SV-MedVision Pro: Agentic Multi-modal Grounding for Autonomous Radiology 🏥

Advanced Multi-Agent Clinical Diagnostic System

Developed by: Rashedul Albab
GitHub: rashedulalbab253
Docker Hub: rashedulalbab1234

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🌟 Overview

SV-MedVision Pro is a high-performance, full-stack medical AI platform designed for automated diagnostic imaging analysis. It utilizes a Multi-Agent Orchestration architecture to provide grounded, verified clinical reports from X-rays, MRIs, and CT scans.

🔬 Key Features

• Agentic Diagnostic Team: A collaborative hierarchy consisting of a Lead Radiologist and a specialized Medical Researcher.
• Real-Time Clinical Grounding: Uses RAG to consult 2024-2025 clinical literature (PubMed, Mayo Clinic) before finalizing reports.
• Flash Inference: Powered by Groq LPUs (Llama 4 Scout) for near-instant analysis.
• Professional PDF Export: Generates timestamped, clinical-grade reports automatically.
• Modern UI: A premium 'Midnight Cyber' dashboard built for professional clinical environments.

🏗️ Architecture

• Backend: FastAPI (Python)
• AI Framework: Agno (Phidata)
• Frontend: High-fidelity HTML5/CSS3/Vanilla JS
• Containerization: Docker & GitHub Actions CI/CD

🚀 Getting Started

Local Setup

1. Clone the repository
2. Install dependencies:

   pip install -r requirements.txt

3. Run the Backend:

   uvicorn backend.main:app --reload

4. Access the UI: Open http://localhost:8000

Docker Setup

docker pull rashedulalbab1234/sv-medvision-pro:latest
docker run -p 8000:8000 rashedulalbab1234/sv-medvision-pro:latest

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Research Interest: Multi-modal AI & Clinical Safety.*