Rewrite Studio

Small Streamlit app for rewriting and summarizing text with the OpenAI API.

The goal of this project is to show how I structure a simple AI feature:

• separate prompts, service layer, and UI
• keep API secrets in a local .env file
• present a clean, minimal interface

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Preview

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Tech Stack

• Python 3.10
• Streamlit for UI rendering
• OpenAI API for rewrite and summary generation
• Modular service layer for clean separation of logic
• Environment variables for API security

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Features

• Rewrite text into a target tone:

  • Friendly
  • Confident
  • Concise
  • Playful

• Summarize text into:

  • Short summary
  • Medium summary
  • Detailed summary

• Streamlit front end with a two column layout

• Uses the official OpenAI Python SDK

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Getting started

Clone the repo

git clone https://github.com/Dhudson-AI/rewrite-studio.git
cd rewrite-studio

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Environment setup

Create a virtual environment:

python -m venv venv

Activate it on macOS or Linux:

source venv/bin/activate

Activate it on Windows:

venv\Scripts\activate

Install dependencies:

pip install -r requirements.txt

Create your environment file:

cp .env.example .env

Add your OpenAI API key inside the new .env file.

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Running the app

streamlit run app.py

This opens Rewrite Studio in your browser.
Paste text into the left column.
Choose a tone or summary type.
View the rewritten output on the right.

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Project structure

rewrite-studio/
│
├── app.py
├── services/
│   ├── tone_rewriter.py
│   ├── summarizer.py
│   ├── client.py
├── ui/
│   ├── layout.py
│   ├── components.py
├── .env.example
├── requirements.txt
└── README.md

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Architecture

The project follows a simple separation of concerns.

• The ui folder handles layout and presentation
• The services folder contains prompt templates and API logic
• The client module manages model configuration and request handling

Tone rewriting uses structured prompts for clarity and consistency.
Summaries use proportional compression to preserve important ideas.

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Why this project exists

Rewrite Studio demonstrates practical skills required for real AI powered features:

• Designing clear and controlled prompts
• Organizing a small but complete codebase
• Handling environment variables securely
• Creating a minimal and functional UI
• Writing code that can be extended without major rewrites

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Future extensions

Possible improvements:

• Additional tone options
• More summary modes
• Export rewritten text as PDF or Markdown
• History view for previous rewrites
• Light authentication support

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Requirements

• Python 3.10 or newer
• Streamlit
• OpenAI Python SDK
• python-dotenv

All dependencies are listed in requirements.txt.

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License

MIT License. You may use or modify this project with attribution.

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Contact

Created by Dillon Hudson
GitHub profile: https://github.com/Dhudson-AI