--- title: "Multi-Agent-Medical-Assistant" type: "tool" slug: "souvikmajumder26-multi-agent-medical-assistant" canonical_url: "https://www.graphcanon.com/tools/souvikmajumder26-multi-agent-medical-assistant" github_url: "https://github.com/souvikmajumder26/Multi-Agent-Medical-Assistant" homepage_url: null stars: 924 forks: 204 primary_language: "Python" license: "Apache-2.0" categories: ["model-training", "evaluation-observability", "data-retrieval", "speech-audio", "computer-vision", "llm-frameworks", "inference-serving", "ai-agents", "developer-tools", "vector-databases"] tags: ["agents", "disease-detection", "generative-ai", "agentic-ai", "genai-chatbot", "chatbot", "agent", "computer-vision"] updated_at: "2026-07-07T18:48:44.933907+00:00" --- # Multi-Agent-Medical-Assistant > ⚕️ Multi-Agent-Medical-Assistant: AI-powered multi-agentic system for medical diagnosis and assistance A Python-based repository housing a multi-agent, genAI-driven medical diagnostic chatbot aimed at healthcare professionals and patients. It leverages large language models (LLMs), computer vision techniques, RAG with vector databases, real-time web search capabilities, and human-in-the-loop validations for robust medical diagnosis and research. ## Facts - Repository: https://github.com/souvikmajumder26/Multi-Agent-Medical-Assistant - Stars: 924 · Forks: 204 · Open issues: 3 · Watchers: 13 - Primary language: Python - License: Apache-2.0 - Last pushed: 2025-05-03T04:43:30+00:00 ## Categories - [Model Training](/categories/model-training.md) - [Evaluation & Observability](/categories/evaluation-observability.md) - [Data & Retrieval](/categories/data-retrieval.md) - [Speech & Audio](/categories/speech-audio.md) - [Computer Vision](/categories/computer-vision.md) - [LLM Frameworks](/categories/llm-frameworks.md) - [Inference & Serving](/categories/inference-serving.md) - [AI Agents](/categories/ai-agents.md) - [Developer Tools](/categories/developer-tools.md) - [Vector Databases](/categories/vector-databases.md) ## Tags agents, disease-detection, generative-ai, agentic-ai, genai-chatbot, chatbot, agent, computer-vision ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [JavaGuide](/tools/snailclimb-javaguide.md) - Snailclimb/JavaGuide: 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发 (★ 156,863) - [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,298) ## README (excerpt) ```text

⚕️ Multi-Agent-Medical-Assistant :
AI-powered multi-agentic system for medical diagnosis and assistance

---- > [!IMPORTANT] > 📋 Version Updates from v2.0 to v2.1 and further: > 1. **Document Processing Upgrade**: Unstructured.io has been replaced with Docling for document parsing and extraction of text, tables, and images to be embedded. > 2. **Enhanced RAG References**: Links to source documents and reference images present in reranked retrieved chunks stored in local storage are added to the bottom of the RAG responses. > > To use Unstructured.io based solution, refer release - [v2.0](https://github.com/souvikmajumder26/Multi-Agent-Medical-Assistant/tree/v2.0). ## 📚 Table of Contents - [Overview](#overview) - [Demo](#demo) - [Technical Flow Chart](#technical-flowchart) - [Key Features](#key-features) - [Tech Stack](#technology-stack) - [Installation and Setup](#installation-setup) - [Using Docker](#docker-setup) - [Manual Installation](#manual-setup) - [Usage](#usage) - [Contributions](#contributions) - [License](#license) - [Citing](#citing) - [Contact](#contact) ---- ## 📌 Overview The **Multi-Agent Medical Assistant** is an **AI-powered chatbot** designed to assist with **medical diagnosis, research, and patient interactions**. 🚀 **Powered by Multi-Agent Intelligence**, this system integrates: - **🤖 Large Language Models (LLMs)** - **🖼️ Computer Vision Models** for medical imaging analysis - **📚 Retrieval-Augmented Generation (RAG)** leveraging vector databases - **🌐 Real-time Web Search** for up-to-date medical insights - **👨‍⚕️ Human-in-the-Loop Validation** to verify AI-based medical image diagnoses ### **What You’ll Learn from This Project** 📖 🔹 **👨‍💻 Multi-Agent Orchestration** with structured graph workflows 🔹 **🔍 Advanced RAG Techniques** – hybrid retrieval, semantic chunking, and vector search 🔹 **⚡ Confidence-Based Routing** & **Agent-to-Agent Handoff** 🔹 **🔒 Scalable, Production-Ready AI with Modularized Code & Robust Exception Handling** 📂 **For learners**: Check out [`agents/README.md`](agents/README.md) for a **detailed breakdown** of the agentic workflow! 🎯 --- ## 💫 Demo https://github.com/user-attachments/assets/d27d4a2e-1c7d-45e2-bbc5-b3d95ccd5b35 If you like what you see and would want to support the project's developer, you can Buy Me A Coffee ! :) 📂 **For an even more detailed demo video**: Check out [`Multi-Agent-Medical-Assistant-v1.9`](assets/Multi-Agent-Medical-Assistant-v1.9_Compressed.mp4). 📽️ --- ## 🛡️ Technical Flow Chart --- ## ✨ Key Features - 🤖 **Multi-Agent Architecture** : Specialized agents working in harmony to handle diagnosis, information retrieval, reasoning, and more - 🔍 **Advanced Agentic RAG Retrieval System** : - Docling based parsing to extract text, tables, and images from PDFs. - Embedding markdown formatted text, tables and LLM based image summaries. - LLM based semantic chunking with structural boundary awareness. - LLM based query expansion with related medical domain terms. - Qdrant hybrid search combining BM25 sparse keyword search along with dense embedding vector search. - HuggingFace Cross-Encoder based reranking of retrieved document chunks for accurate LLM reponses. - Input-output guardrails to ensure safe and relevant responses. - Links to source documents and images present in reference document chunks ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/souvikmajumder26-multi-agent-medical-assistant`](/api/graphcanon/tools/souvikmajumder26-multi-agent-medical-assistant) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_