beebot
semantic-kernel
beebot | semantic-kernel | |
---|---|---|
1 | 48 | |
379 | 18,964 | |
5.8% | 3.8% | |
8.7 | 9.9 | |
8 months ago | 5 days ago | |
Python | C# | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
beebot
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Overview: AI Assembly Architectures
BeeBot: github.com/AutoPackAI/beebot
semantic-kernel
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Introducing Semantic Kernel
Semantic Kernel is an open-source SDK that allows us to easily bring AI capabilities to our applications. It allows us to connect to AI services such as OpenAI and Azure OpenAI with ease. If you have worked with LangChain, Semantic Kernel is a Microsoft implementation of a project like LangChain. Semantic Kernel allows us to integrate AI functionality such as text generation, text summarization, chat completion, and image generation in our applications.
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#SemanticKernel β πChat Service demo running Phi-2 LLM locally with #LMStudio
There is an amazing sample on how to create your own LLM Service class to be used in Semantic Kernel. You can view the Sample here: https://github.com/microsoft/semantic-kernel/blob/3451a4ebbc9db0d049f48804c12791c681a326cb/dotnet/samples/KernelSyntaxExamples/Example16_CustomLLM.cs
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Semantic Tests for SemanticKernel Plugins using skUnit
This week, I had the chance to explore the SemanticKernel code base, particularly the core plugins. SemanticKernel comes equipped with these built-in plugins:
- FLaNK Stack for 04 December 2023
- Semantic Kernel
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Getting Started with Semantic Kernel and C#
In this article we'll look at the high-level capabilities building AI orchestration systems in C# with Semantic Kernel, a rapidly maturing open-source AI orchestration framework.
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Agency: Pure Go LangChain Alternative
I'm using Semantic Kernel (https://github.com/microsoft/semantic-kernel) and it's really nice. Makes building more complex workflows really simple without sacrificing control.
A bunch of examples (https://github.com/microsoft/semantic-kernel/blob/main/dotne...) for how to handle just about anything you need to do with OAI with a lot less boilerplate.
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New: LangChain templates β fastest way to build a production-ready LLM app
I haven't tried it but there's Microsoft semantic-kernel.
https://github.com/microsoft/semantic-kernel
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Overview: AI Assembly Architectures
Semantic Kernel github.com/microsoft/semantic-kernel
What are some alternatives?
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
langchain - β‘ Building applications with LLMs through composability β‘ [Moved to: https://github.com/langchain-ai/langchain]
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
langchain - π¦π Build context-aware reasoning applications
AgentVerse - π€ AgentVerse πͺ is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation
guidance - A guidance language for controlling large language models.
malmo - Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
awesome-ai-agents - A list of AI autonomous agents
EdgeChains - EdgeChains.js Typescript/Javascript production-friendly Generative AI. Based on Jsonnet. Works anywhere that Webassembly does. Prompts live declaratively & "outside code in config". Kubernetes & edge friendly. Compatible with OpenAI GPT, Gemini, Llama2, Anthropic, Mistral and others
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks