markprompt
semantic-kernel
| markprompt | semantic-kernel | |
|---|---|---|
| 9 | 47 | |
| 2,188 | 18,332 | |
| - | 4.2% | |
| 10.0 | 9.9 | |
| 5 months ago | 6 days ago | |
| TypeScript | C# | |
| Apache License 2.0 | 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.
markprompt
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Announcing the Markprompt + Contenda integration: Confbrew
Register for a key on Markprompt
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Open-Source GPT-4 Platform for Markdown
I filed an issue a few hours ago. https://github.com/motifland/markprompt/issues/5 (for asciidoc)
- Markprompt - GPT-4 prompt for your Markdown docs
- Open Source GPT-4 platform for Markdown
- Markprompt: Open-Source GPT-4 for Markdown, Markdoc and MDX
semantic-kernel
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#SemanticKernel – 📎Chat 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 – 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
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Automated Routing of Tasks to Optimal Models: A PR for Semantic-Kernel
The need for efficient model routing has been a point of discussion in the community. Addressing this, I've submitted a pull request to Semantic-Kernel that introduces an automated multi-model connector.
What are some alternatives?
vscode-markdoc - VSCode extension for Markdoc syntax highlighting and language support
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
langchain - 🦜🔗 Build context-aware reasoning applications
openai-cookbook - Examples and guides for using the OpenAI API
guidance - A guidance language for controlling large language models.
julia-sanfrancisco - A clone of the game "Where in the World is Carmen Sandiego?" largely re-created with generative AI.
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
vectordb-benchmark
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
dspy - DSPy: The framework for programming—not prompting—foundation models