Improve The Response Time From LLM — OpenAI and Azure OpenAI

Shweta Lodha
Apr 19, 2024


Semantic Kernel, a powerful tool for integrating large language models into your applications, now supports streaming responses. In this blog post, we’ll explore how to leverage this feature to obtain streamed results from LLMs like AzureOpenAI and OpenAI.

Image generated from Bing

Why Streamed Responses Matter

When working with language models, especially in conversational scenarios, streaming responses offer several advantages:

  • Real-time Interaction: Streaming allows you to receive partial responses as they become available, enabling more interactive and dynamic conversations.
  • Reduced Latency: Instead of waiting for the entire response, you can start processing and displaying content incrementally, reducing overall latency.
  • Efficient Resource Usage: Streaming conserves memory and resources by handling data in smaller chunks.

How to Use Streaming Responses

If this is what interests you, then check out my complete article on my blog.