MediQuery is an AI-driven web application that helps users analyze and gain insights from medical reports. Leveraging state-of-the-art AI technologies such as Google Gemini, Pinecone, and a modern web stack with Next.js and Shadcn/ui, it allows users to upload PDFs or images of their medical reports and get precise, personalized insights through an interactive chat interface.
- 📄 Upload Medical Reports: Supports PDF and image uploads (JPG, PNG) for analysis.
- 💡 AI-Powered Insights: Uses Google's Gemini for vision capabilities to extract key information.
- 🧠 Chat with AI: Interactive chat interface to ask questions and receive insights.
- 🔍 RAG Model Integration: Combines knowledge retrieval with generative AI for accurate results.
- 🔒 Secure Data Handling: Advanced encryption ensures user data privacy.
- 🎨 Beautiful UI: Developed with Next.js and Shadcn/ui for a modern and responsive user interface.
Experience MediQuery in action: MediQuery Demo
To set up the project locally, follow these steps:
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Clone the repository:
git clone https://github.com/your-username/medical-report-analyzer.git
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Navigate to the project directory:
cd mediquery -
Running the Development Server
npm run dev
Open http://localhost:3000 in your browser to view the application. You can start making changes by editing the app/page.tsx file, and your updates will reflect instantly.
This project leverages next/font for optimized font loading, automatically integrating Inter, a custom Google Font, for improved typography.
To dive deeper into Next.js, check out these resources:
- Next.js Documentation - Explore Next.js features, APIs, and best practices.
- Interactive Next.js Tutorial - Follow an interactive tutorial to get hands-on experience with Next.js.
For more insights and to contribute, visit the Next.js GitHub repository - your feedback and contributions are always welcome!
The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.
Check out our Next.js deployment documentation for more details.
- Heartfelt thanks to all contributors who have helped shape MediQuery
- Special appreciation to our vibrant open-source community for their unwavering support
- Gratitude to the developers of the tools and libraries that power our platform
For inquiries, support, or collaboration opportunities, reach out to us:
We are committed to fostering an inclusive and respectful community. Please read our Code of Conduct before contributing.
This project is licensed under the MIT License. See the LICENSE file for details.