📄🔊 OpenReader WebUI

OpenReader WebUI is an open source text to speech document reader web app built using Next.js, offering a TTS read along experience with narration for EPUB, PDF, TXT, MD, and DOCX documents. It supports multiple TTS providers including OpenAI, Deepinfra, and custom OpenAI-compatible endpoints like Kokoro-FastAPI and Orpheus-FastAPI

• 🎯 Multi-Provider TTS Support
  • Kokoro-FastAPI: Supporting multi-voice combinations (like af_heart+af_bella)
  • Orpheus-FastAPI
  • Custom OpenAI-compatible: Any TTS API with /v1/audio/voices and /v1/audio/speech endpoints
  • Cloud TTS Providers (requiring API keys)
    • Deepinfra: Kokoro-82M + models with support for cloned voices and more
    • OpenAI API (): tts-1, tts-1-hd, and gpt-4o-mini-tts w/ instructions
• 🛜 (Updated) Server-side Sync and Storage
  • (New) External Library Import enables importing documents to the browser's storage from a folder mounted on the server
  • (Updated) Sync documents between the browser and server to get them on other browsers or devices
• 🎧 Server-side Audiobook Export in m4b/mp3, with resumable, chapter-based export and regeneration
• 📖 Read Along Experience providing real-time text highlighting during playback (PDF/EPUB)
  • (New) Word-by-word highlighting uses word-by-word timestamps generated server-side with whisper.cpp (optional)
• 🧠 Smart Sentence-Aware Narration merges sentences across pages/chapters for smoother TTS
• 🚀 Optimized Next.js TTS Proxy with audio caching and optimized repeat playback
• 🎨 Customizable Experience
  • 🎨 Multiple app theme options
  • ⚙️ Various TTS and document handling settings
  • And more ...

🐳 Docker Quick Start

Prerequisites

• Recent version of Docker installed on your machine
• A TTS API server (Kokoro-FastAPI, Orpheus-FastAPI, Deepinfra, OpenAI, etc.) running and accessible

Note: If you have good hardware, you can run Kokoro-FastAPI with Docker locally (see below).

1. 🐳 Start the Docker container

Minimal (auth disabled, embedded storage is ephemeral, no library import):

docker run --name openreader-webui \
  --restart unless-stopped \
  -p 3003:3003 \
  -p 8333:8333 \
  ghcr.io/richardr1126/openreader-webui:latest

Fully featured (persistent storage, embedded SeaweedFS weed mini for documents, optional auth):

docker run --name openreader-webui \
  --restart unless-stopped \
  -p 3003:3003 \
  -p 8333:8333 \
  -v openreader_docstore:/app/docstore \
  -v /path/to/your/library:/app/docstore/library:ro \
  -e API_BASE=http://host.docker.internal:8880/v1 \
  -e API_KEY=none \
  -e BASE_URL=http://localhost:3003 \
  -e AUTH_SECRET=<paste_the_output_of_openssl_here> \
  ghcr.io/richardr1126/openreader-webui:latest

You can remove the /app/docstore/library mount if you don't need server library import. You can remove either BASE_URL or AUTH_SECRET to keep auth disabled.

Quick notes:

• API_BASE should point to your TTS API server's base URL (for local Docker Kokoro, use http://host.docker.internal:8880/v1).
• Expose -p 8333:8333 for direct browser access to embedded SeaweedFS presigned URLs.
• If port 8333 is not exposed, uploads still work via /api/documents/blob/upload/fallback.
• To enable auth, set both BASE_URL and AUTH_SECRET.

Docker networking and blob behavior (Click to expand)

Ports

• 3003 serves the OpenReader app and API routes.
• 8333 serves embedded SeaweedFS S3 for browser direct blob access.

Upload behavior

• Primary upload path: browser uploads to presigned URL from /api/documents/blob/upload/presign.
• Fallback upload path: /api/documents/blob/upload/fallback if direct upload fails.
• Content serving path: /api/documents/blob (server-served bytes/snippets).

