OpenReader WebUI
Web-based text-to-speech document reader for EPUB, PDF, DOCX, MD and TXT
499 stars 70 forks last commit first released MIT
Actively maintained
Last commit 3 Jul 2026.
OpenReader WebUI is a web application that converts documents into spoken audio using pluggable text-to-speech providers. It supports EPUB, PDF, DOCX, Markdown and plain text files and provides a read-along experience with configurable narration and export options.
Key Features
- Supports EPUB, PDF, DOCX, MD and TXT document formats with in-page read-along highlighting
- Multi-provider TTS support (OpenAI-compatible endpoints, Deepinfra, Kokoro/Orpheus FastAPI and other OpenAI-style APIs)
- Word-by-word timestamps (optional) produced server-side for precise highlighting
- Smart sentence-aware narration to merge sentences across pages/chapters for smoother playback
- Audiobook export to m4b/mp3 with resumable, chapter-based generation and audio caching
- Local-first storage using Dexie/IndexedDB with optional server-side /docstore for shared documents
- Optimized Next.js TTS proxy that requests audio server-side and caches audio for repeat playback
- Theming and UI customization options with Tailwind-based interface
Use Cases
- Listen to ebooks and documents hands-free with synchronized read-along highlighting
- Produce downloadable audiobooks from personal document collections with chapter structure
- Integrate local or cloud TTS providers for accessible reading workflows and study aids
Limitations and Considerations
- Requires an accessible TTS API provider or compatible OpenAI-style endpoint; quality and latency depend on the chosen provider
- Word-level highlighting is optional and requires a separate whisper.cpp binary for timestamp generation
- DOCX conversion and some exports rely on external tooling (LibreOffice for DOCX, FFmpeg for m4b creation)
- Performance and parallel processing depend on available server hardware and TTS provider throughput
OpenReader WebUI is focused on flexible, high-quality TTS for documents with strong local-first behavior and configurable provider support. It is best suited for users who can provide or run a compatible TTS API and who need precise read-along and audiobook export features.
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