Agentic AI¶
The following sections provide reference content that supports working with agentic workflows:
| Topic | Description |
|---|---|
| Availability information | Describes support for the various elements that are part of GenAI model creation, including LLMs, embeddings, sharing and permissions, and supported dataset types. |
| LLM reference | View brief descriptions of each available LLM. |
| Feature considerations | Describes things to consider when working with GenAI capabilities in DataRobot. |
| Troubleshooting | Provides an overview of common errors and their handling. |
| Prompting strategy | Provides strategies for creating effective prompting. |
| LLM metric reference | Provides detailed metric descriptions, including formulas for calculating DataRobot's custom metrics for LLM evaluation. |
| LLM gateway administration | Details the steps for organizational admins to follow when adding LLMs to the LLM gateway. |
| ACL metadata hydration and enforcement | Details the API routes and permissions required for ACL metadata hydration and enforcement. |
| Agentic repositories | Overview of the repositories DataRobot provides for agentic workflow development. |