Get started using Amazon Bedrock in SageMaker Unified Studio - Amazon SageMaker
Step 1: Explore Amazon Bedrock foundation modelsStep 2: Chat with a model in the chat playgroundStep 3: Create a chat agent appAdditional capabilities

Get started using Amazon Bedrock in SageMaker Unified Studio

Amazon Bedrock in SageMaker Unified Studio offers multiple playgrounds that allow you to easily access and experiment with Amazon Bedrock models. With the chat playground, you can chat with a model through text and image prompts. With the image and video playground, you can use a compatible model to generate and edit images and videos.

In addition to the playgrounds, you can also use Amazon Bedrock in SageMaker Unified Studio to create chat agent apps and flows apps. A chat agent app allows users to create a custom app that interacts with a Amazon Bedrock model through a conversational interface. You can enhance chat agent apps with Amazon Bedrock features such as data sources and guardrails and share the app with other users. A flows app allows users to link together prompts, foundation models, and other components to create a visual, end-to-end generative AI workflow.

The following section will walk you through the basic functionalities of Amazon Bedrock in SageMaker Unified Studio. First, you will select a model from the model catalog and chat with it in the chat playground. Then, you will create a chat agent app that can create playlists for a rock and pop radio station. For more in-depth information on other Amazon Bedrock features you can use with Amazon Bedrock in SageMaker Unified Studio, see Amazon Bedrock in SageMaker Unified Studio.

Step 1: Explore Amazon Bedrock foundation models

The following section shows how to select a model from the model catalog in the Amazon Bedrock in SageMaker Unified Studio playground. You can also access the model catalog from inside your projects. The models you have access to in your projects might be different from those you can access in the playground, based on your administrator's settings. To check which models you can access in a project, open or create a project, and then select Models in the navigation pane to open the model catalog.

To open the model catalog in the playground

  1. Navigate to the Amazon SageMaker landing page by using the URL from your admininstrator.

  2. Access Amazon SageMaker using your IAM or single sign-on (SSO) credentials. For more information, see Access Amazon SageMaker Unified Studio.

  3. At the top of the page, choose Discover.

  4. Under Data and model catalog, choose Amazon Bedrock models. This opens the model catalog in the Amazon Bedrock in SageMaker Unified Studio playground.

  5. (Optional) Choose Group by: Modality and select Provider to sort the list by model provider.

  6. Choose a model from the list of models that you have access to. For information about a model, choose View full model details in the information panel. If you don't have access to an appropriate model, contact your administrator. Some features may not be supported by all models.

If you are ready to begin chatting with the model you chose, proceed to the following step.

Step 2: Chat with a model in the chat playground

In this section you will chat with your selected model in the chat playground. You chat by sending a prompt to the model and receiving a response. For more information, see Experiment with the Amazon Bedrock playgrounds.

Warning

Generative AI may give inaccurate responses. Avoid sharing sensitive information. Chats may be visible to others in your organization.

To chat with a model

  1. In the chat playground, enter What is Avebury stone circle? in the Enter prompt text box.

  2. (Optional) If the model you chose is a reasoning model, you can choose Reason to have the model include its reasoning in the reponse. For more information, see Enhance model responses with model reasoning in the Amazon Bedrock user guide.

  3. Press Enter on your keyboard, or choose the run button, to send the prompt to the model. The response from the model will be generated in the playground.

  4. Continue chatting with the model by entering the prompt Is there a museum there?.

    The model will use the previous prompt as context for generating its response to this question.

  5. (Optional) Compare the output from multiple models, or shared apps.

    1. In the playground, turn on Compare mode. This will open two panes side-by-side.

    2. In each panes, select a model that you want to compare. If you want to use a shared app, select App in Type and then select the app in App.

    3. Enter a prompt in the text box and run the prompt. The output from each model is shown in their respective panes. You can choose the copy icon to copy the prompt or model response to the clipboard.

    4. (Optional) Choose Add chat window to add a third window. You can compare up to 3 models or apps.

    5. Turn off Compare mode to stop comparing models.

  6. Choose Reset to start a new chat with the model.

Step 3: Create a chat agent app

In this section you will learn how to create a simple Amazon Bedrock in SageMaker Unified Studio chat agent app that creates playlists for a radio station and shares the dates and locations of upcoming shows.

To create an Amazon Bedrock chat agent app

  1. On the Amazon SageMaker home page, choose Build chat agent app to create a new chat agent app. The Select or create a new project to continue dialog box opens.

  2. In the Select or create a new project to continue dialog box, do one of the following:

    • If you want to use a new project, follow the instructions at Step 2 - Create a new project. For the Project profile in step 1, choose Generative AI application development.

    • If you want to use an existing project, select the project that you want to use and then choose Continue.

  3. On the app creation page, an untitled app will automatically be created for you. In Untitled App - nnnn, enter Radio show as the name for your app.

  4. In the Configs pane, do the following:

    1. For Model, select a model that supports Guardrails, Data, and Function components. The description of the model tells you the components that a model supports. For full information about the model, choose View full model details in the information panel. For more information, see Find serverless models with the model catalog. If you don't have access to an appropriate model, contact your administrator. Different models might not support all features.

    2. For Enter a system instruction in Instructions for chat agent & examples, enter You are a chat agent app that creates 2 hour long playlists for a radio station that plays rock and pop music..

    3. In the UI section, update the user interface for the app by doing the following:

      1. In Hint text for empty chat enter Hi! I'm your radio show playlist creator..

      2. In Hint text for user input enter Enter a prompt that describes the playlist that you want..

      3. In Quick start prompts choose Edit.

      4. Choose Reset to clear the list of quick start prompts

      5. For Quick-start prompt 1, enter Create a playlist of pop music songs..

      6. (Optional). Enter quick start prompts of your choice in the remaining quick start prompt text boxes.

      7. Choose Back to configs.

  5. Choose Save to save the current working draft of your app.

  6. In the Quick start prompts section of the Preview pane, run the quick start prompt that you just created by choosing the prompt.

    The app shows the prompt and the response from the model in the Preview pane.

  7. In the prompt text box (the text should read Enter a prompt that describes the playlist that you want), enter Create a playlist of songs where each song on the list is related to the next song, by musician, bands, or other connections. Be sure to explain the connection from one song to the next. .

  8. Choose the run button (or press Enter on your keyboard) to send the prompt to the model.

You have now created a basic chat agent app that can create playlists for a rock and pop radio station. You can experiment with sending prompts and receiving responses from your chat agent app.

Additional capabilities

Amazon Bedrock in SageMaker Unified Studio offers many additional capabilities to the ones covered in this walkthrough, including the following.

  • You can customize and influence model behavior using inference parameters and system prompts. For more information, see What is a prompt?.

  • You can enhance your chat agent app by adding data sources and guardrails. For more information, see Build a chat agent app.

  • You can share your chat agent app with other users and use it as a component in a flows app. For more information, see Share a chat agent app and Deploy a chat agent app.

  • You can create a flows app to link together different components such as knowledge bases and reusable prompts. For more information, see Build a flow app.