kikootwo
09cff5b68d
Introduce a per-user "ignored audiobooks" feature to suppress auto-requests. Changes include: - Database: add Prisma model IgnoredAudiobook and SQL migration to create ignored_audiobooks table with indexes and FK to users. - Backend: new API routes to list, add, delete, and check ignored audiobooks (/api/user/ignored-audiobooks, /check/:asin, /:id). Add annotateWithIgnoreStatus utility and integrate it into multiple audiobook list endpoints (popular, new-releases, category, search, authors, series). - Request creator: add ignore-list check (with sibling-ASIN expansion) and a bypassIgnore option for manual requests; return an 'ignored' reason when blocked. - Frontend: hooks (useIsIgnored, useToggleIgnore, useIgnoredList) and UI updates — AudiobookCard shows an "Ignored" indicator and AudiobookDetailsModal adds an ignore toggle and propagates local state changes. - Misc: adjust deduplication duration tolerance (to 5% / min 10 minutes), tweak SWR refresh intervals for shelves/syncing, and small logging/info updates. - Tests: add unit tests for request-creator ignore logic and update existing tests/mocks to account for ignore annotation; extend prisma test helper with ignoredAudiobook mock. This commit implements the ignore-list end-to-end (DB, server, client, and tests) so users can ignore specific ASINs and have auto-request flows respect that preference.
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