Which Docker setup should I use? (Click to expand)

Goal	Recommended setup
Fast local setup, no persistence	Minimal docker run example
Persistent docs/audiobooks and optional auth	Fully featured docker run example with /app/docstore volume
Browser direct blob uploads/downloads	Publish both 3003 and 8333
Private blob endpoint (no 8333 published)	Keep using app APIs; uploads use fallback proxy when direct presigned upload is unreachable

Common Docker environment variables (Click to expand)

Variable	Purpose	Example / Notes
API_BASE	Default TTS API base URL (server-side)	http://host.docker.internal:8880/v1
API_KEY	Default TTS API key	none or your provider key
BASE_URL	Enables auth when set with AUTH_SECRET	External URL for this app, e.g. http://localhost:3003 or https://reader.example.com
AUTH_SECRET	Enables auth when set with BASE_URL	Generate with openssl rand -base64 32
AUTH_TRUSTED_ORIGINS	Extra allowed auth request origins	Comma-separated list; leave empty to trust only BASE_URL
POSTGRES_URL	Use Postgres for server DB (metadata + auth tables) instead of SQLite	If set, startup migrations target Postgres
GITHUB_CLIENT_ID	Optional GitHub OAuth sign-in	Requires GITHUB_CLIENT_SECRET
GITHUB_CLIENT_SECRET	Optional GitHub OAuth sign-in	Requires GITHUB_CLIENT_ID

Blob and embedded storage environment variables (Click to expand)

Variable	Purpose	Example / Notes
USE_EMBEDDED_WEED_MINI	Start SeaweedFS before app startup	default: true when unset in shared entrypoint
WEED_MINI_DIR	Data directory for embedded weed mini	default: docstore/seaweedfs
WEED_MINI_WAIT_SEC	Startup wait timeout for embedded weed mini	default: 20
S3_BUCKET	S3 bucket used for document blobs	default: openreader-documents in embedded mode
S3_REGION	S3 region used by AWS SDK	default: us-east-1 in embedded mode
S3_ENDPOINT	Custom endpoint for S3-compatible providers	default: http://<BASE_URL host>:8333 when BASE_URL is set, otherwise detected LAN host
S3_ACCESS_KEY_ID	S3 access key	auto-generated in embedded mode if unset
S3_SECRET_ACCESS_KEY	S3 secret key	auto-generated in embedded mode if unset
S3_FORCE_PATH_STYLE	Force path-style addressing	default: true in embedded mode
S3_PREFIX	Prefix for stored object keys	default: openreader

Docker volume mounts (Click to expand)

Mount	Type	Recommended	Purpose	Example
/app/docstore	Docker named volume	Yes (if you want persistence)	Persists embedded SeaweedFS blob data (docstore/seaweedfs), SQLite metadata DB (docstore/sqlite3.db when POSTGRES_URL is unset), audiobook export artifacts, and migration/runtime files	-v openreader_docstore:/app/docstore
/app/docstore/library	Bind mount (host folder)	Optional + :ro	Read-only source directory for Server Library Import; files are imported/copied into browser storage, not modified in place	-v /path/to/your/library:/app/docstore/library:ro

To import from the mounted library: Settings → Documents → Server Library Import

Note: Every file in the mounted library is imported into the client browser's storage. Keep the library reasonably sized to avoid performance issues.

Visit http://localhost:3003 to run the app and set your settings.

2. ⚙️ Configure the app settings in the UI

• Set the TTS Provider and Model in the Settings modal
• Set the TTS API Base URL and API Key if needed (more secure to set in env vars)
• Select your model's voice from the dropdown (voices try to be fetched from TTS Provider API)

3. ⬆️ Updating Docker Image

docker stop openreader-webui || true && \
docker rm openreader-webui || true && \
docker image rm ghcr.io/richardr1126/openreader-webui:latest || true && \
docker pull ghcr.io/richardr1126/openreader-webui:latest

🗣️ Local Kokoro-FastAPI Quick-start (CPU or GPU)

You can run the Kokoro TTS API server directly with Docker. We are not responsible for issues with Kokoro-FastAPI. For best performance, use an NVIDIA GPU (for GPU version) or Apple Silicon (for CPU version).

