Part of the GPT-RAG solution.
The GPT-RAG Orchestrator service is an agentic orchestration layer built on Azure AI Foundry Agent Service and the Microsoft Agent Framework. It enables agent-based RAG workflows by coordinating multiple specialized agents—each with a defined role—to collaboratively generate accurate, context-aware responses for complex user queries.
| Key | Strategy | Description |
|---|---|---|
single_agent_rag |
Single Agent RAG | RAG strategy using Azure AI Foundry Agent Service v2 with dynamic routing and direct LLM bypass. |
maf_agent_service |
MAF + Agent Service | Microsoft Agent Framework with Azure AI Foundry Agent Service v2 for server-side threads and tool orchestration, with request-scoped client lifecycle for stable async cleanup. |
maf_lite |
MAF Lite | Microsoft Agent Framework with direct Azure OpenAI model access (no Agent Service dependency). |
mcp |
MCP | Model Context Protocol strategy using Semantic Kernel. |
nl2sql |
NL2SQL | Natural language to SQL translation strategy for structured data queries. |
For comprehensive information about GPT-RAG, including architecture details, configuration guides, best practices, troubleshooting resources, deployment guidance, customization options, and advanced usage scenarios, please refer to the official project documentation.
Before deploying the application, you must provision the infrastructure as described in the GPT-RAG repo. This includes creating all necessary Azure resources required to support the application runtime.
Click to view software prerequisites
The machine used to customize and or deploy the service should have:
- Azure CLI: Install Azure CLI
- Azure Developer CLI (optional, if using azd): Install azd
- Git: Download Git
- Python 3.12: Download Python 3.12
- Docker CLI: Install Docker
- VS Code (recommended): Download VS Code
Make sure you're logged in to Azure before anything else:
az loginInitialize the template:
azd init -t azure/gpt-rag-orchestrator Important
Use the same environment name with azd init as in the infrastructure deployment to keep components consistent.
Update env variables then deploy:
azd env refresh
azd deploy Important
Run azd env refresh with the same subscription and resource group used in the infrastructure deployment.
Aqui está uma versão mais clara, direta e consistente da instrução:
To deploy using a script, first clone the repository, set the App Configuration endpoint, and then run the deployment script.
git clone https://github.com/Azure/gpt-rag-orchestrator.git
$env:APP_CONFIG_ENDPOINT = "https://<your-app-config-name>.azconfig.io"
cd gpt-rag-orchestrator
.\scripts\deploy.ps1Encountered an error or bug? Help us improve the quality of this accelerator by reporting issues or suggesting enhancements on our GitHub Issues page. Your feedback helps make GPT-RAG better for everyone!
Note
For earlier versions, use the corresponding release in the GitHub repository (e.g., v1.0.0 for the initial version).
We appreciate contributions! See CONTRIBUTING for guidelines on submitting pull requests.
This project may contain trademarks or logos. Authorized use of Microsoft trademarks or logos must follow Microsoft’s Trademark & Brand Guidelines. Modified versions must not imply sponsorship or cause confusion. Third-party trademarks are subject to their own policies.