Overview of 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. Rather than simply generating text responses, it leverages tools such as terminals, browsers, file systems, web search, and code execution to actively complete work.

Defining an AI agent

An AI agent transcends basic text generation. When provided with a specific goal, it autonomously determines the necessary actions, utilizes available tools, observes outcomes, and continues progressing toward the objective.

While many AI agents can already utilize tools to complete multi-step tasks, the distinguishing factor lies in post-task behavior. Some agents treat every new task as a fresh problem, whereas Hermes is engineered to preserve valuable knowledge and procedures, enhancing its utility over time. Explore Agentic AI to understand how this applies to running agents on DaDesktop.

Hermes’s unique advantages

Hermes features a built-in learning loop that enables it to create skills from experience, refine those skills during use, retain useful information, and retrieve data from previous sessions when needed.

Benefits of using Hermes Agent

Hermes excels in scenarios involving multi-step processes, various tools, or multiple applications. Instead of manually switching between AI chats, terminals, browsers, and files, you can assign the overarching task to Hermes and allow it to orchestrate the workflow.

• Execute complete tasks: Provide Hermes with a high-level objective rather than seeking individual step-by-step instructions.
• Maintain long-term context: Preserve critical information across independent sessions.
• Create reusable workflows: Store successful methodologies as skills to avoid re-solving identical problems from scratch.
• Automate recurring duties: Schedule tasks to execute automatically in the background.
• Delegate responsibilities: Employ separate subagents to handle different components of larger projects.
• Model flexibility: Connect Hermes to local models or compatible cloud model providers.

Capabilities of Hermes

• Software development: Analyze code, debug issues, implement changes, execute tests, and manage repositories.
• Research: Conduct web searches, review sources, aggregate data, and structure findings.
• Automation: Execute scripts and schedule recurring routines such as reporting, monitoring, and maintenance.
• System administration: Utilize the terminal, install software, configure systems, and troubleshoot issues.
• Browser interactions: Navigate websites, interact with web pages, and extract data.
• File management: Read, create, edit, search, and organize files.
• Tool integrations: Connect additional services and tools via MCP.

Hermes’s learning trajectory

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

When a similar task arises in the future, Hermes can utilize that skill as a baseline. Should the workflow require refinement, the skill can be updated. Additionally, its memory retains useful facts and lessons learned from prior work.

Memory and skills serve distinct functions: memory stores contextual information, while skills hold procedural steps. Together, they enable Hermes to accumulate knowledge about both what it knows and how to perform recurring tasks.

Background task automation

Hermes includes a built-in scheduler for recurring duties. You can define schedules using natural language, allowing Hermes to perform work without requiring you to initiate a session.

This is ideal for reports, monitoring, backups, research, and other routines. Scheduled tasks can also maintain continuity between executions, building upon previous work.

Local and cloud model support

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 workflows.

Using local models offers greater control over the model, hardware, and data processing location. It also enables Hermes to work with local files and resources without transmitting them to external model providers.

Installing Hermes

Hermes is compatible with Linux, macOS, Windows, and WSL2. You may install the desktop application or utilize the command-line interface without the desktop version.

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

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

On Windows, run the installer via PowerShell:

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

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

hermes setup

Consult the Hermes documentation for detailed installation and configuration options.

Running Hermes on DaDesktop

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

This setup is particularly beneficial when the desired model requires more VRAM than your local machine offers. Select a GPU with sufficient VRAM, launch a DaDesktop environment, 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 on.

Learn more about running local LLMs on DaDesktop.