Build an AI agent bot in Teams

An AI agent in Microsoft Teams is a conversational chatbot that uses Large Language Models (LLMs) to interact with the users. It understands user intentions and selects a sequence of actions, enabling the chatbot to complete common tasks.

Prerequisites

Create a new AI agent project

1. Open Visual Studio Code.

2. Select the Teams Toolkit icon in the Visual Studio Code Activity Bar

3. Select Create a New App.

   

4. Select Custom Engine Agent.

   

5. Select AI Agent.

   

6. To build an app, select any of the following options:

   • Build new
   • Assistants API

   1. Select Build New.

      

   2. Select JavaScript.

      

   3. By default OpenAI service gets selected, you can optionally enter the credentials to access OpenAI. Select Enter.

      

   4. Select Default folder.

      

      To change the default location, follow these steps:

      1. Select Browse.
      2. Select the location for the project workspace.
      3. Select Select Folder.

   5. Enter an app name for your app and then select the Enter key.

      

      You've successfully created your AI agent bot.

      

   6. Under EXPLORER, go to the env > .env.testtool.user file.

   7. Update the following values:

      • SECRET_AZURE_OPENAI_API_KEY=<your-key>
      • AZURE_OPENAI_ENDPOINT=<your-endpoint>
      • AZURE_OPENAI_DEPLOYMENT_NAME=<your-deployment>

      

   8. To debug your app, select the F5 key or from the left pane, select Run and Debug (Ctrl+Shift+D) and then select Debug in Test Tool (Preview) from the dropdown list.

      

   Test Tool opens the bot in a webpage.

   

   Take a tour of the bot app source code

   Folder	Contents
   .vscode	Visual Studio Code files for debugging.
   appPackage	Templates for the Teams app manifest.
   env	Environment files.
   infra	Templates for provisioning Azure resources.
   src	The source code for the app.

   The following files can be customized and they demonstrate an example of implementation to get you started:

   File	Contents
   src/index.js	Sets up the bot app server.
   src/adapter.js	Sets up the bot adapter.
   src/config.js	Defines the environment variables.
   src/prompts/planner/skprompt.txt	Defines the prompt.
   src/prompts/planner/config.json	Configures the prompt.
   src/prompts/planner/actions.json	Defines the actions.
   src/app/app.js	Handles business logics for the AI Agent.
   src/app/messages.js	Defines the message activity handlers.
   src/app/actions.js	Defines the AI actions.

   The following are Teams Toolkit specific project files. For more information on how Teams Toolkit works, see a complete guide on GitHub:

   File	Contents
   teamsapp.yml	This is the main Teams Toolkit project file. The project file defines the properties and configuration stage definitions.
   teamsapp.local.yml	This overrides teamsapp.yml with actions that enable local execution and debugging.
   teamsapp.testtool.yml	This overrides teamsapp.yml with actions that enable local execution and debugging in Teams App Test Tool.

Create an AI agent using Teams AI library

Build new

Teams AI library provides a comprehensive flow that simplifies the process of building your own AI agent. The important concepts that you need to understand are as follows:

• Actions: An action is an atomic function that is registered to the AI system.
• Planner: The planner receives the user's request, which is in the form of a prompt or prompt template, and returns a plan to fulfill it. This is achieved by using AI to mix and match atomic functions, known as actions, that are registered to the AI system. These actions are recombined into a series of steps that complete a goal.
• Action Planner: Action Planner uses an LLM to generate plans. It can trigger parameterized actions and send text based responses to the user.

Build with Assistants API

Assistants API from OpenAI simplify the development effort of creating an AI agent. OpenAI as a platform offers prebuilt tools such as Code Interpreter, Knowledge Retrieval, and Function Calling that simplifies the code you need to write for common scenarios.

Customize the app template

Customize prompt augmentation

The SDK provides a functionality to augment the prompt.

• The actions, which are defined in the src/prompts/planner/actions.json file, are inserted into the prompt. This allows the LLM to be aware of the available functions.
• An internal piece of prompt text is inserted into the prompt to instruct LLM to determine which functions to call based on the available functions. This prompt text orders LLM to generate the response in a structured json format.
• The SDK validates the LLM response and lets LLM correct or refine the response if the response is in wrong format.

In the src/prompts/planner/config.json file, configure augmentation.augmentation_type. The options are:

• Sequence: Suitable for tasks that require multiple steps or complex logic.
• Monologue: Suitable for tasks that require natural language understanding and generation, and more flexibility and creativity.

Build new add functions

• In the src/prompts/planner/actions.json file, define your actions schema.

  [
      ...
      {
          "name": "myFunction",
          "description": "The function description",
          "parameters": {
              "type": "object",
              "properties": {
                  "parameter1": {
                      "type": "string",
                      "description": "The parameter1 description"
                  },
              },
              "required": ["parameter1"]
          }
      }
  ]
  

• In the src/app/actions.ts file, define the action handlers.

  // Define your own function
  export async function myFunction(context: TurnContext, state: TurnState, parameters): Promise<string> {
    // Implement your function logic
    ...
    // Return the result
    return "...";
  }
  

• In the src/app/app.ts file, register the actions.

  app.ai.action("myFunction", myFunction);
  

Customize assistant creation

The src/creator.ts file creates a new OpenAI Assistant. You can customize the assistant by updating the parameters including instruction, model, tools, and functions.

Build with Assistants API add functions

When the assistant provides a function and its arguments for execution, the SDK aligns this function with a preregistered action. It later activates the action handler and submits the outcome back to the assistant. To integrate your functions, register the actions within the app.

• In the src/app/actions.ts file, define the action handlers.

  // Define your own function
  export async function myFunction(context: TurnContext, state: TurnState, parameters): Promise<string> {
    // Implement your function logic
    ...
    // Return the result
    return "...";
  }
  

• In the src/app/app.ts file, register the actions.

  app.ai.action("myFunction", myFunction);
  

See also

Teams AI library