What problem does it solve? Adding a conversational AI assistant to a WPF desktop application normally requires building the entire chat UI, streaming logic, Markdown rendering, and provider integration from scratch. This Skill guides you through embedding the DevExpress AIChatControl so the chat surface, streaming, file attachments, and history are handled for you. ## Core Features & Use Cases - Provider Integration: Register an IChatClient for Azure OpenAI, OpenAI, Ollama, or Semantic Kernel via AIExtensionsContainerDesktop at startup. - Rich Chat Features: Enable response streaming, Markdown rendering with sanitization, file attachments, prompt suggestions, and chat history persistence with SaveMessages/LoadMessages. - RAG & Multi-Client Scenarios: Build chat-with-your-data apps using the dx.wpf.aichatrag CLI template or the OpenAI Assistant API, and run multiple chat surfaces with keyed clients via ChatClientServiceKey. - Use Case: You are building a document Q&A assistant inside a WPF line-of-business app. Use this Skill to switch the project SDK to Microsoft.NET.Sdk.Razor, register an Azure OpenAI client, drop the AIChatControl into a ThemedWindow, and enable streaming plus Markdown rendering. ## Quick Start Ask the AI to add the DevExpress AIChatControl to your WPF project with an Azure OpenAI client, streaming, and Markdown rendering enabled.
