OncoAgent: High-Precision Medical System

OncoAgent is an open-source, multi-agent AI system designed for clinical oncology triage. It safely cross-references complex patient histories against official medical guidelines. Here is a concise breakdown of its core architecture: 1. Hardware-Optimized Foundation Built exclusively for AMD Instinct MI300X accelerators (ROCm), it leverages vLLM to power a dual-tier setup of Qwen models (9B/27B), ensuring high-throughput, low-latency clinical inference. 2. Multi-Agent Orchestration (LangGraph) A stateful workflow replaces monolithic prompting. A Router Agent sanitizes input (stripping private data via a Zero-PHI policy), a Specialist Agent analyzes the case, and a Critic Agent runs a Reflexion loop to verify the medical accuracy of the output before it reaches the user. 3. Advanced Medical RAG The engine ingests NCCN and ESMO oncology guidelines using Adaptive Semantic Chunking (splitting by medical headers, not arbitrary characters). It uses local vector databases (ChromaDB/FAISS) and exposes retrieval confidence metrics directly in the UI for full transparency. 4. Strict Safety Policies To prevent dangerous AI behavior, OncoAgent enforces a strict Anti-Hallucination Policy. If a treatment isn't explicitly found in the retrieved guidelines, the system must state: "Information inconclusive in the provided guidelines." 5. Deployment & UI Modular and fully Dockerized for seamless deployment (e.g., Hugging Face Spaces), it features a professional Gradio UI that focuses on clinical usability, fast response times, and clear, structured results.