This is a sample application from Microsoft demonstrating how to build a chatbot with Azure OpenAI and your own data using Retrieval-Augmented Generation (RAG). It is a full-stack web application with a Python Quart async backend and a React/TypeScript frontend. The backend handles conversation orchestration, integrates with Azure OpenAI for chat completions, and supports multiple data sources (Azure Cognitive Search, CosmosDB, Elasticsearch, Pinecone, etc.) for grounding responses. It also includes a comprehensive data preparation pipeline (scripts) for chunking documents, generating embeddings, and indexing into search services. The frontend provides a modern chat interface with features like streaming responses, citation display, chat history, and file upload. The repository is primarily an application but has a strong data engineering component, making it a hybrid. It is actively maintained, well-structured with tests and CI/CD, but has some technical drift due to preview APIs and outdated dependencies.