Azure-AI-RAG-CSharp-Semantic-Kernel-Functions

A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.

This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT 3.5 Turbo LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.

Azure Functions Python Sample Codes. NOTE: The project, hosted in a repository, is no longer actively maintained by its creators or contributors. There won't be any further updates, bug fixes, or support from the original developers in the project.

A creative writing multi-agent solution to help users write articles.

A TypeScript sample app for the Retrieval Augmented Generation pattern running on Azure, using Azure AI Search for retrieval and Azure OpenAI and LangChain large language models (LLMs) to power ChatGPT-style and Q&A experiences.

Apache Spark Connector for Azure Cosmos DB

Build a generative AI application using LangChain.js, from local to Azure

A creative writing multi-agent solution to help users write articles using Aspire and Semantic Kernel

This repository offers a Python framework for a retrieval-augmented generation (RAG) pipeline using text and images from MHTML documents, leveraging Azure AI and OpenAI services. It includes ingestion and enrichment flows, a RAG with Vision pipeline, and evaluation tools.

Copy Neo4j data to Azure Cosmos DB