Reference implementation of the Retrieval-Augmented Generation (RAG) pattern.

1 Data ingestion

2 Orchestrator

3 App Front-End

To deploy this solution you just need to execute the next steps:

1) Provision required Azure services

You can do it by clicking on the following button

or by using Azure Developer CLI (azd) executing the following lines in terminal

azd auth login
azd init -t azure/gpt-rag
azd up

Important: when selecting the target location check here the regions that currently support the Azure OpenAI models you want to use.

2) Ingestion Component

Use Data ingestion repo template to create your data ingestion git repo and execute the steps in its Deploy section.

3) Orchestrator Component

Use Orchestrator repo template to create your orchestrator git repo and execute the steps in its Deploy section.

4) Front-end Component

Use App Front-end repo template to create your own frontend git repo and execute the steps in its Deploy section.

• Pricing Model

• Governance Model

• Get started with the Cloud Adoption Framework

• What is an Azure landing zone?

• Azure Cognitive Search

• Azure OpenAI Service

• Revolutionize your Enterprise Data with ChatGPT: Next-gen Apps w/ Azure OpenAI and Cognitive Search

• Introducing Azure OpenAI Service On Your Data in Public Preview

• Grounding LLMs

• Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback

• Microsoft Guidance Validation and Robustness of responses

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

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