Developing multiple AWS Bedrock models for multiple clients

To set up another isolated AWS Bedrock model for a different project, you can follow these steps:

1. Create a new agent: Use the Amazon Bedrock Agents Boto3 client to create a new agent with a unique name, description, and foundation model. This will be separate from your existing agent.

2. Configure the new agent: Set up a new action group for this agent, defining the specific actions, parameters, and APIs it will use. This ensures the new agent's capabilities are tailored to your new project's requirements.

3. Establish a separate knowledge base: Create a new knowledge base specifically for this project. This will keep the information isolated from your existing knowledge base.

4. Set up a new repository: Create a separate repository for any custom logic or code required for the new agent's actions. This ensures complete separation from your existing project's codebase.

5. IAM permissions: Ensure that appropriate IAM roles and permissions are set up for the new agent and its associated resources.

6. Testing and deployment: Test the new agent thoroughly in isolation before deploying it to your production environment.

Regarding tutorials for setting up Bedrock action and knowledge base agents, Amazon provides documentation and examples in the AWS console and through their developer resources. While there isn't a specific step-by-step tutorial mentioned in the provided sources, you can refer to the Amazon Bedrock documentation for detailed guidance on creating and configuring agents, setting up knowledge bases, and implementing action groups.

For the repository setup, you would follow standard practices for creating and managing code repositories, ensuring that it's separate from your existing project's repository.

By following these steps, you can create a completely isolated Bedrock model with its own agents, knowledge base, and associated resources, preventing any intermingling with your existing project.

Sources
Design multi-agent orchestration with reasoning using Amazon Bedrock and open source frameworks | AWS Machine Learning Blog
Build and modify agents in Amazon Bedrock for your application - Amazon Bedrock