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- RAG chat app with Azure OpenAI and Azure AI Search (Python)
RAG chat app with Azure OpenAI and Azure AI Search (Python) This solution creates a ChatGPT-like frontend experience over your own documents using RAG (Retrieval Augmented Generation)
- RAG chat app with your data (Python) - Code Samples
It uses Azure OpenAI Service to access a GPT model (gpt-4 1-mini), and Azure AI Search for data indexing and retrieval The repo includes sample data so it's ready to try end to end
- Building a Retrieval-Augmented Generation (RAG) App with Azure AI . . .
Azure AI Search resource (Standard tier recommended) Azure OpenAI resource (with a deployed chat completions model) Python 3 8+ PowerShell (for running setup scripts) Git (to clone the repository) Basic familiarity with the command line Indexing We will examine how to perform indexing and prepare the data for querying using the core components
- Overview of RAG Chat App using Azure AI Search with OpenAI in Python . . .
Table of Contents:00:35 - Retrieval Augmented Generation (RAG)01:18 - Code walkthrough01:52 - Azure Architecture
- AI Chat App Hack: A Guide for Technical Students
Learn how to build a RAG Chat App using Azure OpenAI, Azure AI Search, and Python Extend the app for your own data sources Collaborate with other developers from around the world Win exciting prizes Getting started with the AI Chat App Hack is simple Here are the steps you need to follow: Visit the AI Chat App Hack page and register
- RAG tutorial: Search using an LLM - Azure AI Search
The defining characteristic of a RAG solution on Azure AI Search is sending queries to a Large Language Model (LLM) for a conversational search experience over your indexed content It can be surprisingly easy if you implement just the basics In this tutorial, you: This tutorial builds on the previous tutorials
- GitHub - Azure-Samples chat-with-your-data-solution-accelerator: A . . .
Azure OpenAI Service offers out-of-the-box, end-to-end RAG implementation that uses a REST API or the web-based interface in the Azure AI Foundry to create a solution that connects to your data to enable an enhanced chat experience with Azure OpenAI ChatGPT models and Azure AI Search
- Best approach for RAG using Azure OpenAI and AI Search with Python SDK . . .
I struggle understanding what are the pros and cons of each one of these approaches for implementing a RAG using Azure OpenAI with AI Search as source, with Python SDK Both work well, but option B looks much cleaner Why should we even bother doing all the steps in option A ourselves? Am I missing something?
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