Teams AI library quick start guide

आलेख
11/12/2024

Get started with Teams AI library using the LightBot sample, which is designed to help you through the process of creating apps that can control lights, such as turning them on and off using Teams AI library. The bot uses the gpt-3.5-turbo model to chat with Microsoft Teams users and respond in a polite and respectful manner, staying within the scope of the conversation.

Prerequisites

To get started, ensure that you have the following tools:

Install	For using...
Visual Studio Code	JavaScript, TypeScript, and Python build environments. Use the latest version.
Teams Toolkit	Microsoft Visual Studio Code extension that creates a project scaffolding for your app. Use the latest version.
Git	Git is a version control system that helps you manage different versions of code within a repository.
Node.js	Back-end JavaScript runtime environment. For more information, see Node.js version compatibility table for project type.
Microsoft Teams	To collaborate with everyone, you work with them through apps for chat, meetings, and call all in one place.
OpenAI or Azure OpenAI	First create your OpenAI API key to use OpenAI's GPT. If you want to host your app or access resources in Microsoft Azure, you must create an Azure OpenAI service.
Microsoft Edge (recommended) or Google Chrome	A browser with developer tools.
Microsoft 365 developer account	Access to Teams account with the appropriate permissions to install an app and enable custom Teams apps and turn on custom app uploading.

If you've already run the samples before or encountered a runtime error, follow these steps to start fresh:

Check all the .env and env/.env.*.* files in the sample and delete any automatically populated values to ensure that Teams Toolkit generates new resources for you.
If you don’t want Teams Toolkit to generate the app ID and password, update the BOT_ID and BOT_PASSWORD in the .env file with your own values.
Remove values or leave the values blank for SECRET_BOT_PASSWORD and TEAMS_APP_UPDATE_TIME in the .env file to avoid conflicts.

Teams Toolkit automatically provisions BOT_ID and BOT_PASSWORD resources. If you want to use your own resources, you need to manually add them to the .env file. Teams Toolkit doesn't auto-generate the following resources:

An Azure OpenAI or OpenAI key
A database or similar storage options

Build and run the sample app

Get started with Teams AI library using the LightBot sample. It enables your computer’s localhost to quickly execute a Teams AI library-based sample.

Go to the sample.
Run the following command to clone the repository:

Windows Command Prompt
```
git clone https://github.com/microsoft/teams-ai.git
```
Go to Visual Studio Code.
Select File > Open Folder.
Go to the location where you cloned teams-ai repo and select the teams-ai folder.
Select Select Folder.
Select View > Terminal. A terminal window opens.
In the terminal window, run the following command to go to the js folder:

terminal
```
cd .\js\
```
Run the following command to install dependencies:

terminal
```
yarn install
```
Run the following command to build dependencies:

terminal
```
yarn build
```
After the dependencies are installed, select File > Open Folder.
Go to teams-ai > js > samples> 03.ai-concepts> c.actionMapping-lightBot and select Select Folder. All the files for the LightBot sample are listed under the EXPLORER section in Visual Studio Code.

Update the following steps based on the AI services you select.

OpenAI key
Azure OpenAI

Go to the env folder and update the following code in ./env/.env.local.user file:

text
```
 SECRET_OPENAI_KEY=<your OpenAI key>
```

Go to the infra folder and ensure that the following lines in the azure.bicep file are commented out:

Bicep

    // {
    //   name: 'AZURE_OPENAI_KEY'
    //   value: azureOpenAIKey
    // }
    // {
    //   name: 'AZURE_OPENAI_ENDPOINT'
    //   value: azureOpenAIEndpoint
    // }

Go to the env folder and update the following code in ./env/.env.local.user file:

text

SECRET_AZURE_OPENAI_KEY=<your Azure OpenAI key>
SECRET_AZURE_OPENAI_ENDPOINT=<your Azure OpenAI Endpoint>

Go to the teamsapp.local.yml file and modify the last step to use Azure OpenAI variables:

