GPT-RAG

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GPT-RAG is a solution accelerator for building Retrieval-Augmented Generation (RAG) solutions on Azure. It provides architecture templates and deployment assets for secure and scalable AI applications.

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At a glance

Pricing

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Free tier

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API

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Skill level

Technical

About

What is GPT-RAG?

GPT-RAG is designed to accelerate the development of Retrieval-Augmented Generation (RAG) solutions within the Azure ecosystem. It leverages Azure Cognitive Search and Azure OpenAI services to enable the creation of ChatGPT-style experiences. The accelerator offers pre-built architecture templates and essential deployment assets, facilitating the rapid and secure deployment of scalable AI applications. This tool is ideal for developers and organizations looking to integrate advanced AI capabilities with their existing Azure infrastructure.

Best used for

Building and deploying secure, scalable Retrieval-Augmented Generation (RAG) solutions on Azure using OpenAI and Cognitive Search.

Common actions

Build RAG solutions

Deploy AI applications

Integrate Azure AI

Create ChatGPT experiences

Accelerate AI development

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Capabilities

Key features

RAG solution accelerator
Azure Cognitive Search integration
Azure OpenAI integration
ChatGPT-style experiences
Architecture templates

Target Audience

DevelopersAI EngineersSolution ArchitectsEnterprises

Integrations

Not yet documented

Pricing & Plans

unknown

Free

FAQs

What are the typical costs associated with deploying a solution using GPT-RAG, considering it leverages Azure services?

While GPT-RAG itself is an accelerator, deployment will incur costs based on the Azure services consumed, such as Azure Cognitive Search, Azure OpenAI, and other supporting infrastructure. Users should budget for these operational expenses.

Does GPT-RAG support RAG implementations outside of Azure Cognitive Search, or is it exclusively tied to Azure's ecosystem?

GPT-RAG is specifically designed to accelerate RAG solutions within the Azure ecosystem, with direct integration and templates for Azure Cognitive Search. While the RAG concept is broad, this accelerator focuses on Azure-native components.

Can GPT-RAG be used with custom large language models (LLMs) or is it limited to Azure OpenAI models?

GPT-RAG is built to integrate seamlessly with Azure OpenAI services, providing a streamlined experience for models available through that platform. Adapting it for custom LLMs outside of Azure OpenAI would likely require additional development.

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