A comprehensive framework for building, deploying, and managing Agentic AI Retrieval-Augmented Generation (RAG) workflows on Google Cloud Platform, with a focus on medical customer support applications.
This framework provides a complete end-to-end solution for implementing production-grade RAG systems with agentic capabilities. It addresses the unique challenges of retrieval-augmented generation workflows, including vector database management, agent orchestration, document processing, compliance, evaluation, and cost optimization.
The framework is built on Google Cloud Platform and leverages key agent technologies:
- Agent Development Kit (ADK) for building multi-agent systems
- Google Agentspace for agent discovery and governance
- Vector Database Integration: Efficient storage, indexing, and retrieval of medical knowledge embeddings
- Agent Orchestration: Coordinating tools, reasoning chains, and stateful interactions for medical support
- Document Processing: Chunking, embedding, and indexing medical documents effectively
- Compliance Framework: HIPAA-compliant handling of sensitive medical information
- Real-time Serving: Low-latency, high-throughput serving with streaming responses
- Cost Optimization: Managing the significant costs of LLM API calls and embedding generation
- React-based UI: Modern, responsive interface for medical support agents
- Monitoring & Governance: Comprehensive dashboards for system oversight
The framework consists of several interconnected layers, each addressing specific aspects of RAG system development and deployment. See the Architecture Documentation for detailed diagrams and explanations.
- Docker and Docker Compose
- Google Cloud SDK
- Node.js and npm (for UI development)
- Python 3.9+
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Clone this repository:
git clone https://github.com/yourusername/enhanced-rag-framework.git cd enhanced-rag-framework -
Set up environment variables:
cp .env.example .env # Edit .env with your configuration -
Start the services:
docker-compose up
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Access the UI at http://localhost:3000
See the Deployment Guide for detailed instructions on deploying to Google Cloud Platform.
- Architecture
- Configuration Layer
- Execution Engine
- Validation Layer
- Governance Layer
- Infrastructure Components
- Developer Experience
- Deployment Guide
- CLI and SDK Usage
- Monitoring and Logging
This project is licensed under the MIT License - see the LICENSE file for details.
- Google Cloud Platform for providing the infrastructure and agent technologies
- The open-source community for their invaluable contributions