In the rapidly evolving landscape of automation and intelligent systems, Agentic Workflows are becoming increasingly crucial. They enable complex tasks to be broken down and executed autonomously by specialized agents. At the heart of these workflows lies the need for agents to perform specific actions and return structured outputs. This is where implementing functions within your .do Agentic Flows becomes essential.
Welcome to the reference.do blog, your guide to understanding and leveraging the power of the .do platform. In this post, we'll delve into how you can empower your agents by integrating functions, making them more capable and your workflows more robust.
Think of an Agentic Workflow as a series of steps performed by different agents to achieve a larger objective. Each agent is designed to handle a particular part of the process. For an agent to be truly effective, it needs to be able to perform specific "functions" – actions or computations that contribute to the overall workflow goal.
These functions can range from simple data retrieval and processing to complex interactions with external services or internal systems. By defining and implementing these functions within your .do agents, you equip them with the necessary tools to execute their assigned tasks efficiently and reliably.
The reference.do documentation provides the canonical source for understanding how to build and deploy Agentic Workflows and Services-as-Software on the .do platform. The API documentation, data models, and code examples guide you through the process of defining your agents' capabilities.
At a fundamental level, an agent's function is what it does to produce an output based on an input. This is often represented within the workflow structure. Consider the AgentStepOutput interface provided in the reference documentation:
interface AgentStepOutput {
status: 'success' | 'failure';
output: any; // The output of the agent step can be anything
agentId: string; // The ID of the agent that executed this step
}
This interface highlights the core components of an agent's function execution: a status indicating whether the function succeeded or failed, the actual output of the function (which can be of any type, allowing for flexibility), and the identifier of the agent that performed the function.
When you're implementing a function for your agent on the .do platform, you are essentially defining the logic that produces this AgentStepOutput. This involves:
The structure of the AgentWorkflowOutput interface further illustrates how these individual agent functions contribute to the overall workflow:
interface AgentWorkflowOutput {
status: 'completed' | 'failed';
steps: AgentStepOutput[];
finalOutput: any; // The final output of the entire workflow
}
The steps array within the AgentWorkflowOutput is a collection of AgentStepOutput objects, clearly showing the output of each individual agent's function within the workflow execution. This provides a transparent view of how each function contributed to the final result.
To truly master the implementation of functions within your .do Agentic Flows, it's crucial to consult the reference.do documentation. Here, you will find:
Q: What is the purpose of the reference documentation?
A: The reference provides canonical documentation for all aspects of the .do platform, including API specifications, data models, and best practices for building Agentic Workflows and Services-as-Software.
Q: What kind of information is included in the API documentation?
A: You can find detailed information on API endpoints, request/response formats, data schemas, and code examples for interacting with the .do platform.
Q: Does the reference cover data models used on the platform?
A: Yes, the reference includes documentation on the underlying data models used within the .do platform, such as the structure of Agents, Workflows, and Services.
Q: Are there examples of building Agentic Workflows and Services-as-Software?
A: You can find guides and examples demonstrating how to implement common Agentic Workflows and build Services-as-Software using the provided APIs and SDKs.
By leveraging the resources available at reference.do, you can unlock the full potential of your .do Agentic Flows by equipping your agents with well-defined and efficiently implemented functions. Start exploring the documentation today and begin building more intelligent and capable automated systems.