README.md

metadata

title: Narrative Summarizer
emoji: 📚
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 4.15.0
app_file: app.py
pinned: false
license: mit
tags:
  - summarization
  - text
  - transformer
  - bart
  - compression
  - gradio

📚 Narrative Summarizer

Summarize long .txt narrative files into compressed, LLM-optimized summaries using BART. Choose between Bread, Butter, or both prompt styles for custom compression behavior. Upload a .txt file, select your preferences, and receive a clean, compressed summary in seconds.

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📚 Narrative Summarizer — Hugging Face Space

psyrishi/narrative-summarizer

A user-friendly summarization tool for .txt files, powered by Hugging Face Transformers and built with Gradio.

This app transforms long-form narratives into compressed, LLM-friendly summaries using either the "Bread", "Butter", or a combination of both prompt styles. It supports checkpointing to avoid data loss on interruptions and ensures large text files are processed reliably.

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✨ Features

• ✅ Supports .txt file uploads up to 3 MB (or more)
• 📌 Prompt options: Bread, Butter, or Bread and Butter
• 🔁 Multi-iteration summarization support
• 🧠 Model: facebook/bart-large-cnn
• 💾 Auto checkpointing: progress won't be lost on timeout
• 🧰 Output is saved for download post-processing
• 🌐 Clean Gradio UI – easy to run in browser

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📥 How to Use

1. Upload a .txt file (max ~3MB recommended)

2. Select a summarization style from dropdown:

   • Bread only
   • Butter only
   • Bread and Butter

3. Choose:

   • Iterations: how many times the prompts apply
   • Max Length: max summary tokens per chunk
   • Min Length: min summary tokens per chunk

4. Click Summarize

5. Get your condensed output in the results box

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⚙️ Tech Stack

Component	Details
Frontend	Gradio
Backend	Hugging Face transformers
Model	facebook/bart-large-cnn
Checkpointing	JSON-based resume system
Language	Python 3.10+

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📂 Folder Structure

.
├── app.py              # Gradio frontend app
├── summarizer.py       # Backend summarization logic
├── requirements.txt    # Dependencies
├── inputs/             # Uploaded input files
├── outputs/            # Final summarized outputs
└── checkpoints/        # Intermediate checkpointing

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🛠️ Setup (Local)

Clone this repo and run it locally:

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

pip install -r requirements.txt
python app.py

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🚀 Space Configuration

Here’s how to fill out the Hugging Face Space creation form:

Field	Value
Owner	psyrishi
Space Name	narrative-summarizer
Short Description	Summarizer for the txt files
License	Choose: MIT, Apache 2.0, or Other
Space SDK	✅ Gradio
Gradio Template	Start from Scratch or Blank
Hardware	✅ Free (sufficient for your use case)
Visibility	Choose: Public (recommended) or Private
Dev Mode	(Optional) Available to PRO subscribers

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🧪 Prompt Styles Explained

• 🥖 Bread: Focuses on compression for efficient LLM parsing
• 🧈 Butter: Enhances nuance and detail while summarizing
• 🥪 Bread + Butter: Applies both sequentially for balance

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📌 Example Input

Once upon a time, in a quiet village nestled between two mountains...

📤 Example Output (Bread only)

A peaceful mountain village faces hidden turmoil, gradually unveiling conflicts beneath its quiet surface.

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🔐 License

Recommend using:

MIT License

Copyright (c) 2025 psyrishi
Permission is hereby granted, free of charge, to any person obtaining a copy...

Or Apache 2.0.

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👋 Feedback & Contributions

Feel free to fork the repo, create pull requests, or open issues if you'd like to contribute or improve the tool.