Kokoro-FastAPI (CPU)

docker run -d \
  --name kokoro-tts \
  --restart unless-stopped \
  -p 8880:8880 \
  -e ONNX_NUM_THREADS=8 \
  -e ONNX_INTER_OP_THREADS=4 \
  -e ONNX_EXECUTION_MODE=parallel \
  -e ONNX_OPTIMIZATION_LEVEL=all \
  -e ONNX_MEMORY_PATTERN=true \
  -e ONNX_ARENA_EXTEND_STRATEGY=kNextPowerOfTwo \
  -e API_LOG_LEVEL=DEBUG \
  ghcr.io/remsky/kokoro-fastapi-cpu:v0.2.4

Adjust environment variables as needed for your hardware and use case.

Kokoro-FastAPI (GPU)

docker run -d \
  --name kokoro-tts \
  --gpus all \
  --user 1001:1001 \
  --restart unless-stopped \
  -p 8880:8880 \
  -e USE_GPU=true \
  -e PYTHONUNBUFFERED=1 \
  -e API_LOG_LEVEL=DEBUG \
  ghcr.io/remsky/kokoro-fastapi-gpu:v0.2.4

Adjust environment variables as needed for your hardware and use case.

⚠️ Important Notes:

• For best results, set the -e API_BASE= for OpenReader's Docker to http://kokoro-tts:8880/v1
• For issues or support, see the Kokoro-FastAPI repository.
• The GPU version requires NVIDIA Docker support and works best with NVIDIA GPUs. The CPU version works best on Apple Silicon or modern x86 CPUs.

Local Development Installation

Prerequisites

• Node.js (recommended: use nvm)

• pnpm (recommended) or npm

  npm install -g pnpm
  

• A TTS API server (Kokoro-FastAPI, Orpheus-FastAPI, Deepinfra, OpenAI, etc.) running and accessible

• SeaweedFS weed binary (required)

  brew install seaweedfs
  

  Note: Verify install with weed version.

Optionally required for different features:

• FFmpeg (required for audiobook m4b creation only)

  brew install ffmpeg
  

• libreoffice (required for DOCX files)

  brew install libreoffice
  

• whisper.cpp (optional, required for word-by-word highlighting)

  # clone and build whisper.cpp (no model download needed – OpenReader handles that)
  git clone https://github.com/ggml-org/whisper.cpp.git
  cd whisper.cpp
  cmake -B build
  cmake --build build -j --config Release
  
  # point OpenReader to the compiled whisper-cli binary
  echo WHISPER_CPP_BIN=\"$(pwd)/build/bin/whisper-cli\"
  

  Note: The WHISPER_CPP_BIN path should be set in your .env file for OpenReader to use word-by-word highlighting features.

Steps

1. Clone the repository:

   git clone https://github.com/richardr1126/OpenReader-WebUI.git
   cd OpenReader-WebUI
   

2. Install dependencies:

   With pnpm (recommended):

   pnpm i # or npm i
   

3. Configure the environment:

   cp .env.example .env
   # Edit .env with your configuration settings
   

   Auth is recommended for contributors and is enabled when both values are set:

   • Set BASE_URL to your local URL (default: http://localhost:3003)

   • Generate a AUTH_SECRET and paste it into .env:

     openssl rand -base64 32
     

   • (Optional) If you use both localhost and LAN URL, set AUTH_TRUSTED_ORIGINS (leave empty to trust only BASE_URL):

     AUTH_TRUSTED_ORIGINS=http://localhost:3003,http://192.168.0.116:3003
     

   The embedded weed mini object store is enabled by default for local development, and started through the shared entrypoint. The ACCESS_KEY_ID and SECRET_ACCESS_KEY are auto-generated if unset, but for stable credentials across restarts, you can generate and set them in .env:

   • (Optional) Generate S3_ACCESS_KEY_ID and S3_SECRET_ACCESS_KEY and paste them into .env for stable credentials:

     S3_ACCESS_KEY_ID=<`openssl rand -hex 16`>
     S3_SECRET_ACCESS_KEY=<`openssl rand -hex 32`>
     

   • (Optional) Connect to external S3-compatible storage instead of embedded weed mini:

     USE_EMBEDDED_WEED_MINI=false
     
     # Required
     S3_BUCKET=your-bucket
     S3_REGION=us-east-1
     S3_ACCESS_KEY_ID=your-access-key
     S3_SECRET_ACCESS_KEY=your-secret-key
     
     # Optional / provider-specific
     S3_ENDPOINT=
     S3_FORCE_PATH_STYLE=
     S3_PREFIX=openreader
     

     Notes:

     • For AWS S3: usually leave S3_ENDPOINT empty and S3_FORCE_PATH_STYLE empty/false.
     • For MinIO/SeaweedFS/R2/B2 S3: set S3_ENDPOINT to your endpoint URL and set S3_FORCE_PATH_STYLE=true when required by that provider.

