Develop agentic workflows¶
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The DataRobot Agentic Application Template repository provides ready-to-use templates for building and deploying AI agents with multi-agent frameworks. These templates streamline the process of setting up your own agents with minimal configuration requirements and support both local development and testing, as well as deployment to production environments within DataRobot.
To start building and deploying AI agents from DataRobot-provided templates, review the Quickstart guide.
| Topic | Description |
|---|---|
| Installation | Install required components for agentic application development. |
| Quickstart | Build and deploy AI agents from templates leveraging multi-agent frameworks. |
| Agent components | Learn about the components required to create an agent using DataRobot's agent framework. |
| Agent authentication | Learn how to implement authentication in your DataRobot agentic application, covering API tokens, authorization context, OAuth 2.0, and security best practices. |
| Customize agents | Customize agent code, test locally, and deploy agentic application for production use. |
| Add Python packages | Add required Python packages to agentic application using execution environment or custom model requirements. |
| Configure LLM providers in code | Configure different LLM providers for your agentic application including DataRobot gateway, external APIs, and custom deployments. |
| Configure LLM providers with metadata | Configure LLM providers using environment variables and Pulumi for infrastructure-level configuration without modifying agent code. |
| Add tools to agents | Add local tools, predefined tools, and DataRobot global tools to your agentic application, including detailed integration patterns. |
| Deploy agentic tools | Deploy global agentic tools from the DataRobot Registry to handle tasks critical to the agent application. |
| Integrate tools using MCP server | Integrate tools into your agentic workflows using the Model Context Protocol (MCP) server for centralized tool management and standardized interfaces. |
| Access request headers | Learn how to access HTTP request headers in your deployed agents for authentication, tracking, and custom metadata. |
| Troubleshooting | Diagnose and resolve common issues when working with DataRobot agentic application. |