README.md

metadata

title: Narrative Summarizer
emoji: 📚
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 5.45.0
app_file: app.py
pinned: false
license: mit
tags:
  - summarization
  - text
  - transformer
  - bart
  - compression
  - gradio

Narrative Summarizer

A Gradio-based app to summarize large narrative .txt files using transformer models with advanced chunking and multi-pass summarization.

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Features

• Robust UTF-8 file handling with encoding detection for smooth uploads.
• Token-based chunking to handle large files efficiently.
• Multiple prompt styles via dropdown:
  • Bread Only
  • Butter Only
  • Bread and Butter
• Iterative summarization passes for better global compression.
• Second-pass summarization to refine and compress summaries further.
• Built with Hugging Face Transformers and Gradio.

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Setup

1. Clone this repo:

   git clone https://huggingface.co/spaces/psyrishi/narrative-summarizer
   cd narrative-summarizer
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the app locally:

   python app.py
   

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Usage

• Upload a .txt file (UTF-8 or similar encodings supported).
• Choose a prompt style from the dropdown.
• Select the number of summarization iterations (≥1).
• Click Summarize to get the output.

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How It Works

• Reads the input file with encoding detection to avoid decode errors.
• Splits text into token-based chunks (~200 tokens each).
• Applies custom prompts and summarizes each chunk.
• Optionally, performs multiple iterative passes to refine the summary.
• Combines chunk summaries and performs a second-pass summarization for global compression.

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Notes

• Model used: facebook/bart-large-cnn (can be customized in summarizer.py).
• GPU acceleration can speed up summarization if available.
• For very large files, increase iterations cautiously to avoid long runtimes.

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License

This project is licensed under the MIT License.

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Author

Created by psyrishi

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Feel free to contribute or raise issues!