RLLM is an innovative RSS reader powered by Large Language Models (LLM), providing intelligent content analysis and summarization capabilities.
- ✅ Support for RSS 1.0, 2.0 and Atom feeds
- ✅ Article/Quote Reading and Collection
- ✅ AI Article Summary Generation
- ✅ AI Article Insight Analysis
- ✅ Daily Reading AI Summary
- ✅ Integrated with Anthropic, Deepseek and OpenAI
- 📝 Enhanced Collection Management
- 📝 Collection AI Summary
- 📝 Recent Reading Analysis
- 📝 Recent Reading Trends/Tags
See Development section for detailed instructions on building from source code.
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Download the latest unsigned IPA file from GitHub Actions (Latest successful build)
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Sign and install the IPA file using one of these methods:
- AltStore - Popular sideloading tool with automatic resigning
- Sideloadly - Cross-platform sideloading tool
- ESign - On-device signing tool
- TrollStore - Permanent app installation for iOS 14.0-15.4.1, 15.5beta4, and 16.0-16.6.1
- Scarlet - On-device app installer
- Your Apple Developer account and Xcode
- Enterprise certificate (if you have access)
Note: The IPA file is unsigned and requires signing before it can be installed on your device, except when using TrollStore on supported iOS versions.
- Xcode 15.0+
- iOS 17.0+
- Swift 5.0+
- Clone the repository
git clone https://github.com/DanielZhangyc/RLLM.git
cd RLLM- Open the project in Xcode
open RLLM.xcodeproj- Build and run the project in Xcode
We welcome contributions! Here's how you can help:
- Fork the repository
- Create a new branch (
git checkout -b feature/amazing-feature) - Make your changes
- Commit your changes (
git commit -m 'Write something here') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Need help? Feel free to:
- Open an issue
- Start a discussion
RLLM is a combination of "RSS" and "LLM", representing our goal of enhancing the RSS reading experience with AI capabilities.
Yes, you need to provide your own API keys for the LLM services you want to use. These can be configured in the app settings.
This project is licensed under the MIT License - see the LICENSE file for details.



