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An agent is an AI system that reasons through problems and executes tasks autonomously. Agents are configured by specifying models, tools, instructions, and reasoning approach—providing everything needed to accomplish tasks from simple workflows to complex, open-ended objectives.

Agents UI guide

Create and manage agents through the SeekrFlow web interface.

Agents SDK guide

Create and manage agents programmatically with the Python SDK.

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Agent primitives

Agents are built from two core primitives:

Models

A model serves as the agent’s cognitive engine, providing the reasoning capabilities needed to understand tasks, determine the best course of action, and generate responses. SeekrFlow supports both base models and fine-tuned models.

Tools

Tools are modular components that extend an agent’s capabilities beyond built-in reasoning. With tools, agents can take actions, access external systems, or query knowledge stores.

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Agent configuration

When creating an agent, you configure several key properties:

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Reasoning effort

Reasoning effort controls how much reasoning the agent uses when working through a request. The default is medium.

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Agent status

Each agent has a status that indicates its deployment state:

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Multi-agent workflows

Agents can delegate subtasks to other agents using the agent-as-tool pattern. A supervisor agent remains in control throughout a run, invoking sub-agents as callable tools to handle specialized tasks and then integrating their results into a unified response. This enables composable, multi-agent systems where each agent focuses on a specific capability. For implementation details, see Agent as tool.
Last modified on July 7, 2026