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.
This pull request includes various updates and improvements across multiple files, focusing on new features, documentation enhancements, and configuration options. The most important changes include adding new installation options, updating environment variables for database integration, and enhancing documentation with new sections and tutorials.
New Features and Configuration Options:
CHANGELOG.md: Added an option to install specific GPT-RAG components: data ingestion, orchestrator, and frontend.
docs/CUSTOMIZATIONS.md: Introduced a new section for selecting specific components to install during deployment.
Documentation Enhancements:
README.md: Added metadata for sample page type and updated recommended app authentication section with a tutorial link. [1][2][3]
docs/API_Management_Integration.md: Added a comprehensive guide on integrating Azure API Management (APIM) with detailed steps and benefits.
docs/CUSTOMIZATIONS.md: Added a new section on filtering files with AI Search using security trimming.
Environment Variables and Integration:
docs/AI_INTEGRATION_HUB.md: Updated environment variables for SQL and Teradata integrations to use a more consistent naming convention. [1][2]
azure.yaml: Removed post-deploy hooks for both POSIX and Windows environments.
This pull request includes various updates and improvements across multiple files, focusing on new features, documentation enhancements, and configuration options. The most important changes include adding new installation options, updating environment variables for database integration, and enhancing documentation with new sections and tutorials.
New Features and Configuration Options:
CHANGELOG.md: Added an option to install specific GPT-RAG components: data ingestion, orchestrator, and frontend.docs/CUSTOMIZATIONS.md: Introduced a new section for selecting specific components to install during deployment.Documentation Enhancements:
README.md: Added metadata for sample page type and updated recommended app authentication section with a tutorial link. [1] [2] [3]docs/API_Management_Integration.md: Added a comprehensive guide on integrating Azure API Management (APIM) with detailed steps and benefits.docs/CUSTOMIZATIONS.md: Added a new section on filtering files with AI Search using security trimming.Environment Variables and Integration:
docs/AI_INTEGRATION_HUB.md: Updated environment variables for SQL and Teradata integrations to use a more consistent naming convention. [1] [2]azure.yaml: Removed post-deploy hooks for both POSIX and Windows environments.