📚 Automated Book Publication Workflow 📚

A Python-based AI-driven system for automating the workflow of fetching, paraphrasing, reviewing, editing, and versioning book chapters — with human-in-the-loop controls and intelligent retrieval using reinforcement learning-inspired scoring.

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📌 Project Objective

The goal of this project is to build an Automated Book Publication Software-as-a-Service (SaaS) pipeline that:

• Scrapes chapter content and screenshots from public web sources.
• Applies AI paraphrasing (text spinning) and content review.
• Provides a human-in-the-loop Streamlit-based editor for final modifications.
• Stores multiple content versions in ChromaDB with metadata.
• Uses a reward scoring system (RL-inspired) to retrieve the best content version.

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🚀 Core Features

• 📖 Chapter Scraping & Screenshots — Using Playwright for automated data extraction.
• ✍️ AI Writing (Spin Writer) — Generates alternative phrasing via LLM APIs (Gemini / Ollama / Open Source).
• 📝 AI Content Review — Feedback on content quality and readability.
• 👨‍💻 Human-in-the-Loop Editor — Streamlit UI for manual editing and approval.
• 🗂️ Version Control with ChromaDB — Track each saved content version with metadata.
• 🏆 Reinforcement Learning-inspired Search — Reward scoring to pick the best version automatically.
• 🎛️ Modular & Scalable Python Codebase — Easy to extend for additional features.

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🖼️ Screenshots & Demo

Video:

Dashboard Editor:

AI Rephrase Preview:

Short Demo GIF:

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🛠️ Tech Stack

• Python 3.11+
• Playwright — for web scraping & screenshots
• Gemini API / Ollama — for AI writing (LLMs)
• Streamlit — human-in-the-loop UI
• ChromaDB — content version storage & retrieval
• Reinforcement Learning-inspired Reward Scoring — for best version selection
• Pandas, Matplotlib — for data handling and visualization

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📦 Installation & Local Setup

1️⃣ Clone this repository:

git clone https://github.com/saifmukadam10/automated-book-publication-saas.git
cd automated-book-publication-saas

2️⃣ Create a virtual environment and install dependencies:
python -m venv .venv
source .venv/bin/activate    # (Linux/Mac)
.venv\Scripts\activate       # (Windows)

pip install -r requirements.txt

3️⃣ Run the Streamlit app:
streamlit run rl_search/dashboard_app.py

4️⃣ Open the app in your browser:
http://localhost:8501

📧 Contact

👤 Saif Mukadam
📍 Computer Science Engineer (AI & ML) at M.H. Saboo Siddik College of Engineering
🔗 [LinkedIn](https://www.linkedin.com/in/saif-mukadam-10m)
📧 +91 9619133704
📧 [mukadamsaif9@gmail.com](mailto:mukadamsaif9@gmail.com)