What is the Hermes Agent?

The Hermes Agent, developed by Nous Research, is an open-source AI agent designed to execute complex tasks, retain learned information, and evolve over time. Rather than limiting itself to generating responses, it actively performs work by leveraging tools such as terminal access, web browsing, file system operations, web search, and code execution.

What defines an AI agent?

An AI agent transcends simple text generation. When given a specific objective, it autonomously determines the necessary actions, utilizes appropriate tools, monitors outcomes, and persistently works towards achieving the goal.

While numerous AI agents can already interact with tools to complete multi-stage processes, the distinction lies in post-task behavior. Traditional agents often treat every assignment as an isolated problem. In contrast, the Hermes Agent is architected to preserve valuable knowledge and procedures, thereby enhancing its utility over time. To understand how this concept applies to deploying agents on DaDesktop, refer to our overview of Agentic AI.

What sets Hermes apart?

Hermes features an intrinsic learning loop. It extracts skills from past experiences, refines these capabilities during operation, retains pertinent details, and references prior sessions when specific historical data is required for current tasks.

Why choose the Hermes Agent?

The Hermes Agent is particularly effective for tasks requiring coordination across multiple steps, tools, or applications. Instead of manually toggling between AI chat interfaces, terminals, browsers, and file managers, you can delegate the overarching objective to Hermes, allowing it to orchestrate the necessary actions.

• End-to-Task Execution: Provide a high-level objective rather than seeking step-by-step instructions for each component.
• Long-Term Context: Maintain crucial information across separate, independent sessions.
• Workflow Reusability: Preserve successful strategies as skills to avoid re-solving identical problems.
• Background Automation: Schedule recurring tasks to execute autonomously in the background.
• Task Delegation: Utilize distinct sub-agents to handle various components of a larger project.
• Model Flexibility: Integrate Hermes with local models or compatible cloud-based model providers.

Capabilities of the Hermes Agent

• Software Engineering: Analyze code, debug errors, implement changes, execute tests, and manage repositories.
• Research & Analysis: Conduct web searches, examine sources, aggregate data, and synthesize findings.
• Process Automation: Execute scripts and manage recurring routines such as reporting, system monitoring, and other scheduled operations.
• System Administration: Interact with terminals, install software, configure systems, and resolve technical issues.
• Web Interaction: Navigate websites, engage with dynamic web pages, and extract data.
• File Management: Read, create, modify, search, and organize files.
• Integration Capabilities: Connect external services and tools via MCP.

Continuous Improvement Through Usage

Consider a complex, multi-step task assigned to Hermes. During the resolution process, if Hermes identifies an effective workflow, it can archive this approach as a skill, ensuring the knowledge is not lost upon task completion.

When a similar challenge arises, Hermes can leverage this stored skill as a foundational template. If further optimization is possible, the skill can be updated. Additionally, its memory retains key facts and insights derived from previous endeavors.

Memory and skills serve distinct roles: memory preserves contextual information and facts, while skills encapsulate procedural knowledge. Combined, these elements enable Hermes to accumulate a comprehensive understanding of both its knowledge base and the most efficient methods for executing recurring tasks.

Background Work Automation

Hermes includes a built-in scheduler for recurring duties. You can define schedules using natural language, enabling Hermes to perform work autonomously without requiring an active user session.

This functionality is ideal for generating reports, monitoring systems, managing backups, and handling research tasks. Scheduled jobs can maintain continuity between executions, allowing them to iterate and build upon prior results.

Local and Cloud Model Support

Hermes is not restricted to a specific Large Language Model (LLM). You can connect it to local models or supported cloud providers, allowing you to switch models without altering the agent’s tools, memory, or established workflows.

Utilizing local models offers enhanced control over hardware, model parameters, and data processing locations. It also allows Hermes to process local files and resources without transmitting them to external model providers.

Installing the Hermes Agent

Hermes is compatible with Linux, macOS, Windows, and WSL2. You can install the desktop application or utilize the command-line interface independently.

To install on Linux, macOS, or WSL2, open a terminal and execute the following command:

curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash

For Windows, run the installer via PowerShell:

irm https://hermes-agent.nousresearch.com/install.ps1 | iex

Following installation, launch the setup wizard to configure your model provider and other preferences:

hermes setup

Refer to the Hermes documentation for detailed installation options and configuration settings.

Deploying Hermes on DaDesktop

The Hermes Agent requires a robust environment to execute its tools and store its data. DaDesktop offers a cloud desktop environment equipped with the necessary CPU, RAM, storage, and GPU resources to run Hermes alongside a local LLM.

This solution is particularly beneficial when the desired model requires more VRAM than is available on your local hardware. By selecting a GPU with sufficient VRAM, launching a DaDesktop instance, installing Hermes, and running the model locally, you can ensure optimal performance.

Additionally, you can keep the DaDesktop environment active for scheduled tasks and long-running workflows, eliminating the need to leave your personal computer powered on.

Explore further details on running local LLMs with DaDesktop.