarize_text(text, num_sentences=3):
+    parser = PlaintextParser.from_string(text, Tokenizer("english"))
+    summarizer = TextRankSummarizer()
+    summarizer.stop_words = get_stop_words("english")
+
+    summary = summarizer(parser.document, num_sentences)
+    return "\n".join([str(sentence) for sentence in summary])
+
+def main():
+    text = input("Enter the longer piece of text: ")
+    num_sentences = int(input("Enter the number of sentences for summary: "))
+
+    summary = summarize_text(text, num_sentences)
+    print("\nSummary:")
+    print(summary)
+
+if __name__ == "__main__":
+    main()