Warning

Phlox is an experimental project. For full details on limitations and risks, please read the Usage Warning section carefully before proceeding.

Phlox is an open-source patient management system integrating AI-powered medical transcription, clinical note generation, and an AI chatbot interface. It's designed to run locally, utilizing local models for inference and transcription.

Key Features ✨

• 🔒 100% Local & Private: Runs entirely on your machine with no third-party services - all data stays local. Free and open source forever; the security of your data is in your hands.
• 🖥️ Desktop App: Native Apple Silicon application with bundled LLM and transcription servers - no external dependencies required.
• 🎤 AI Medical Transcription & Summarization: Convert patient encounters to structured clinical notes using customizable templates.
• 📝 Flexible Template System: Structure clinical notes to your preferences, with versioning and automated template generation from example notes.
• ✅ Task Manager: Parse clinical plans into actionable task lists with AI-generated summaries.
• ✉️ Correspondence Generation: One-click generation of patient letters based on clinical notes.
• 🤖 AI-chat/RAG: Reference tool to query medical guidelines, literature, and documentation backed by a local knowledge base (ChromaDB).
• 💡 Adaptive Refinement: Outputs improve the more you use it; Phlox learns from your previous notes.
• 📰 Dashboard with RSS Reader: Stay updated with LLM-summarized articles from medical RSS feeds.

Stack 🛠️

• Frontend: Chakra UI (React/Vite)
• Backend: FastAPI (Python/uv)
• Database: SQLCipher
• Desktop Wrapper: Tauri (Rust)
• LLM Backend: Ollama, OpenAI-compatible endpoints, or bundled llama.cpp server
• Transcription: Whisper-compatible endpoints or bundled whisper.cpp server
• RAG: ChromaDB

Quick Start 🚀

Desktop App (Apple Silicon)

Pre-built Apple Silicon binaries are available from GitHub Releases.

Note: The desktop app provides transcription and correspondence features only. For extended reference tools (Chat, RAG, PDF Upload), use the Docker/Podman deployment below.

Docker/Podman (Extended Reference Tools)

1. Prerequisites: Podman/Docker, Ollama/OpenAI-compatible endpoint, Whisper endpoint.
2. Hardware Requirements: For reasonable performance, a GPU (CUDA, ROCm) or Apple M-Series chip is strongly recommended. Without these, especially with larger models, the system will run extremely slowly.
3. Clone: git clone https://github.com/bloodworks-io/phlox.git && cd phlox
4. Build: docker build -t phlox:latest .
5. Environment: Create .env in phlox/ (see example in documentation).
6. Run: docker-compose up (Production) or docker-compose -f docker-compose.dev.yml up (Development).
7. Access: http://localhost:5000

For detailed setup, feature explanations, and important warnings, please see the Documentation.

Deployment Options

Docker/Podman (Extended Reference Tools)

The complete Phlox experience with all features:

• Medical transcription and clinical notes
• Correspondence generation
• AI Chat interface
• RAG/document knowledge base
• Dashboard with RSS reader

Desktop App (Streamlined)

Native desktop application for Apple Silicon:

• Medical transcription and clinical notes
• Correspondence generation
• Bundled llama.cpp and whisper servers - no external dependencies
• All data stored locally. Nothing leaves your machine.

Additional platforms and full feature parity coming in future releases.

Roadmap 🗺️

Here's what's coming next for Phlox:

• Use structured JSON outputs for managing LLM responses
• Add support for OpenAI-compatible endpoints
• Tauri desktop app with local inference (llama.cpp + whisper bundled)
• MCP server support for custom tools and agentic workflows
• Advanced template version control
• Meeting and multi-disciplinary meeting scribing

Usage Warning ⚠️

Phlox is an experimental project intended for educational and personal use. It is not a certified medical device and should NOT be used for clinical decision-making.

Phlox is not suitable for production deployment in the form provided in this repo. If you intend to use it in a clinical setting, you are responsible for ensuring compliance with local applicable regulations (HIPAA, GDPR, TGA, etc.)

AI outputs can be unreliable. Always verify AI-generated content and use professional clinical judgment. The application displays a disclaimer on startup with full details.

Security note: The Docker deployment binds to 0.0.0.0 by default and has no authentication. You MUST place it behind a reverse proxy with an authentication layer like Authelia. The desktop app requires a passphrase to unlock the encrypted database.

License 📄

MIT License

Contributing 🤝

Contributing Guidelines