YAML

   - uses: file/createOrUpdateEnvironmentFile
     with:
      target: ./.env
      envs:
      BOT_ID: ${{BOT_ID}}
      BOT_PASSWORD: ${{SECRET_BOT_PASSWORD}}
      #OPENAI_KEY: ${{SECRET_OPENAI_KEY}}
      AZURE_OPENAI_KEY: ${{SECRET_AZURE_OPENAI_KEY}}
      AZURE_OPENAI_ENDPOINT: ${{SECRET_AZURE_OPENAI_ENDPOINT}}

Go to the infra folder and ensure that the following lines in the azure.bicep file are commented out:

Bicep
```
    // {
    //  name: 'OPENAI_KEY'
    //  value: openAIKey
    // }
```

Go to infra > azure.parameters.json and replace the lines from 20 to 22 with the following code:

JSON

   "azureOpenAIKey": {
   "value": "${{SECRET_AZURE_OPENAI_KEY}}"
   },
   "azureOpenAIEndpoint": {
   "value": "${{SECRET_AZURE_OPENAI_ENDPOINT}}"
   }

From the left pane, select Teams Toolkit.
Under ACCOUNTS, sign-in to the following:
- Microsoft 365 account
- Azure account
To debug your app, select F5.

A browser tab opens the Teams web client to add the bot to your tenant.
Select Add.

When the app is added, a dialog to select the required scope appears.
Select Open to open the app in personal scope.

Alternatively, you can either search and select the required scope or select a channel, chat, or meeting from the list, and move through the dialog to select Go.

A chat window opens.
In the message compose area, send a message to invoke the bot.

नोट

If you're building a bot for the first time, it's recommended to use Teams Toolkit extension for Visual Studio Code to build a bot, see build your first bot app using JavaScript.

Prerequisites

To get started, ensure that you have the following tools:

Install	For using...
Visual Studio	C Sharp build environments. Use the latest version.
Teams Toolkit	Microsoft Visual Studio Code extension that creates a project scaffolding for your app. Use the latest version.
Git	Git is a version control system that helps you manage different versions of code within a repository.
Microsoft Teams	To collaborate with everyone, you work with them through apps for chats, meetings, and calls all in one place.
OpenAI or Azure OpenAI	First create your OpenAI API key to use OpenAI's GPT. If you want to host your app or access resources in Microsoft Azure, you must create an Azure OpenAI service.
Microsoft Edge (recommended) or Google Chrome	A browser with developer tools.
Microsoft 365 developer account	Access to Teams account with the appropriate permissions to install an app and enable custom Teams apps and turn on custom app uploading.

If you've already run the samples before or encountered a runtime error, follow these steps to start fresh:

Check all the .env and env/.env.*.* files in the sample and delete any automatically populated values to ensure that Teams Toolkit generates new resources for you.
If you don’t want Teams Toolkit to generate the app ID and password, update the MicrosoftAppId and MicrosoftAppPassword in the .env file with your own values.
Remove values or leave the values blank for SECRET_BOT_PASSWORD and TEAMS_APP_UPDATE_TIME in the .env file to avoid conflicts.

Teams Toolkit automatically provisions MicrosoftAppId and MicrosoftAppPassword resources. If you want to use your own resources, you need to manually add them to the .env file. Teams Toolkit doesn't auto-generate the following resources:

An Azure OpenAI or OpenAI key
A database or similar storage options

Build and run the sample app

Go to the sample.

Clone the repository to test the sample app.

git clone https://github.com/microsoft/teams-ai.git

Go to the dotnet folder.
```
cd teams-ai/dotnet
```
Go to the folder where you cloned the repository and select 04.ai.c.actionMapping.lightBot.
Select LightBot.sln. The solution opens in Visual Studio.

In Visual Studio, update your OpenAI-related settings in the appsettings.Development.json file.

JSON

"Azure": {
"OpenAIApiKey": "<your-azure-openai-api-key>",
"OpenAIEndpoint": "<your-azure-openai-endpoint>"
},

Go to Prompts/sequence/skprompt.txt and update the following code in skprompt.txt file:

skprompt.txt

The following is a conversation with an AI assistant. 
The assistant can turn a light on or off.
The assistant must return the following JSON structure:

{"type":"plan","commands":[{"type":"DO","action":"<name>","entities":{"<name>":<value>}},{"type":"SAY","response":"<response>"}]}

The following actions are supported:

- LightsOn
- LightsOff
- Pause time=<duration in ms>
- LightStatus

The lights are currently {{getLightStatus}}.

