Create Grounded Conexiones del modelo with Amazon Bedrock RAG capability

Create Anclado en la base de conocimientos Conexiones del modelo using the native RAG (Retrieval Augmented Generation) capability from Amazon Bedrock to generate accurate and contextually relevant information referenced from Base de conocimientos de Amazon.

We are now offering you the option to create Conexiones del modelo using the Amazon Bedrock-RAG capability. A search query on RAG retrieves relevant chunks of content from large-data-sets which are relevant and accurate to the provided context. After retrieving the relevant information, the model uses it to generate a response.

A few things to consider

  • To use the Amazon Bedrock-RAG capability, you would first create a Knowledge Base in Amazon Bedrock before creating the Anclado en la base de conocimientos Conexión del modelo.

    See: Create Base de conocimientos de Amazon

  • To use additional models from Amazon Bedrock that are not available for selection when creating a Conexión del modelo, you would have to procure the Model ID and the Model ARN from the supported models of Amazon Bedrock.

    See: Add Amazon Bedrock models from Servicios de AWS

Work flow for using Amazon Bedrock RAG capability for creating Conexiones del modelo

Antes de empezar

The Automation Admin requires these roles and permissions to create and manage Conexiones del modelo for their business organization.
  • Role: AAE_Basic, Automation Admin custom role
  • Permission: Attended Bot Runner
  • Settings: AI Data Management must be enabled by the Automation Admin and the check box selected for Allow users to disable logs on AI Skills. Allow users with the Bot Creator license to disable data logging when using AI Skills to enable the Data logging toggle in the Habilidades de IA screen.

See Roles y permisos para Herramientas de la IA for the Automation Admin custom role permissions.

Other requirements:

  • As mentioned earlier, you would first create an Base de conocimientos de Amazon to create a Anclado en la base de conocimientos Conexión del modelo and use it successfully in an Habilidad de IA.
  • If you want to store authentication details in a credential vault, have that information handy. See Almacenamiento seguro de credenciales en Credential Vault.
  • To test a Conexión del modelo, you must be connected to a Agente de bot 22.60.10 and later. As part of the test, you would have to run the bot on your desktop. Hence ensure the Agente de bot is configured to your user. For this task, if you have to switch connection to a different Control Room, see: Cambiar el registro del dispositivo entre las instancias de Control Room.
  • You would need access to the Grabadora package and the Habilidades de IA package to test the connection successfully. A test Indicación would be executed to test the Conexión del modelo.

Procedimiento

  1. In your Control Room environment, navigate to AI > Model connections > Create model connection.
  2. In the Create model connection screen you would configure these Connection settings:
    Create Grounded Conexiones del modelo with Amazon Bedrock RAG capability
    You can manually enter the model name in the Choose a model or create a custom one field. The name you enter will be used for creating the Conexión del modelo.
    1. Model connection name: Provide a name for easy identification of the Conexión del modelo.
    2. Description (optional): Add a meaningful short description defining the connection.
    3. Choose a vendor: Choose a foundational model vendor from the supported list of vendors. For creating a Anclado en la base de conocimientos Conexión del modelo with Amazon Bedrock, you would select Amazon Bedrock from the drop-down list.
    4. Choose a type: Choose Anclado en la base de conocimientos for using the RAG capability.
    5. Choose a model or create a custom one: Choose a model from the drop-down list of validated models from Amazon Bedrock.
      Additionally, we also support other models available from Amazon Bedrock, which are not available in the drop-down list. You can use either the Model ID or Model ARN to add to the list. See: Add Amazon Bedrock models from Servicios de AWS.
      For a complete list of supported models for each foundational model vendor, see Preguntas frecuentes sobre AI Agent Studio.
    6. Click Next to proceed to the Authentication details section.
  3. In the Authentication details section, configure these settings:
    1. Region: Choose the region where your selected model is deployed for authenticating the Conexión del modelo. You can also add a region that is not available in the drop-down list by referring to the list in Amazon Bedrock. Enter in this format to get the region added to the list. For example: us-east-1.
      For a list of supported deployment regions for Amazon Bedrock models, see Supported regions and models for Amazon Bedrock knowledge bases.
    2. Knowledge base ID: Provide the Knowledge Base ID you procured from Amazon Bedrock. .
      See Amazon Bedrock knowledge bases
    3. Access Key: This AWS access key serves as your unique identifier within the AWS ecosystem. It is a fundamental part of the authentication process, allowing Servicios de AWS to recognize and validate your access.
    4. Secret Access Key: This key is the confidential counterpart to your Access Key ID. This key is used to sign requests made to AWS, enhancing security by ensuring that only authorized individuals or systems can access your AWS resources.
    5. Session Token (optional): This is an optional field. In addition to the above information, you can include a Session token, which is a temporary, time-bound token used when working with temporary security credentials. It provides an added layer of security, particularly in scenarios where temporary access is required, such as when using temporary security credentials.
    6. After setting up the authentication details, confirm and click Next to proceed to the Test connection section to test the Conexión del modelo.
    Nota: For details on setting up the Access Key, Secret Access Key, and Session Token for Amazon Bedrock, see: Amazon Bedrock: acción Autenticar.
  4. Click Test connection to make sure all connection details have been defined correctly and check if the connection is working.
    This is a desktop operation using a Agente de bot. Use Agente de bot 22.60.10 and later for successful testing.
    • If the connection works as expected, the system will process the request and you will get a system generated success message.
    • If the connection does not work as expected, you will get a system-generated message stating the reason for the connection failure. For example, if you have not downloaded the supported foundational model package to your workspace, you would get an error message. You would have to download the package and then retest the Conexión del modelo.
    • If the testing a Conexión del modelo is unsuccessful or if you leave the task incomplete, the Conexión del modelo will not get saved and you will have to restart the process of creating the Conexión del modelo.
  5. Click Next to proceed to the Invite roles section to begin assigning custom roles to users.
    The Automation Admin would create custom roles and assign the Conexiones del modelo to the role, which can then be assigned to users. Only users assigned to this custom role can use this Conexión del modelo.
  6. Assign access to the Pro Developer via custom role (using RBAC), for using this Conexión del modelo to create an Habilidad de IA.
  7. Click Create model connection to complete creating the Conexión del modelo.
    After successfully creating the Conexión del modelo, the Pro Developer would use it to create an Habilidad de IA

    See: Crear Habilidades de IA con Anclado en la base de conocimientos Conexiones del modelo

    .

Qué hacer a continuación

After creating and testing the Conexión del modelo, you would assign it to the Pro Developers, who would use this connection to create Habilidades de IA.

See Crear Habilidades de IA con Anclado en la base de conocimientos Conexiones del modelo.

Nota: When you create or test an Habilidad de IA in the AI Skill screen, the success or failure details along with the model responses can be viewed in these navigation screens:
  • Administration > AI governance > AI Prompt log
  • Administration > AI governance > Event log
  • Administration > Audit log

See Gobernanza de la IA.

As the next step in your sequence of tasks, go to Crear Habilidades de IA con Anclado en la base de conocimientos Conexiones del modelo and create an Habilidad de IA and connect to a Anclado en la base de conocimientos Conexión del modelo to eventually use it in an automation.