LUIS Samples

Welcome to the Language Understanding (LUIS) samples repository. LUIS allows your application to understand what a person wants in their own words. LUIS uses machine learning to allow developers to build applications that can receive user input in natural language and extract meaning from it.

Create your Azure LUIS service

Use the Deploy to Azure button to quickly create an Azure LUIS service. You get one free LUIS service per account. The free service has a sku of F0. The basic tier has a sku of S0.

Examples by language

Example	CSharp	Java	Node.js	Javascript	Python	PHP	Ruby	JSON
*Bot Integration sample - hotel finder	✔		✔
Bot Integration sample - HomeAutomation	✔		✔
Bot Integration sample - HomeAutomation & Application Insights			✔
Add an utterance to app model	✔	✔	✔	✔	✔	✔	✔
Send utterance to endpoint	✔			✔	✔	✔	✔
Azure function to LUIS endpoint	✔
Backup all apps in Subscription			✔
Build app programmatically			✔
Upload utterances from query log			✔
Upload utterances from exported app			✔
Add list entity			✔
*Notes app sample	✔
App model definition - Bookflight								✔
App model definition - Colors								✔
App model definition - IoT								✔
Phrase lists								✔
Bing Spell Check				✔
Azure function with application insights	✔
Botframework v4 - endpoint			Typescript

* = example demonstrates complete cycle: create, train, publish, query

Examples by usage

Example	Demonstrates
Bot Integration sample - hotel finder	Bot Framework SDK, Create-Train-Publish-Query
Bot Integration sample - HomeAutomation	Web app bot
Bot Integration sample - HomeAutomation & Application Insights	Web app bot, Application Insights
Add an utterance to app model	Authoring API
Send utterance to endpoint	Endpoint API, Public app
Azure function to LUIS endpoint	Endpoint API
Backup all apps in Subscription	Authoring API
Build app programmatically	Authoring API
Upload utterances from query log	Authoring API
Upload utterances from exported app	Authoring API
Notes app sample	Create-Train-Publish-Query, Prebuilt domain
App model definition - Bookflight	Hierarchical entity, Composite entity, List entity, datetimeV2 prebuilt entity, number prebuilt entity, upload labeled utterance
App model definition - Colors	Phrase list feature
App model definition - IoT	Prebuilt domain
Phrase lists	Phrase list feature, Hierarchical entity, datetimeV2 prebuilt entity, number prebuilt entity
Bing Spell Check	Public App
Azure function with application insights	Azure function, Application Insights
Add list entity	List entity, train, query
Botframework v4 - endpoint	Uses NPM package botframework-luis, version 4.0.0-alpha2

Interactive app

Ask LUIS to turn on the lights in this interactive demonstration.

References

• LUIS Docs
• Authoring API docs
• Endpoint API docs
• LUIS .Net SDK
• Bot Framework
• Bot Builder Samples
• Azure REST API Specifications:LUIS swagger files
• BotBuilder v4, Nodejs, .Net. Coming soon: Python & Java
• BotBuilder v4 LUIS libraries: Nodejs NPM package, .Net NuGet package

Videos

• Introduction to LUIS
• Advanced learning with LUIS
• Channel 9 Deep Dive into LUIS and Chatbots

LUIS with Bot framework Blog

• blog.botframework.com

Related Projects

• Prebuilt entity recognizer
• Azure Code Samples for LUIS
• Universal Language Intelligence Service - Nodejs: A wrapper for the Microsoft LUIS cognitive that provides universal language support (after training) using the bing translate api
• Microsoft Cognitive Services control for Microsoft Bot Builder - C# & Nodejs: The cognitive services control makes consuming different Microsoft Cognitive Services easy for bots developed using Microsoft Bot Builder SDK. The control is available for C# and Node.js SDKs.
• Activate Azure with Intelligent Apps - C#: Fabrikam Investment Bank Customer Service uses LUIS
• LUIS Console Application Sample - C#
• Adaptive Cards

Community Projects

If you find a open-source project or sample using LUIS, submit a PR for the community-projects.md file.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.