LangChain has announced streaming support aimed at enhancing the user experience of LLM applications by addressing latency issues through token-by-token output rather than waiting for the entire response. This improvement is particularly significant for chat applications, as it provides users with immediate feedback, similar to how ChatGPT functions. The updated chat-langchain repository now includes streaming and asynchronous execution, serving as a template for developers to build advanced chat and Q&A applications. The application utilizes FastAPI for the backend and Jinja templates for the UI and is designed to be easily deployable for multiple users. Streaming is supported for both synchronous and asynchronous executions, and callback handlers like StreamingLLMCallbackHandler and QuestionGenCallbackHandler facilitate real-time interaction through websockets. The project is open source, encouraging community input, and aims to expand streaming support to other LLMs and provide more examples for callback handlers.