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Language Visual Studio Code TypeScript Python POML Documentation¶ Welcome to the Prompt Orchestration Markup Language (POML) documentation. POML (Prompt Orchestration Markup Language) is a novel markup language designed to bring structure, maintainability, and versatility to advanced prompt engineering for Large Language Models (LLMs). It addresses common challenges in prompt development, such as
Jianwei Yang*1† Reuben Tan1† Qianhui Wu1† Ruijie Zheng2‡ Baolin Peng1‡ Yongyuan Liang2‡ Yu Gu1 Mu Cai3 Seonghyeon Ye4 Joel Jang5 Yuquan Deng5 Lars Liden1 Jianfeng Gao1▽ 1Microsoft Research 2University of Maryland 3University of Wisconsin-Madison 4KAIST 5University of Washington * Project lead. †First authors. ‡Second authors. ▽Leadership Magma is the first foundation model for
Programmatically assemble prompts for LLMs using JavaScript. Orchestrate LLMs, tools, and data in a single script. JavaScript toolbox to work with prompts Abstraction to make it easy and productive Seamless Visual Studio Code integration or flexible command line Built-in support for GitHub Copilot and GitHub Models, OpenAI, Azure OpenAI, Anthropic, and more
The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces. However, we argue that the power multimodal models like GPT-4V as a general agent on multiple operating systems across different applications is largely underestimated due to the lack of a robust screen parsing technique capable of: 1. reliably identifying interactable
Home Indexing Prompt Tuning Query Configuration CLI Extras Welcome to GraphRAG 👉 Microsoft Research Blog Post 👉 GraphRAG Arxiv Figure 1: An LLM-generated knowledge graph built using GPT-4 Turbo. GraphRAG is a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting
GarnetA high-performance cache-store from Microsoft Research High PerformanceGarnet uses a thread-scalable storage layer called Tsavorite, and provides cache-friendly shared-memory scalability with tiered storage support. Garnet supports cluster mode (sharding and replication). It has a fast pluggable network design to get high end-to-end performance (throughput and 99th percentile latency). Garne
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Power Platform による、企業で有用なアプリのサンプルを無償提供しています。 本アプリは、日本マイクロソフトの社員有志により作成・公開しています。 こちらのアプリは Power Platform の Premium 機能を利用しています。 また、アプリは無償でダウンロードが可能です。 アプリについて 以下のリンクからソースをダウンロードし、フォルダ内の手順書に従ってインストール、ご利用をお願いします。 また、アプリご利用の際には Premium ライセンスが必要となります。 評価環境について アプリサンプルを Power Platform の評価環境でお試しされたい場合、以下の手順書または動画をご参考に評価環境を作成してください。 Power Platform (Power Apps, Power Automate) のお試し環境を準備しよう(手順書) Power Platfo
July 20, 2023 by Anders Hejlsberg, Steve Lucco, Daniel Rosenwasser, Pierce Boggan, Umesh Madan, Mike Hopcroft, and Gayathri Chandrasekaran In the last few months, we've seen a rush of excitement around the newest wave of large language models. While chat assistants have been the most direct application, there's a big question around how to best integrate these models into existing app interfaces.
TypeChat TypeChat helps get well-typed responses from language models to build pragmatic natural language interfaces. All powered through your types.
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Introduction This is a (non-comprehensive) guide for C# and .NET developers that are completely new to the Rust programming language. Some concepts and constructs translate fairly well between C#/.NET and Rust, but which may be expressed differently, whereas others are a radical departure, like memory management. This guide provides a brief comparison and mapping of those constructs and concepts w
Introduction to Machine Learning for Beginners
YARP documentation has been moved to https://learn.microsoft.com/search/?terms=YARP%20Getting%20Started&category=Documentation.
Introducing DoWhy DoWhy | An end-to-end library for causal inference Graphical Models and Potential Outcomes: Best of both worlds Four steps of causal inference Citing this package Roadmap Contributing Quick-Start Tutorial Tutorial on Causal Inference and its Connections to Machine Learning (Using DoWhy+EconML) Starter Notebooks Getting started with DoWhy: A simple example Confounding Example: Fin
Azure Synapse Analytics Azure Storage および Azure Data Lake Storage Gen2 Azure Stream Analytics Azure Machine Learning Azure App Service Event Hubs IoT Hub Power BI
Never build the same code twiceGive your monorepo the smarts to actually save you time Get Started Seriously, never build more than onceBuilding once is painful enough! Lage will remember what is done before and skip any work that is not needed. Lage even skips the work based on your changes… really!
Design, Code and Play Games on MakeCode Arcade Devices
We're excited to announce our first preview release aligning with React Native 0.62! As a preview release, we will try our best not to make breaking changes, but still have a few bumps to sort out before we're ready for release. You can now start trying out the 0.62-preview of React Native for Windows! A similar upgrade for React Native for macOS is in progress. Stay tuned for the next update! Wha
Take your apps across PC, Xbox, Surface Tablets, and dual-screens with our robust Windows extension to React Native. React Native for Windows brings React Native support for the Windows SDK. With this, you can use JavaScript to build native Windows apps for all devices supported by Windows 10 and higher including PCs, tablets, 2-in-1s, Xbox, Mixed reality devices, etc. Some build-time tools will s
Skip to the content. Forecasting Best Practices Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehen
Modern and Seamless UIs WinUI makes it easy to build modern, seamless UIs that feel natural to use on every Windows device. It embodies Fluent Design to enable intuitive, accessible, and powerful experiences and the latest user interface patterns. Unmatched Native Performance WinUI is powered by a highly optimized C++ core that delivers blistering performance, long battery life, and responsive int
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