xFlawless11x
ba1efa88f5
Adds request_grabbed event that fires when a torrent/NZB is successfully handed off to the configured download client, filling the gap between request_approved (pre-search) and request_available (fully imported). - Add request_grabbed to NOTIFICATION_EVENTS with titleByRequestType (Audiobook Grabbed / Ebook Grabbed), info severity, Details messageLabel - Add NotificationEventConfig interface and update getEventMeta() return type to expose messageLabel to all providers without TypeScript errors - Add messageLabel: 'Reason' to issue_reported event - Fix all 4 providers (Discord, ntfy, Pushover, Apprise) to derive message field label from meta.messageLabel ?? 'Error' instead of hardcoded isIssue ternary — prevents grab details showing as Error - Trigger request_grabbed in download-torrent.processor.ts after client.addDownload() succeeds; message carries torrent title, indexer, and download client name; requestType sourced from request.type - Update notifications.md documentation Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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