Use the new tools in Azure AI Foundry to quickly build an agentic RAG application.
Quickly build a RAG chatbot using Azure Cosmos DB for NoSQL and Azure OpenAI. This notebook guides you through vector search and retrieval-augmented generation
Deploy our most popular RAG solution to Azure so that you can chat with your own documents.
Watch the recordings from the 25+ live streams for RAGHack 2024, covering multiple languages, Azure databases, and frameworks.
Learn how RAG flows can be improved through fine-tuning to provide more tailered and accurate answers.
Learn about RAFT (Retrieval Augmented Fine-Tuning), a method to enhance LLMs for better domain adaptation.
Learn best practices for building RAG applications using state-of-the-art retrieval mechanisms from Azure AI Search.
Deploy a Python app that can chat with a PostgreSQL database using Azure OpenAI LLMs.
A hierarchical RAG approach builds a knowledge graph and uses it to answer questions
A step-by-step walkthrough to deploy a JavaScript RAG application to Azure Functions.
A step-by-step walkthrough to evaluate a Python RAG application using GPT-based evaluators.
A learning path for using Azure OpenAI, making a RAG app with it, and generating images.
Learn the steps of an advanced RAG system: ingestion, chunking, update pipelines, query routing, and post-processing.
Find more RAG templates for your favorite language in the AI App Templates gallery.
Discover the options Azure offers for vector search, like Azure AI Search, Cosmos DB, PostgreSQL, and more.
