Add support for selecting individual audio files during manual and bulk imports and pass that selection through the scan, API, job queue, processor and organizer. Key changes: - API: scan now returns audioFiles for each discovered book and emits a new 'grouping' progress phase; execute and manual-import routes accept file lists (audioFiles / selectedFiles) and validate them. - Scanner: group loose audio files by metadata (title/author/narrator), deduplicate multi-part sets (CD1/CD2) across folders, and return audioFiles + groupingKey; add concurrency limit for ffprobe reads and merge groups post-scan. - Job queue & processor: OrganizeFiles payload now includes selectedFiles; processors forward selectedFiles to the FileOrganizer and to cleanup logic. - File organizer & cleanup: filter to only selectedFiles when organizing; cleanup now deletes only the selected files (if provided) instead of removing the whole directory. - UI: Manual import browser and bulk import wizard updated to show per-file selection, track checkedFiles, toggle all, and send selected files to the API; ConfirmPhase updated to allow checking/unchecking files and prevents starting import with no files selected. - Filesystem browse: removed expensive per-subfolder stats to keep browsing responsive (now lists subdirectories without nested stat calls). Overall this change enables finer-grained imports, reduces accidental deletion of unselected files, and improves scan grouping for multi-folder audiobooks.
Audiobook automation for Plex and Audiobookshelf
Radarr/Sonarr + Overseerr for audiobooks, all in one
Features • Setup • Screenshots • Discord
What is this?
You run Plex or Audiobookshelf with audiobooks. You want more audiobooks. You search indexers, download torrents or NZBs, organize files, wait for your server to scan. ReadMeABook does all of that automatically.
Request a book → Prowlarr searches → qBittorrent or SABnzbd downloads → Files organized → Library imports. Done.
Also includes BookDate: AI recommendations with a Tinder-style swipe interface. Swipe right to request.
User friendly audible-backed searches, multi-file chapter merging, e-book sidecar support, OIDC OAuth, admin approval workflows, and more.
Features
- Plex or Audiobookshelf
- Torrents via qBittorrent
- Usenet via SABnzbd
- Prowlarr for indexer search (torrents + NZBs)
- BookDate: AI recommendations (OpenAI/Claude/Local) with swipe interface
- Chapter merging: Multi-file downloads → single M4B with chapters
- E-book sidecar: Optional EPUB/PDF downloads from Shadow Library
- Request approval: Admin approval workflow for multi-user setups
- Setup wizard: Step-by-step guided config with connection testing
Setup
Prerequisites: Docker, Plex or Audiobookshelf, qBittorrent or SABnzbd, Prowlarr
Quick Start
# Download docker-compose.yml
curl -fsSL https://raw.githubusercontent.com/kikootwo/readmeabook/main/docker-compose.yml -o docker-compose.yml
# Start the container
docker compose up -d
Open http://localhost:3030 and follow the setup wizard.
Manual Setup
If you prefer to customize the compose file:
services:
readmeabook:
image: ghcr.io/kikootwo/readmeabook:latest
container_name: readmeabook
restart: unless-stopped
ports:
- "3030:3030"
volumes:
- ./config:/app/config
- ./cache:/app/cache
- ./downloads:/downloads # Your download client's path
- ./media:/media # Your audiobook library
- ./pgdata:/var/lib/postgresql/data
- ./redis:/var/lib/redis
environment:
PUID: 1000 # Optional: your user ID
PGID: 1000 # Optional: your group ID
PUBLIC_URL: "https://audiobooks.example.com" # Required for OAuth
Then run docker compose up -d to start.
Important: Your download client (qBittorrent/SABnzbd) and RMAB must see files at the same path. See the Volume Mapping Guide if downloads aren't being detected.
Screenshots
Community
Join the Discord: https://discord.gg/kaw6jKbKts
Feature and fix Contributions are highly welcome. Documentation in documentation/ if you want to contribute. Discord is a great place to ask questions!
Support
If you find this project useful, consider supporting development via GitHub Sponsors or Ko-fi.
If you'd like to support but cannot sponsor, a simple star on the GitHub repo is also greatly appreciated!
Built with AI Assistance
This is a human-engineered application. Architecture, design decisions, code review, and project direction are managed by a principal engineer with nearly 15 years of professional software development experience.
AI tools (Claude, GitHub Copilot) serve as force multipliers. Accelerating implementation, maintaining consistency, and handling boilerplate, while human expertise drives the technical vision. This mirrors how AI assistance is used at leading technology companies today.
The workflow:
- Token-optimized documentation system designed for AI consumption (CLAUDE.md)
- Structured navigation enabling AI to find relevant context without reading entire codebases
- Consistent architectural patterns that AI tools can follow and extend
- Human review of all AI-generated code before merge
The result: enterprise-grade velocity on a solo project without sacrificing code quality or architectural integrity.
AGPL v3 License
