Introduction to the Hermes Agent

The Hermes Agent is an open-source AI agent developed by Nous Research, engineered to execute complex tasks, retain acquired knowledge, and evolve its capabilities over time. Rather than limiting itself to generating text responses, it leverages a suite of tools—including terminals, browsers, file systems, web search, and code execution—to perform practical work.

Defining an AI agent

AI agents transcend simple text generation. When provided with a specific objective, an agent can autonomously determine the necessary actions, utilize available tools, analyze the outcomes, and iteratively progress toward the final goal.

While many AI agents possess the ability to use tools and complete multi-step processes, the critical distinction lies in how they handle post-task learning. Some agents treat every assignment as an isolated problem. In contrast, Hermes is architected to preserve valuable insights and procedural knowledge, thereby enhancing its utility with continued use. Explore Agentic AI to understand how this approach applies to executing agents on DaDesktop.

What distinguishes Hermes?

Hermes features an integrated learning loop that enables it to derive skills from practical experience, refine those skills during operation, retain pertinent information, and retrieve data from past sessions when required.

Why choose the Hermes Agent?

Hermes is particularly advantageous for tasks involving multiple steps, diverse tools, or various applications. Instead of manually toggling between AI chats, terminals, browsers, and file managers, you can delegate the overall objective to Hermes, allowing it to orchestrate the workflow.

• Execute holistic tasks: Provide a clear objective rather than issuing discrete commands.
• Maintain long-term context: Preserve essential information across different sessions.
• Create reusable workflows: Save successful strategies as skills to avoid re-solving identical problems.
• Automate routine processes: Schedule tasks to execute automatically in the background.
• Delegate responsibilities: Utilize distinct subagents to handle specific components of larger tasks.
• Select your model: Integrate Hermes with local models or supported cloud-based providers.

Capabilities of Hermes

• Software development: Analyze code, debug issues, implement changes, execute tests, and manage repositories.
• Research: Perform web searches, review sources, gather data, and synthesize findings.
• Automation: Execute scripts and schedule recurring duties such as reporting, monitoring, and other routine operations.
• System administration: Utilize terminal commands, install software, configure systems, and resolve technical issues.
• Browser interactions: Navigate websites, interact with page elements, and extract data.
• File management: Read, create, edit, search, and organize files.
• Tool integrations: Connect external services and tools via MCP.

How Hermes evolves with usage

Consider assigning Hermes a complex, multi-step challenge. During the resolution process, it may identify an effective workflow. Instead of discarding this knowledge upon task completion, it can store the workflow as a persistent skill.

When a similar task arises in the future, Hermes can leverage this stored skill as a foundation. If refinements are needed, the skill can be updated. Additionally, its memory retains key facts and lessons learned from previous engagements.

Memory and skills serve complementary functions: memory stores contextual information and facts, while skills encapsulate procedural methods. Combined, they allow Hermes to accumulate a robust understanding of both its knowledge base and how to execute recurring tasks.

Background automation

Hermes includes a native scheduler for recurring duties. You can define schedules using natural language, enabling Hermes to perform work autonomously without requiring a manual session start.

This capability is ideal for generating reports, monitoring systems, managing backups, conducting research, and handling other routine tasks. Scheduled jobs can also maintain continuity between executions, allowing them to build upon prior work.

Local and cloud model compatibility

Hermes is not restricted to a single LLM. It can connect to local models or supported cloud providers, allowing you to switch models without altering the agent’s tools, memory, or established workflows.

Utilizing a local model provides greater control over the model itself, the hardware, and data processing locations. It also allows Hermes to interact with local files and resources without transmitting them to external providers.

Installing Hermes

Hermes is compatible with Linux, macOS, Windows, and WSL2. You may install the desktop application or opt for the command-line version exclusively.

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

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

Post-installation, launch the setup wizard to configure your model provider and other parameters:

hermes setup

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

Running Hermes on DaDesktop

Hermes requires an environment capable of executing its tools and retaining its data. DaDesktop offers a cloud desktop equipped with the necessary CPU, RAM, storage, and GPU resources to run Hermes alongside a local LLM.

This setup is beneficial when the desired model requires more VRAM than your local hardware provides. Select a GPU with sufficient VRAM, launch a DaDesktop instance, install Hermes, and run the model locally next to the agent.

You can also keep the desktop active for scheduled tasks and long-running workflows, eliminating the need to keep your personal computer running continuously.

Learn more about running local LLMs on DaDesktop.