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Text Summarizer

Extractive AI summarization using TF-IDF sentence scoring. Picks the most important sentences from your text.

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Summarize Smarter, Not Harder

In a world of information overload, being able to extract key insights quickly is a superpower. Our **Text Summarizer** uses localized Natural Language Processing (NLP) to condense long articles, reports, or essays into their most essential points.

How TF-IDF Summarization Works

Instead of relying on remote AI models, this tool uses a mathematical approach called TF-IDF (Term Frequency-Inverse Document Frequency):

  • Sentence Tokenization: The script breaks your input into individual sentences and words.
  • Word Scoring: It calculates which words are the most important based on how often they appear in a sentence versus the rest of the text.
  • Sentence Ranking: Every sentence is given a "relevance score" based on the weight of the words it contains.
  • Extraction: The highest-ranking sentences are pulled together to form a concise summary.

Why Use Local Summarization?

Privacy is our priority. By running the summarization algorithm in your browser, your sensitive documents never leave your device. This makes it ideal for summarizing confidential business reports, legal papers, or personal study notes.

Frequently Asked Questions

Is this "Generative AI"?
No. This is an "Extractive" summarizer. It identifies and pulls the most important existing sentences from your text rather than generating new wording. This ensures 100% accuracy to the source material.
What is the ideal input size?
This tool works best with articles between 500 and 5,000 words. For very long books or documents, we recommend summarizing one chapter at a time for better focus.
Does it work with non-English text?
The TF-IDF algorithm is language-agnostic in its basic form, but it works most effectively with English because it identifies standard sentence structures and common words.