What is Hermes Agent?

Hermes Agent is an open-source AI agent developed by Nous Research, designed to execute tasks, retain learned knowledge, and evolve over time. It leverages tools such as terminals, browsers, file systems, web search, and code execution to perform work autonomously, rather than simply generating text-based responses.

What is an AI agent?

An AI agent goes beyond mere text generation. When provided with a specific goal, it can determine the necessary actions, utilize available tools, observe outcomes, and iteratively work towards achieving the objective.

While many AI agents can use tools to complete multi-step tasks, the key distinction lies in what happens after task completion. Some agents treat every task as a completely new problem. In contrast, Hermes is engineered to retain useful knowledge and procedures, allowing it to become increasingly effective over time. To understand how this applies to running agents on DaDesktop, refer to Agentic AI.

What distinguishes Hermes?

Hermes features a built-in learning loop. It can generate skills based on experience, refine those skills during use, remember critical information, and retrieve insights from previous sessions when relevant data is needed for current tasks.

Why use Hermes Agent?

Hermes is particularly valuable for tasks involving multiple steps, various tools, or distinct applications. Instead of manually switching between AI chats, terminals, browsers, and file editors, you can assign the overall task to Hermes and allow it to coordinate the workflow.

• Execute complete tasks: Provide Hermes with a high-level objective rather than requesting individual instructions.
• Maintain long-term context: Preserve useful information across separate sessions.
• Create reusable workflows: Store successful approaches as skills to avoid re-solving the same problems from scratch.
• Automate recurring duties: Schedule tasks to run automatically in the background.
• Delegate complexity: Utilize separate sub-agents to handle different components of larger tasks.
• Select your model: Connect Hermes to local models or supported cloud model providers.

What Hermes can do

• Software development: Analyze code, debug issues, implement changes, run tests, and manage repositories.
• Research: Perform web searches, review sources, aggregate data, and organize findings.
• Automation: Execute scripts and schedule recurring tasks such as report generation, monitoring, and other routines.
• System administration: Operate terminals, install software, configure systems, and troubleshoot issues.
• Browser interactions: Navigate websites, interact with web pages, and extract information.
• File management: Read, create, edit, search, and organize files.
• Tool integrations: Connect additional services and tools via MCP.

How Hermes improves with use

Consider a complex task requiring several steps. While solving it, Hermes may identify an effective workflow. Instead of losing this knowledge upon task completion, it can save the workflow as a skill.

When a similar task arises in the future, Hermes can leverage this saved skill as a starting point. If the workflow requires refinement, the skill can be updated. Additionally, its memory can retain key facts and lessons learned from previous work.

Memory and skills serve distinct functions. Memory holds contextual information and facts, while skills encapsulate the procedures for executing tasks. Together, they enable Hermes to accumulate knowledge about both its understanding and the execution of recurring work.

Background work automation

Hermes includes a built-in scheduler for recurring tasks. You can define schedules using natural language, allowing Hermes to perform work independently without waiting for a manual session start.

This capability is ideal for reports, monitoring, backups, research tasks, and other regular routines. Scheduled tasks can also maintain continuity between runs, allowing them to build upon previous work.

Running local or cloud models

Hermes is not restricted to a single LLM. You can connect it to local models or supported cloud providers and switch models without altering the agent's tools, memory, or workflows.

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

How to install Hermes

Hermes is compatible with Linux, macOS, Windows, and WSL2. You can install the desktop application or use the command-line version without the GUI.

On Linux, macOS, or WSL2, open a terminal and execute the following:

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

On Windows, run the installer from PowerShell:

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

Following installation, run the setup wizard to configure your model provider and other options:

hermes setup

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

Run Hermes on DaDesktop

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

This is particularly useful when the desired model requires more VRAM than your local machine possesses. Select a GPU with sufficient VRAM, launch a DaDesktop instance, install Hermes, and run the model locally alongside the agent.

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

Learn more about running local LLMs on DaDesktop.