omnigram

About Omnigram

Omnigram is a multi-platform (iOS, Android, Web, Windows, Linux, Mac) file reading and audiobook client written in Flutter. It supports multiple formats, including EPUB and PDF. It provides audiobook functionality through TTS models and supports other AI models for assisted reading. In addition, it has local book management capabilities, allowing users to easily manage book storage on NAS. For its backend service deployment, refer to omnigam-server. Or check the official project documentation.

Features

• Supports iOS and Android for EPUB ebook reading
• Supports TTS text-to-speech, allows custom TTS engines
• Supports local book management (NAS), including searching, reading, listening, notes, favorites, downloading, deleting books, settings, etc.
• Supports conversational assistant with Markdown support, code block highlighting, conversation settings
• Books support TTS reading using models
• Supports PDF, documents and other NAS content services management
• Supports Web, Windows, Linux, Mac

Omnigram Infrastructure

Official Documentation

You can find the official documentation (including installation manuals) at https://omnigram.lxpio.com/.

Examples

For the mobile app, you can use https://omnigram-demo.lxpio.com:9443 for the Server Endpoint URL

The credential
email: admin
password: 123456

For Dev

This project uses a three-way repository including:

• riverpod
• isar

Build

For Omnigram APP

git clone github.com/lxpio/omnigram.git
cd omnigram/app
make

For Omnigram Server

git clone github.com/lxpio/omnigram.git
cd omnigram/server
make 

# make docker 

TTS Service

When the current App supports the FishTTS API Server, refer to FishTTS.

git clone https://github.com/fishaudio/fish-speech.git
cd fish-speech

pip install -e .
python -m tools.api_server --listen 0.0.0.0:8999 --llama-checkpoint-path "checkpoints/fish-speech-1.5" --decoder-checkpoint-path "checkpoints/fish-speech-1.5/firefly-gan-vq-fsq-8x1024-21hz-generator.pth"

Acknowledgments

This project makes extensive use of code from Immich, and we thank them for their open-source contributions.

The creation of this project utilized three libraries, including:

• riverpod
• isar
• fish-speech

License

This project is licensed under the MIT License - see the LICENSE.md file for details