Multi-Agent Avatar Accelerator

The Multi-Agent Avatar Accelerator is a robust conversational AI framework and toolkit designed for architects, developers, and enterprises building intelligent, interactive conversational experiences through sophisticated multi-agent systems. This solution integrates advanced technologies such as Agentic AI, Semantic Kernel, Azure OpenAI, Azure Document Intelligence, Azure Cosmos DB, and Azure Communication Services, alongside an engaging frontend experience powered by Azure AI Avatar integrated wi...

Use Case Scenario

This code accelerator is specifically designed for architects and developers, particularly suited to healthcare environments where structured interactions and precise data capture are essential. For example, it effectively manages prescription workflows by capturing patient prescription details via structured question-and-answer interactions or document uploads. Once captured, the information is securely stored, and automated confirmations are communicated directly to patients and caregivers. Real-time i...

Why Agentic AI and Multi-Agent Systems?

A key advantage of this solution lies in its utilization of an Agentic AI approach combined with multi-agent orchestration. Traditional Robotic Process Automation (RPA) systems often struggle to handle deviations or unexpected data inputs effectively. In contrast, the Agentic AI method dynamically adapts interactions based on conversational context. If initial user inputs are insufficient or incomplete, specialized agents proactively request additional information until all necessary requirements are fulfi...

Additionally, a multi-agent architecture significantly enhances modularity, scalability, and maintainability. Individual agents specialize in specific tasks or functions, enabling independent development, easier troubleshooting, and rapid adaptation to evolving business requirements or regulatory demands. This modular design reduces complexity, accelerates solution deployment, and simplifies ongoing maintenance and enhancements.

🎯 Use Cases

• Healthcare prescription management and medication adherence for patients and caregivers
• Automated patient onboarding and structured information capture
• Document-driven data extraction (medical prescriptions, insurance forms)
• Structured follow-up interactions and automated confirmation emails
• Multi-agent conversational experiences specifically tailored for healthcare scenarios

🔍 What It Offers

• ✅ Prebuilt conversational workflows for structured Q&A interactions and prescription management
• ✅ Seamless integration with Azure OpenAI (GPT-4o) and Azure Document Intelligence for intelligent data extraction
• ✅ Real-time interactive avatar using Azure AI Avatar Speech SDK
• ✅ Reliable and scalable data persistence with Azure Cosmos DB
• ✅ Automated email notifications through Azure Communication Services
• ✅ Modular architecture with clearly defined components, integration patterns, and best practices

👥 Who Should Use This

• Architects and developers building intelligent conversational multi-agent systems
• Innovation teams developing Minimum Viable Products (MVPs) for patient-facing AI experiences
• Business and technical teams within healthcare providers and pharmaceutical enterprises
• Partners and system integrators delivering customized healthcare conversational platforms and multi-agent solutions

🧩 Key Components

Agent Orchestration

• Semantic Kernel: Intelligent orchestration and workflow management across agents.

Conversational AI

• Azure OpenAI (GPT-4o): Natural language understanding and structured data extraction.
• Azure Document Intelligence: Accurate data extraction from document uploads.

Data Storage

• Azure Cosmos DB: Secure, structured, and scalable data management.

Frontend Technologies

• Next.js and React.js: Responsive and intuitive user interface.
• Azure AI Avatar and Azure Speech SDK: Engaging conversational interactions.

Communication

• Azure Communication Services: Automated, structured email confirmations and notifications.

Backend Framework

• FastAPI: Structured, scalable backend services and REST API endpoints.

Monitoring and Observability

• Azure Monitor and Application Insights: Comprehensive telemetry and diagnostics.

🚀 Getting Started

Step 1: Clone the Repository

git clone https://github.com/ujjwalmsft/Multi-Agent-Avatar.git

Step 2: Setup the Project

Frontend:

cd frontend
npm install
npm run dev

Backend:

cd backend
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload

Step 3: Configure Azure Services

Set your Azure credentials and environment variables:

backend/config/.env.dev

Step 4: Deploy

Deploy locally, use Docker, or deploy directly to Azure App Service.

Step 5: Customize

Tailor workflows and integrations according to your enterprise-specific requirements and scenarios.

🔧 Technology Stack

Component	Technology
AI & NLP	Azure OpenAI (GPT-4o), Azure Document Intelligence
Avatar Interaction	Azure AI Avatar, Azure Speech SDK
Orchestration	Semantic Kernel
Data Storage	Azure Cosmos DB, Azure Blob Storage
Communication	Azure Communication Services
Frontend Technologies	Next.js, React.js
Backend Technologies	FastAPI, Python
Observability	Azure Monitor, Application Insights

🔭 Roadmap

• Integration of Model Context Protocol (MCP) for enhanced agent orchestration.
• Multi-session support leveraging Semantic Kernel threading capabilities.
• Advanced predictive analytics to provide proactive healthcare insights.
• Expanded multilingual support and enhanced multi-document processing capabilities.

🤝 Contributing

We encourage feedback, feature requests, and contributions. Please open an issue or submit a pull request to help improve and expand this solution.

📬 Contact

For co-engineering engagements, tailored workshops, or enterprise deployment assistance, please reach out to the OCTO Depth Engagement Team:
📧 octodet@microsoft.com