Always respond in the form of a JSON based plan. Stick with DO/SAY.

In the debug dropdown menu, select Dev Tunnels > Create a Tunnel...
Select the Account to use to create the tunnel. Azure, Microsoft Account (MSA), and GitHub accounts are supported. Update the following options:
1. Name: Enter a name for the tunnel.
2. Tunnel Type: Select Persistent or Temporary.
3. Access: Select Public.
4. Select OK. Visual Studio displays a confirmation message that a tunnel is created.
The tunnel you created is listed under Dev Tunnels > (name of the tunnel).
Go to Solution Explorer and select your project.
Right-click menu and select Teams Toolkit > Prepare Teams App Dependencies.

If prompted, sign in to your Microsoft 365 account. You receive a message that Teams app dependencies are successfully prepared.
Select OK.
Select F5 or select Debug > Start.
Select Add to add the bot to your tenant.

When the app is added, a dialog to select the required scope appears.
Select Open to open the app in personal scope.

Alternatively, you can either search and select the required scope or select a channel, chat, or meeting from the list, and move through the dialog to select Go.

A chat window opens.
In the message compose area, send a message to invoke the bot.

You can also deploy the samples to Azure using Teams Toolkit. To deploy, follow these steps:

In Visual Studio, go to Solution Explorer and select your project.
Right-click menu and select Teams Toolkit > Provision in the Cloud. Toolkit provisions your sample to Azure.
Right-click menu and select Teams Toolkit > Deploy to the Cloud.

Prerequisites

To get started, ensure that you have the following tools:

Install	For using...
Visual Studio Code	JavaScript, TypeScript, and Python build environments. Use the latest version.
Teams Toolkit	Microsoft Visual Studio Code extension that creates a project scaffolding for your app. Use the latest version.
Python	Python is an interpreted and object-oriented programming language with dynamic semantics. Use versions between 3.8 to 4.0.
Poetry	Dependency management and packaging tool for Python.
Python VSCode Extension	Provides rich support for Python on VSCode.
Git	Git is a version control system that helps you manage different versions of code within a repository.
Microsoft Teams	To collaborate with everyone, you work with them through apps for chats, meetings, and calls all in one place.
OpenAI or Azure OpenAI	First create your OpenAI API key to use OpenAI's GPT. If you want to host your app or access resources in Microsoft Azure, you must create an Azure OpenAI service.
Microsoft Edge (recommended) or Google Chrome	A browser with developer tools.
Microsoft 365 developer account	Access to Teams account with the appropriate permissions to install an app and enable custom Teams apps and turn on custom app uploading.

If you've already run the samples before or encountered a runtime error, follow these steps to start fresh:

Check all the .env and env/.env.*.* files in the sample and delete any automatically populated values to ensure that Teams Toolkit generates new resources for you.
If you don’t want Teams Toolkit to generate the app ID and password, update the BOT_ID and BOT_PASSWORD in the .env file with your own values.
Remove values or leave the values blank for SECRET_BOT_PASSWORD and TEAMS_APP_UPDATE_TIME in the .env file to avoid conflicts.

An Azure OpenAI or OpenAI key
A database or similar storage options

Build and run the sample app

Go to the sample.

Clone the repository to test the sample app.

git clone https://github.com/microsoft/teams-ai.git

Go to the python folder.
```
cd teams-ai/python
```
Go to the folder where you cloned the repository and select 04.ai.c.actionMapping.lightBot. All the files for the LightBot sample are listed under the EXPLORER section in Visual Studio Code.
Under EXPLORER, duplicate the sample.env file and update the duplicate file to .env.
- OpenAI key
- Azure OpenAI
Go to the env folder and update the following code in ./env/.env.local.user file:

text
```
SECRET_OPENAI_KEY=<your OpenAI key>
```
Go to the env folder and update the following code in ./env/.env.local.user file:

text
```
SECRET_AZURE_OPENAI_KEY=<your Azure OpenAI key>
SECRET_AZURE_OPENAI_ENDPOINT=<your Azure OpenAI Endpoint>
```
To install the following dependencies, go to View > Terminal and run the following commands:

Dependencies Command

python-dotenv pip install python-dotenv

load-dotenv pip install load-dotenv

teams-ai pip install teams-ai

botbuilder-core pip install botbuilder-core
Update config.json and bot.py with your model deployment name.
Go to View > Command Palette... or select Ctrl+Shift+P.
Enter Python: Create Environment to create a virtual environment.
To debug your app, select F5.

