Semantic Kernel

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Chat Copilot Performance improvements for chat and messaging loading

August 28, 2023 Aug 28, 2023 08/28/23
Nilesh Acharya
(image) We are introducing enhancements to greatly improve performance, reduce cost and data throughput for customers of Chat Copilot. In the current design, partitions are defined by an ID. Overtime as the CosmosDB grows with increased storage we have seen scenarios with extended processing time when customers try to load the list of ...

GUEST POST: Getting Started with Semantic Kernel for LangChain users

August 28, 2023 Aug 28, 2023 08/28/23
Gopi Kumar
Large language models such as GPT4 and chatGPT have created a revolution in the way people build innovative new applications and experiences. I describe how I got started with building LLM applications and point to some resources I created in this process that I hope will help in your own exploration into this exciting area of software ...

GUEST POST: Semantic Kernel and Weaviate: Orchestrating interactions around LLMs with long-term memory

August 16, 2023 Aug 16, 2023 08/16/23
Zain Hasan
The Emerging LLM Stack In a recent interview, the co-founder of Cohere stated - “For the first time in the history of our planet, we have machines that we’ve created that can use our language.” A bold statement indeed, but it couldn’t be more accurate and we’ve all witnessed the incredible power of said machines. It would be an ...

Semantic Kernel Planners: Stepwise Planner

August 15, 2023 Aug 15, 2023 08/15/23
authorsNilesh Acharya, Lee Miller
(image) Welcome to the third and final blog post in this series about Semantic Kernel Planners. In the previous blogs we touched on discussed the action planner and sequential planner. In this blog we will discuss Semantic Kernal's latest generation of planner called Stepwise Planner. The Stepwise Planner is a powerful planning object ...

How To Use Microsoft Fabric with Semantic Kernel

August 14, 2023 Aug 14, 2023 08/14/23
John Maeda
For lovers of Microsoft Fabric as their data tool of choice, there's a terrific post up on the Fabric blog on how to get started using Semantic Kernel with your "Lakehouse" of choice. Semantic Kernel is used for the "AI Orchestration" layer in the Copilot Stack as featured at Build 2023. (image) Kinfey Lo details how to use Azure Blob ...

AI tooling for Java developers with SK

August 10, 2023 Aug 10, 2023 08/10/23
Soham Dasgupta
Every system needs to be able to add AI to its workflow to empower the users to complete their task much faster.  The Semantic Kernel team and community have been working hard to create a Java based kernel to support Java developers to unleash AI into their apps.  I will walk you through this journey below. We will review the following ...

Unlock the Power of Telemetry in Semantic Kernel SDK

August 3, 2023 Aug 3, 2023 08/3/23
Nilesh Acharya
(image) As more and more customers are becoming reliant on the Semantic Kernel SDK to create sophisticated and powerful applications, we have heard the need for greater transparency into end-to-end traceability and debugging. For example, if you want to know how a specific plugin can impact performance or looking for a way to debug a request...

Test your ChatGPT plugins in the updated Chat Copilot

August 2, 2023 Aug 2, 2023 08/2/23
Matthew Bolanos
(image) We've been hard at work improving the Chat Copilot reference application to demonstrate how you can use Semantic Kernel to build a fully featured chat experience. Now that its more feature complete, we're elevating it to its own repo here: github.com/microsoft/chat-copilot. We've also given it its own section on our learn site so ...

Help us grow the Semantic Kernel Community!

July 28, 2023 Jul 28, 2023 07/28/23
Alex Chao
(image) A big part of the any successful open-source project is the strength of the community. We've been amazed to see people from around the world attend office hours, engage on Discord, and build real projects with the Semantic Kernel. And we're excited to see what is in store for the future! We'd love to get your feedback on how we ...