GPT RAG
Sharing the learning along the way we been gathering to enable Azure OpenAI at enterprise scale in a secure manner. GPT-RAG core is a Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
Install / Use
npx skills add Azure/GPT-RAGInstalls into whichever agent you are using.
README
GPT-RAG Solution Accelerator
This solution accelerator provides architecture templates and deployment assets to help organizations build secure, scalable, and enterprise-ready Retrieval-Augmented Generation (RAG) solutions powered by AI Agents. It applies proven Azure design patterns and incorporates Zero-Trust security, Responsible AI, and end-to-end observability, enabling teams to operationalize Generative AI with confidence.
For full documentation, visit the GPT-RAG documentation site.
GPT-RAG is built on a Zero-Trust architecture to ensure that all components operate within a controlled, isolated environment. Network access is tightly governed, and communication between services follows least-privilege principles.
Getting started
Head to the documentation site for the complete guides:
- Deployment Guide covers Basic, Zero Trust, and network-isolated deployments, preflight checks, jumpbox workflow, and container image builds.
- Grounding sources overview covers Foundry IQ, Azure AI Search, Work IQ, and how to pick a source. Deeper how-tos for each source are linked from the overview.
- What's New highlights the notable features added over time.
Architecture
Zero-Trust Architecture
AI Agent Capabilities
The accelerator supports a broad range of enterprise scenarios, from customer support to decision automation, by enabling systems to process complex queries across large data collections. It is designed for seamless integration into existing environments and can be adapted to both straightforward and advanced operational patterns.
A key capability of GPT-RAG is its support for AI Agents, enabling scenarios such as NL2SQL query generation and other context-aware interactions. This extensibility allows organizations to build intelligent workflows that retrieve, interpret, and act on data with contextual precision.
GPT-RAG UI
Contributing
We welcome contributions! See the contribution guidelines for details on how to contribute.
Trademarks
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.
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