epub-to-manga

Convert EPUB novels into manga-style EPUBs using a local LLM for scene parsing and Stable Diffusion for image generation.

Disclaimer: This is a proof of concept. Your results may be dog water. ;3

How it works

1. Reads your EPUB and splits the text into scenes
2. Uses an Ollama LLM to parse each scene — extracting characters, dialogue, mood, and setting
3. Generates a manga-style illustration for each page via Stable Diffusion
4. Adds speech bubbles with character dialogue
5. Packages everything into a new EPUB

Requirements

• Python 3.10+
• Ollama running locally
• One of the following Stable Diffusion backends:
  • AUTOMATIC1111 stable-diffusion-webui
  • ComfyUI (recommended for Apple Silicon)
  • InvokeAI

Installation

pip install -r requirements.txt

Pull an Ollama model:

ollama pull llama3

Usage

python3 main.py book.epub
python3 main.py book.epub output.epub
python3 main.py book.epub --layout tiny --model mistral
python3 main.py book.epub --sd-url http://192.168.1.10:7860 --steps 30 --size 512x768
python3 main.py book.epub --dry-run

If no Stable Diffusion backend is running, the tool will detect any local installations and offer to launch or install one for you.

Options

Flag	Default	Description
--layout	normal	normal = 3 scenes/page, tiny = 1 scene/page
--model	llama3	Ollama model for scene parsing
--ollama-url	http://localhost:11434	Ollama API URL
--sd-url	http://127.0.0.1:7860	Stable Diffusion API URL
--sd-path	—	Path to SD install; auto-starts if not running
--steps	20	Diffusion steps per image (higher = better quality)
--style	lineart	lineart = clean outlines, manga = screentone shading
--size	768x1024	Output image dimensions
--workers	2	Parallel image generation workers
--hint	—	Character description, e.g. --hint "Rocky:alien who resembles a rock spider"
--jpeg-quality	85	EPUB image quality (1–95, lower = smaller file)
--dry-run [N]	—	Preview first N prompts without generating images
--verbose / -v	—	Enable debug logging

Configuration

Default URLs and model can be changed in config.py:

OLLAMA_URL = "http://localhost:11434/api/generate"
OLLAMA_MODEL = "llama3"
SD_API_URL = "http://127.0.0.1:7860/sdapi/v1/txt2img"

The tool saves its SD backend path to ~/.epub-to-manga so you don't need --sd-path on subsequent runs.

Resuming

Scene parsing and image generation both support resuming. Parsed scenes are cached to manga-<bookname>.cache.json, and generated page images are saved to <output>_pages/. Re-running the same command will pick up where it left off.

Project structure

epub-to-manga/
├── main.py                  # Entry point
├── config.py                # Default URLs and model
├── requirements.txt
├── core/
│   ├── epub_reader.py       # EPUB text extraction
│   └── scene_splitter.py    # Text → scenes
├── ai/
│   ├── llm_client.py        # Ollama API client
│   ├── scene_parser.py      # Scene → structured JSON
│   └── character_memory.py  # Character tracking across scenes
├── manga/
│   ├── prompt_builder.py    # SD prompt construction
│   ├── panel_layout.py      # Scene grouping into pages
│   └── speech_bubbles.py    # Dialogue overlay rendering
├── image/
│   ├── backend.py           # Backend router (A1111 / ComfyUI)
│   ├── a1111_api.py         # AUTOMATIC1111 API
│   ├── comfy_api.py         # ComfyUI API + workflow builder
│   ├── sd_launcher.py       # SD auto-start and install
│   └── device.py            # Device detection
├── export/
│   └── epub_builder.py      # Output EPUB assembly
└── utils/
    └── naming.py            # Output filename helpers