   Notes:

   • The base URL for the TTS API should be accessible and relative to the Next.js server

   • To disable auth, remove either BASE_URL or AUTH_SECRET.

   • If S3 credentials are unset, they are auto-generated per startup.

4. Run DB migrations:

   • Production / Docker: Migrations run automatically on startup via pnpm start.

   • Development: When using pnpm dev, it needs to be run explicitly:

     pnpm migrate
     

   Note: If you set POSTGRES_URL in .env, migrations will target Postgres instead of local SQLite.

   Generating migrations (contributors):

   • pnpm generate generates migrations for both SQLite and Postgres (requires POSTGRES_URL).

   Manual Drizzle Kit runs:

   • SQLite migrate: npx drizzle-kit migrate --config drizzle.config.sqlite.ts
   • Postgres migrate: npx drizzle-kit migrate --config drizzle.config.pg.ts
   • SQLite generate: npx drizzle-kit generate --config drizzle.config.sqlite.ts
   • Postgres generate: npx drizzle-kit generate --config drizzle.config.pg.ts

5. Start the development server:

   With pnpm (recommended):

   pnpm dev # or npm run dev
   

   or build and run the production server:

   With pnpm:

   pnpm build # or npm run build
   pnpm start # or npm start
   

   Visit http://localhost:3003 to run the app.

💡 Feature requests

For feature requests or ideas you have for the project, please use the Discussions tab.

🙋‍♂️ Support and issues

If you encounter issues, please open an issue on GitHub following the template (which is very light).

👥 Contributing

Contributions are welcome! Fork the repository and submit a pull request with your changes.

❤️ Acknowledgements

This project would not be possible without standing on the shoulders of these giants:

• Kokoro-82M model
• Kokoro-FastAPI
• Better Auth
• SQLite
• PostgreSQL
• SeaweedFS (weed mini)
• whisper.cpp
• ffmpeg
• react-pdf npm package
• react-reader npm package

Docker Supported Architectures

• linux/amd64 (x86_64)
• linux/arm64 (Apple Silicon, Raspberry Pi, SBCs, etc.)

Stack

• Framework: Next.js 15 (App Router), React 19, TypeScript
• Containerization / Runtime: Docker (linux/amd64 + linux/arm64), with a shared entrypoint that can bootstrap embedded SeaweedFS before app startup
• Next.js Client:
  • UI: Tailwind CSS, Headless UI, @tailwindcss/typography
  • Interactions: react-dnd, react-dropzone
  • Authentication: Better Auth client SDK (better-auth/react, anonymous client plugin)
  • Local storage/cache: Dexie.js (IndexedDB) for documents, cache, and app settings
  • Document rendering:
    • PDF: react-pdf, pdf.js
    • EPUB: react-reader, epubjs
    • Markdown/Text: react-markdown, remark-gfm
  • Text preprocessing / matching: compromise, cmpstr
• Next.js Server:
  • APIs: Next.js Route Handlers for document sync, blob/content access, migration flows, audiobook export, and TTS/Whisper proxying
  • Authentication: Better Auth server handlers/adapters for session and auth routing
  • Text preprocessing / NLP utilities: compromise via shared lib/nlp helpers used in server processing paths
  • Metadata database: Drizzle ORM, SQLite (better-sqlite3) by default, optional PostgreSQL (pg)
  • Blob/object storage: embedded SeaweedFS (weed mini) by default, or external S3-compatible storage via AWS SDK v3 (@aws-sdk/client-s3, presigned URLs, upload fallback proxy)
  • Audio/processing pipeline: OpenAI-compatible TTS providers (OpenAI, DeepInfra, Kokoro, Orpheus, custom), ffmpeg for audiobook assembly, optional whisper.cpp for word-level timestamps
• Tooling / Testing: ESLint, TypeScript, Playwright end-to-end tests, and Drizzle migrations/generation scripts

License

This project is licensed under the MIT License.