This repository provides templates to quickly set up all the core Azure resources needed for RAG applications, allowing you to build a secure and scalable environment based on proven architecture patterns. Retrieval-Augmented Generation (RAG) enables large language models to generate responses grounded in your organization’s data, so answers stay current without retraining the model. This accelerator delivers an enterprise-ready foundation with zero-trust security, Responsible AI features, high availability, and auditing—making it ideal for moving from prototypes to MVPs or production.
Expand to view prerequisites
To deploy this template, the user or service principal requires the following permissions on the target Resource Group:
- An Azure subscription.
- An Azure user with Contributor and User Access Admin permissions on the target resource group.
In addition, the machine or environment used for deployment should have:
- Azure Developer CLI: Install azd
- PowerShell 7+ (Windows only): Install PowerShell
- Git: Download Git
- Python 3.12: Download Python
- An Azure AI Services resource created or agreement to Responsible AI terms in the portal
azd init -t azure/gpt-rag
azd provisionTip
You can update main.parameters.json to customize settings before running azd provision.
After infrastructure is in place, deploy the GPT-RAG services from their respective repositories:
-
Orchestrator – Manages information retrieval and response generation with an agent-based approach using Semantic Kernel and Azure AI Foundry Agent Service.
-
Web UI – Provides the user interface, supports streaming responses, and allows easy customization.
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Data Ingestion – Handles data chunking and indexing to optimize retrieval for the RAG workflow.
| Resource | Role | Assignee | Description |
|---|---|---|---|
| GenAI App Configuration Store | App Configuration Data Owner | Executor | Full control over configuration settings |
| GenAI App Configuration Store | App Configuration Data Reader | ContainerApp: orchestrator | Read configuration data |
| GenAI App Configuration Store | App Configuration Data Reader | ContainerApp: frontend | Read configuration data |
| GenAI App Configuration Store | App Configuration Data Reader | ContainerApp: dataingest | Read configuration data |
| GenAI App Configuration Store | App Configuration Data Reader | ContainerApp: mcp | Read configuration data |
| GenAI App Container Registry | AcrPull | ContainerApp: mcp | Pull container images |
| GenAI App Container Registry | AcrPush | Executor | Push container images |
| GenAI App Container Registry | AcrPull | ContainerApp: orchestrator | Pull container images |
| GenAI App Container Registry | AcrPull | ContainerApp: frontend | Pull container images |
| GenAI App Container Registry | AcrPull | ContainerApp: dataingest | Pull container images |
| GenAI App Key Vault | Key Vault Contributor | Executor | Manage Key Vault settings |
| GenAI App Key Vault | Key Vault Secrets Officer | Executor | Create Key Vault Secrets |
| GenAI App Key Vault | Key Vault Secrets User | ContainerApp: orchestrator | Read secrets |
| GenAI App Key Vault | Key Vault Secrets User | ContainerApp: frontend | Read secrets |
| GenAI App Key Vault | Key Vault Secrets User | ContainerApp: dataingest | Read secrets |
| GenAI App Key Vault | Key Vault Secrets User | ContainerApp: mcp | Read secrets |
| GenAI App Search Service | Search Service Contributor | Executor | Create/update search service elements |
| GenAI App Search Service | Search Index Data Contributor | Executor | Read/write search index data |
| GenAI App Search Service | Search Index Data Reader | AI Foundry Project | Read index data |
| GenAI App Search Service | Search Service Contributor | AI Foundry Project | Create AI search connection |
| GenAI App Search Service | Search Index Data Reader | ContainerApp: orchestrator | Read index data |
| GenAI App Search Service | Search Index Data Contributor | ContainerApp: dataingest | Read/write index data |
| GenAI App Search Service | Search Index Data Contributor | ContainerApp: mcp | Read/write index data |
| GenAI App Storage Account | Storage Blob Data Contributor | Executor | Read/write blob data |
| GenAI App Storage Account | Storage Blob Data Reader | AI Foundry Account | Read blob data |
| GenAI App Storage Account | Storage Blob Data Reader | ContainerApp: orchestrator | Read blob data |
| GenAI App Storage Account | Storage Blob Data Reader | ContainerApp: frontend | Read blob data |
| GenAI App Storage Account | Storage Blob Data Contributor | ContainerApp: dataingest | Read/write blob data |
| GenAI App Storage Account | Storage Blob Data Reader | Search Service | Read blob data for search integration |
| GenAI App Storage Account | Storage Blob Data Contributor | ContainerApp: mcp | Read/write blob data |
| GenAI App Storage Account | Storage Queue Data Contributor | ContainerApp: mcp | Read/write storage queue data |
| GenAI App Cosmos DB | Cosmos DB Built-in Data Contributor | ContainerApp: orchestrator | Read/write Cosmos DB data |
| GenAI App Cosmos DB | Cosmos DB Built-in Data Contributor | Executor | Read/write Cosmos DB data |
| AI Foundry Project | Azure AI Project Manager | Executor | Manage AI Foundry projects and assign roles |
| AI Foundry Storage Account | Storage Blob Data Contributor | AI Foundry Project | Enable agent to store/retrieve blob artifacts in customer storage |
| AI Foundry Storage Account Containers | Storage Blob Data Owner (workspace) | AI Foundry Project | Scoped owner access to workspace containers for session-specific data |
| AI Foundry Cosmos DB Account | Cosmos DB Operator | AI Foundry Project | Control-plane operations for enterprise memory database (threads) |
| AI Foundry Cosmos DB Containers | Cosmos DB Built-in Data Contributor | AI Foundry Project | Read/write conversation threads within enterprise memory containers |
| AI Foundry Search Service | Search Service Contributor | AI Foundry Project | Create/update indexes for vector search workflows |
| AI Foundry Search Service | Search Index Data Contributor | AI Foundry Project | Read/write index data for embedding-based queries |
| AI Foundry Account | Cognitive Services User | ContainerApp: orchestrator | Access Cognitive Services operations |
| AI Foundry Account | Cognitive Services User | ContainerApp: dataingest | Access Cognitive Services operations |
| AI Foundry Account | Cognitive Services OpenAI User | ContainerApp: orchestrator | Use OpenAI APIs |
| AI Foundry Account | Cognitive Services OpenAI User | ContainerApp: dataingest | Use OpenAI APIs |
| AI Foundry Account | Cognitive Services User | ContainerApp: mcp | Access Cognitive Services |
| AI Foundry Account | Cognitive Services OpenAI User | ContainerApp: mcp | Use OpenAI APIs |
This repo has undergone a major architectural update. For the original version, see v1.0.0.
To deploy v1.0.0 run the following commands:
azd init -t azure/gpt-rag -b v1.0.0
azd provisionWe appreciate contributions! See CONTRIBUTING.md for guidelines on the Contributor License Agreement (CLA), code of conduct, and 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.
