Agent

Agents are the core AI components in DuploCloud AI Suite. Each Agent is responsible for interpreting user inputs, deciding which Tools to invoke, and orchestrating intelligent responses using integrated data and logic. They serve as the execution layer for AI-powered workflows and can be tailored to a wide range of use cases, from conversational interfaces to backend automation.

DuploCloud supports two types of Agents: Prebuilt and Dynamic. Each offers a different development path, depending on whether you're deploying an existing containerized service or creating a prompt-driven AI workflow within DuploCloud.

Step 1: Create an Agent

Creating a Prebuilt Agent

Prebuilt Agents use a pre-existing container image that defines your Agent’s functionality. For specifics about Prebuilt Agents, see the Developers documentation.

1. Navigate to AI Suite → Studio → Agents.

2. Click Add. The Add Agent Definition pane displays.

   

   The Add Agent Definition pane
3. Complete the following fields:

Name	Enter a name for the Agent.
Agent Type	Select Prebuilt.
Docker Image	Enter the full image path (e.g., registry/myagent:latest).
Base64 Docker Registry Credential (Optional)	Enter credentials if needed.
Port	Enter the port exposed by the container.
Protocol	Select the network protocol your Agent uses for communication (e.g., http, https, or grpc). This determines how external services connect to the containerized Agent.
Token Limit	Set the token output limit.
Environment Variables	Define key-value pairs (mark as mandatory if needed).
Meta Data	Optional key-value configuration.

1. Click Submit to create the Agent. You can view your Agents on the Agents tab.

   

   The Agents tab with the kubernetes-agent Agent displayed

Once the Agent has been successfully completed, complete steps 2 and 3 below to deploy and register the Agent so it can be used with DuploCloud's AI ServiceDesk.

Creating a Dynamic Agent

Dynamic Agents are configured using flexible, user-defined parameters, including tools, prompt behavior, and optional custom build variables. First create an Agent definition, and then build an Agent image based on its configuration.

Creating an Agent Definition

1. Navigate to AI Suite → Studio → Agents.

2. Click Add. The Add Agent Definition pane displays.

   

   The Add Agent Definition pane

Expanded Knowledge Sources section of the Add Agent Definition pane

1. Complete the following fields:

Name	Enter a name for the Agent.
Agent Type	Select Dynamic.
Prompt	Enter the initial instruction or context that guides the Agent’s behavior and responses.
Tools	Select one or more registered Tools for the Agent to use. For more about using Tools, see the DuploCloud Tools documentation.
Provider	Select the Large Language Model (LLM) that will power the Agent (e.g., bedrock or Other.
Model	Choose the specific version or configuration of the selected LLM to use for this Agent.
Temperature	Set the randomness of responses (e.g., 0 for deterministic behavior).
Token Limit	Set the maximum number of tokens for responses (e.g., 1000).
Knowledge Sources	Optionally, click the plus icon () to connect the Agent to a knowledge source such as a vector database collection. This allows the Agent to retrieve and use information from previously uploaded documents stored in a vector database. Complete the fields: Vector DB: Select a previously created vector database to connect as a knowledge source. Collections: Choose one or more document collections within the Vector DB relevant to the Agent (required if Vector DB is selected). Description: Enter a brief summary of the knowledge source’s purpose or contents (optional). Meta Data: Add key-value pairs to filter or target specific content in the knowledge source (optional).
Meta Data	Add custom key-value metadata to the Agent.

1. Click Submit. Once the Agent creation is complete, continue below to package your configuration into a deployable container image.

Building an Image

Now that the Agent is created, trigger a build packages your dynamic Agent’s configuration, including prompts, tool selections, and variables, into a deployable container image.

1. Go to the Builds tab on the Agent’s details page.

2. Click Trigger. The Trigger Build pane displays.

3. Complete the following fields:

Builder Docker Image	This field is prepopulated based on your Agent configurations.
Timeout	Set a timeout for the build job (e.g., 0 for unlimited).
Tools	Select one or more registered tools for the Agent to use. See the Tools documentation for more details.
Build Environment Variables	Define environment variables to initialize tool behavior. Example: Key: init_code Value: from duplo_custom_tool import ExecuteKubectlCommandTool; tool = ExecuteKubectlCommandTool(); print(isinstance(tool, BaseTool)); print(type(tool))
Mandatory	Check if the variable is required.
Custom Build Variables	(Optional) Add any custom key/value pairs for build-time configuration.

1. Click Submit to begin packaging your configured Agent into a runnable container image. After the build is complete, proceed with steps 2 and 3 below to deploy the image and register the Agent.

Step 2: Deploy the Agent Image

Once an Agent image is created, it must be deployed. Deploying the Agent makes it available for use on your infrastructure.

1. Select the Images tab on the Agent page (AI Suite → Studio → Agents → select Agent name).

2. Click the menu icon () next to the Agent image and select Deploy. The Deploy Image pane displays with name and image fields prepopulated.

   

   The Agent page with the Deploy Image pane
3. Choose a deployment method:

   • Quick Deploy: Automatically sets up everything needed to run your Agent: it creates a DuploCloud Service, deploys a pod that runs the Agent container, and exposes it through a load balancer listener using the port specified during Agent creation.

   • Advanced: Allows full control over deployment settings, including network, scaling, and service options.

4. Proceed through the remaining steps to complete the deployment, following the prompts based on whether you selected Quick Deploy or Advanced. Monitor the deployment status on the Deployments tab.

   

   The Agent Deployment tab showing the deployment with Running status

Step 3. Register the Agent

Once your Agent has been successfully deployed, it must be registered so that the DuploCloud AI HelpDesk can route queries to it.

1. Select the Register tab on the Agent page (AI Suite → Studio → Agents → select the Agent name).

2. Click Register. The Register Agent pane displays.

   

   The Register Agent pane
3. Complete the following fields:

Name	Provide a name for this Agent registration.
Instanceid	Enter the ID of the deployed instance (created during deployment).
Allowed Tenants	Select the tenants where this Agent is allowed to operate.
Endpoint	The service endpoint for the deployed Agent (prepopulated).
Path	The endpoint path that handles requests. You can retrieve this from the Agent's registration info, if needed: On the Register tab, click the menu icon () next to the Instance and select Edit. Copy the path from the Path field.
Headers	Optional key/value pairs to pass custom headers during API calls.

1. Click Submit to register the Agent. This Agent can now be utilized by the DuploCloud Service Desk. To learn how to configure and use Service Desk, see the Service Desk documentation.