Amazon Bedrock Studio: Accelerate generative AI development
AWS is pleased to present to the public today Amazon Bedrock Studio, a brand-new web-based generative artificial intelligence (generative AI) development environment. By offering a fast prototyping environment with essential Amazon Bedrock technologies like Knowledge Bases, Agents, and Guardrails, Amazon Bedrock Studio speeds up the creation of generative AI applications.
Summary
A brand-new SSO-enabled web interface called Amazon Bedrock Studio offers developers from all over an organisation the simplest way to work together on projects, experiment with large language models (LLMs) and other foundation models (FMs), and refine generative AI applications. It simplifies access to various Foundation Models (FMs) and developer tools in Bedrock and provides a fast prototyping environment. AWS administrators can set up one or more workspaces for their company in the AWS Management Console for Bedrock and allow individuals or groups to utilise the workspace in order to enable Bedrock Studio.
In only a few minutes, begin developing applications
Using their company credentials (SSO), developers at your firm can easily log in to the Amazon Bedrock Studio online experience and begin experimenting with Bedrock FMs and application development tools right away. Bedrock Studio provides developers with a safe haven away from the AWS Management Console in which to utilise Bedrock features like Knowledge Bases, Amazon Guardrails, and Agents.
Create flexible generative AI applications
With Amazon Bedrock Studio, developers can gradually improve the accuracy and relevance of their generative AI applications. To acquire more accurate responses from their app, developers can begin by choosing an FM that is appropriate for their use case and then iteratively enhance the prompts. Then, they can add APIs to obtain the most recent results and use their own data to ground the app to receive more pertinent responses. Bedrock Studio streamlines and reduces the complexity of app development by automatically deploying pertinent AWS services (such Knowledge Bases and Agents). Additionally, enterprise use cases benefit from a secure environment because data and apps are never removed from the assigned AWS account.
Work together on projects with ease
Teams may brainstorm, test, and improve their generative AI applications together in Amazon Bedrock Studio‘s collaborative development environment. In addition to creating projects and inviting peers, developers may also share apps and insights and receive immediate feedback on their prototypes. Access control is a feature of Bedrock Studio projects that guarantees that only members with permission can use the apps and resources inside of a project.
Encourage creativity without worrying about infrastructure management
Knowledge bases, agents, and guardrails are examples of managed resources that are automatically installed in an AWS account when developers construct applications in Amazon Bedrock Studio. Because these Bedrock resources are always available and scaleable as needed, they don’t need to worry about the underlying compute and storage infrastructure. Furthermore, the Bedrock API makes it simple to access these resources. This means that by utilising the Bedrock API, you can easily combine the generative AI apps created in Bedrock Studio with their workflows and processes.
Take precautions to ensure the finest answers
To make sure their programme doesn’t provide incorrect output, developers can install content filters and create guardrails for both user input and model replies. To acquire the desired results from their apps, they can add prohibited topics and configure filtering levels across different categories to customise the behaviour of Guardrail.
As a developer, you can now log into Bedrock Studio and begin experimenting with your company’s single sign-on credentials. Within Bedrock Studio, you may create apps with a variety of high-performing models, assess them, and distribute your generative AI creations. You can enhance a model’s replies by following the stages that the user interface walks you through. You can play around with the model’s settings, set limits, and safely integrate tools, APIs, and data sources used by your business. Working in teams, you can brainstorm, test, and improve your generative AI apps without needing access to the AWS Management Console or sophisticated machine learning (ML) knowledge.
You can be sure that developers will only be able to utilise the functionality offered by Bedrock Studio and won’t have wider access to AWS infrastructure and services as an Amazon Web Services (AWS) administrator.
Let me now walk you through the process of installing Amazon Bedrock Studio.
Use Amazon Bedrock Studio to get started
You must first create an Amazon Bedrock Studio workspace as an AWS administrator, after which you must choose and add the users you wish to grant access to the workspace. You can provide the relevant individuals with the workspace URL once it has been built. Users with the necessary permissions can start developing generative AI apps, create projects inside their workspace, and log in using single sign-on.
Establish a workstation in Amazon Bedrock Studio
Select Bedrock Studio from the bottom left pane of the Amazon Bedrock dashboard.
You must use the AWS IAM Identity Centre to set up and secure the single sign-on integration with your identity provider (IdP) before you can create a workspace. See the AWS IAM Identity Centre User Guide for comprehensive instructions on configuring other IdPs, such as Okta, Microsoft Entra ID, and AWS Directory Service for Microsoft Active Directory. You set up user access using the IAM Identity Centre default directory for this demo.
Next, select Create workspace, fill in the specifics of your workspace, and create any AWS Identity and Access Management (IAM) roles that are needed.
Additionally, you have the option to choose the workspace’s embedding models and default generative AI models. Select Create once you’re finished.
Choose the newly formed workspace next.
Next, pick the users you wish to grant access to this workspace by choosing User management and then Add users or groups.
You can now copy the Bedrock Studio URL and share it with your users from the Overview tab.
Create apps for generative AI using Amazon Bedrock Studio
Now that the Bedrock Studio URL has been provided, builders can access it and log in using their single sign-on login credentials. Here at Amazon Bedrock Studio, welcome! Allow me to demonstrate how to select among top-tier FMs, import your own data, use functions to call APIs, and use guardrails to secure your apps.
Select from a number of FMs that lead the industry
By selecting examine, you may begin choosing from among the FMs that are offered and use natural language prompts to examine the models.
If you select Build, you may begin developing generative AI applications in playground mode, play around with model settings, refine your application’s behaviour through iterative system prompts, and create new feature prototypes.
Bring your personal data
Using Bedrock Studio, you can choose from a knowledge base built in Amazon Bedrock or securely bring your own data to customise your application by supplying a single file.
Make API calls using functions to increase the relevancy of model responses
When replying to a prompt, the FM can dynamically access and incorporate external data or capabilities by using a function. The model uses an OpenAPI schema you supply to decide which function it needs to call.
A model can include data into its response through functions that it is not directly aware of or has access to beforehand. For instance, even though the model doesn’t save the current weather information, a function may enable the model to acquire it and incorporate it into its response.
Using Guardrails for Amazon Bedrock, secure your apps
By putting in place safeguards tailored to your use cases and responsible AI rules, you may build boundaries to encourage safe interactions between users and your generative AI apps.
The relevant managed resources, including knowledge bases, agents, and guardrails, are automatically deployed in your AWS account when you construct apps in Amazon Bedrock Studio. To access those resources in downstream applications, use the Amazon Bedrock API.
Amazon Bedrock Studio availability
The public preview of Amazon Bedrock Studio is now accessible in the AWS Regions US West (Oregon) and US East (Northern Virginia).
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