A browser tab opens the Teams web client to add the bot to your tenant.
Select Add.

When the app is added, a dialog to select the required scope appears.
Select Open to open the app in personal scope.

Alternatively, you can either search and select the required scope or select a channel, chat, or meeting from the list, and move through the dialog to select Go.

A chat window opens.
In the message compose area, send a message to invoke the bot.

Dependencies	Command
python-dotenv	pip install python-dotenv
load-dotenv	pip install load-dotenv
teams-ai	pip install teams-ai
botbuilder-core	pip install botbuilder-core

Additional tools

You can also use the following tools to run and set up a sample:

Teams Toolkit CLI: You can use the Teams Toolkit CLI to create and manage Teams apps from the command line. For more information, see Teams Toolkit CLI set up instructions.
Bot Framework Emulator: The Bot Framework Emulator is a desktop application that allows you to test and debug your bot locally. You can connect to your bot by entering the bot’s endpoint URL and Microsoft app ID and password. You can then send messages to your bot and see its responses in real-time. For more information, see Bot Framework Emulator set up instructions.
Manual setup: If you prefer to set up your resources manually, you can do so by following the instructions provided by the respective services. For more information, see manual set up instructions.

Next step

Choose one of the following as a next step:

If you want to learn how to use Teams AI library to create an AI-powered bot, select the following:
Build with Teams AI library

If you want to build a a custom engine agent using Teams Toolkit, select the following:
Build a custom engine agent

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अतिरिक्त संसाधन

दस्तावेज़ीकरण

Core Capabilities of Teams AI Library - Teams

In this article, learn more about Teams AI library capabilities, bot logic, Adaptive Cards capabilities, and message extension query.
Tutorial - Build Custom Engine Agent - Teams

Learn how to create a custom engine agent using Teams AI library and Teams Toolkit, set up data in Azure OpenAI, and configure custom engine agent.
Use Teams AI Library to Build Apps/Bots - Teams

Learn how to create an app using Teams AI library with AI component, storage, register data source, migrate bot, prompts, and actions.
Introduction to Teams AI library - Teams

Learn about Teams AI library, Teams-centric component scaffolding, natural language modeling, prompt engineering, LLM, action planner, assistants API, augmentation.
Assistants API quick start guide - Teams

In this module, learn how to quickly try the Assistants API with Teams AI library in Math tutor assistant sample using OpenAI Code Interpreter tool.
Custom engine agent user experience - Teams

Learn about the user experience for custom engine agent
Build a custom engine agent using Teams AI library and Teams Toolkit - Teams

Learn how to build a custom engine agent with Teams AI library and set up, build, and deploy a bot app with Teams Toolkit.
Build a basic AI Chatbot in Teams - Teams

Learn how to build and customize a basic AI chatbot using Teams AI library in Teams Toolkit, about bot app source code and workflow.

प्रशिक्षण

प्रशिक्षण पथ

Build and deploy apps for Microsoft Teams using Teams Toolkit for Visual Studio Code - Training

Teams Toolkit is an extension for Visual Studio Code and Visual Studio 2022. It helps developers create and deploy Teams apps with integrated identity, cloud storage and other services across Microsoft 365 and Azure. In this Learn path, you'll learn how to build a Microsoft Teams app using Teams Toolkit for Visual Studio Code.

Certification

Microsoft प्रमाणित: Azure AI Fundamentals - Certifications

AI समाधान बनाने के लिए Microsoft Azure के सॉफ़्टवेयर और सेवाओं के विकास से संबंधित मौलिक AI अवधारणाओं का प्रदर्शन करें।

इसके माध्यम से साझा किया गया

Teams AI library quick start guide

Prerequisites

Build and run the sample app

Prerequisites

Build and run the sample app

Prerequisites

Build and run the sample app

Additional tools

Next step

अतिरिक्त संसाधन