# 🚀 **OpenHealth** **AI Health Assistant | Powered by Your Data, Running Locally** ### 🌍 Choose Your Language [English](README.md) | [Français](i18n/readme/README.fr.md) | [Deutsch](i18n/readme/README.de.md) | [Español](i18n/readme/README.es.md) | [한국어](i18n/readme/README.ko.md) | [中文](i18n/readme/README.zh.md) | [日本語](i18n/readme/README.ja.md) ## 🌟 Overview > OpenHealth helps you **take charge of your health data**. By leveraging AI and your personal health information, OpenHealth provides a private and locally-run assistant that helps you better understand and manage your health. ## ✨ Project Features Core Features - 📊 **Centralized Health Data Input:** Easily consolidate all your health data in one place. - 🛠️ **Smart Parsing:** Automatically parses your health data and generates structured data files. - 🤝 **Contextual Conversations:** Use the structured data as context for personalized interactions with GPT-powered AI. ## 📥 Supporting Data Sources & Language Models Data Sources You Can Add Supported Language Models • Blood Test Results • Health Checkup Data • Personal Physical Information • Family History • Symptoms • LLaMA • DeepSeek-V3 • GPT • Claude • Gemini ## 🤔 Why We Built OpenHealth > - 💡 **Your health is your responsibility.** > - ✅ True health management combines **your data** + **intelligence**, turning insights into actionable plans. > - 🧠 AI acts as an unbiased tool to guide and support you in managing your long-term health effectively. ## 🗺️ Project Diagram ```mermaid graph LR subgraph Health Data Sources A1[Clinical RecordsBlood Tests/Diagnoses/Prescriptions/Imaging] A2[Health PlatformsApple Health/Google Fit] A3[Wearable DevicesOura/Whoop/Garmin] A4[Personal RecordsDiet/Symptoms/Family History] end subgraph Data Processing B1[Data Parser & Standardization] B2[Unified Health Data Format] end subgraph AI Integration C1[LLM ProcessingCommercial & Local Models] C2[Interaction MethodsRAG/Cache/Agents] end A1 & A2 & A3 & A4 -- B1 B1 -- B2 B2 -- C1 C1 -- C2 style A1 fill:#e6b3cc,stroke:#cc6699,stroke-width:2px,color:#000 style A2 fill:#b3d9ff,stroke:#3399ff,stroke-width:2px,color:#000 style A3 fill:#c2d6d6,stroke:#669999,stroke-width:2px,color:#000 style A4 fill:#d9c3e6,stroke:#9966cc,stroke-width:2px,color:#000 style B1 fill:#c6ecd9,stroke:#66b399,stroke-width:2px,color:#000 style B2 fill:#c6ecd9,stroke:#66b399,stroke-width:2px,color:#000 style C1 fill:#ffe6cc,stroke:#ff9933,stroke-width:2px,color:#000 style C2 fill:#ffe6cc,stroke:#ff9933,stroke-width:2px,color:#000 classDef default color:#000 ``` > **Note:** The data parsing functionality is currently implemented in a separate Python server and is planned to be migrated to TypeScript in the future. ## Getting Started ## ⚙️ How to Run OpenHealth Installation Instructions 1. **Clone the Repository:** ```bash git clone https://github.com/OpenHealthForAll/open-health.git cd open-health ``` 2. **Setup and Run:** ```bash # Copy environment file cp .env.example .env # Start the application using Docker Compose docker compose --env-file .env up ``` 3. **Access OpenHealth:** Open your browser and navigate to `http://localhost:3000` to begin using OpenHealth. > **Note:** If youre using Ollama with Docker, make su
