Introducing the Hermes Agent

Hermes Agent is an open-source AI agent developed by Nous Research, engineered to execute tasks, retain learned knowledge, and enhance its capabilities over time. Unlike traditional models that only generate responses, Hermes actively performs work by leveraging tools such as terminals, browsers, file systems, web search, and code execution environments.

Understanding AI Agents

An AI agent extends beyond text generation. When provided with a specific goal, it independently determines the necessary actions, utilizes tools, observes outcomes, and iteratively progresses toward the objective.

While many AI agents can already handle multi-step tasks and tool usage, the distinction lies in post-task retention. Some agents treat every task as an isolated problem, whereas Hermes is architected to preserve valuable knowledge and procedures, thereby increasing its utility over time. For insights into deploying agents on DaDesktop, refer to Agentic AI.

What Sets Hermes Apart

Hermes features an integrated learning loop that allows it to derive skills from experience, refine those skills during application, retain significant information, and retrieve details from previous sessions when required.

Why Choose Hermes Agent?

Hermes is particularly valuable for tasks involving complex, multi-step processes, multiple tools, or various applications. Rather than manually switching between an AI chat interface, terminal, browser, and file explorer, you can delegate the overall objective to Hermes, allowing it to coordinate the workflow.

• Execute Complete Tasks: Provide Hermes with a high-level objective rather than requesting discrete instructions.
• Maintain Long-Term Context: Preserve useful information across separate interactions and sessions.
• Create Reusable Workflows: Store proven solutions as skills to avoid re-solving identical problems.
• Automate Routine Operations: Schedule tasks to execute automatically in the background.
• Delegate Subtasks: Utilize specialized sub-agents for different components of a larger project.
• Model Flexibility: Connect Hermes to local models or supported cloud-based LLM providers.

Hermes Capabilities

• Software Development: Analyze code, debug issues, implement changes, execute tests, and manage repositories.
• Research: Perform web searches, analyze sources, gather data, and synthesize findings.
• Automation: Execute scripts and schedule recurring activities such as reporting, monitoring, and routine maintenance.
• System Administration: Utilize terminal commands, install software, configure systems, and resolve technical issues.
• Browser Automation: Navigate websites, interact with web elements, and extract data.
• File Management: Read, create, modify, search, and organize digital files.
• Tool Integration: Connect external services and tools via MCP.

Continuous Improvement Through Use

Consider a complex task requiring multiple stages. As Hermes resolves it, it may identify an efficient workflow. Instead of discarding this insight upon task completion, Hermes saves the workflow as a skill.

When a similar task arises in the future, Hermes leverages this skill as a foundation. If adjustments are needed, the skill can be updated. Additionally, its memory retains relevant facts and lessons from prior work.

Memory and skills serve distinct functions: memory holds contextual information, while skills encapsulate procedural steps. Together, they enable Hermes to accumulate knowledge about both its existing understanding and the execution of recurring tasks.

Background Automation

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

This capability is ideal for reporting, monitoring, backups, research, and other routine processes. Scheduled tasks maintain continuity between executions, allowing them to build upon previous results.

Local and Cloud Model Support

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

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

Installation Guide

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

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

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

Once installed, launch the setup wizard to configure your model provider and other settings:

hermes setup

Refer to the Hermes documentation for comprehensive installation options and configuration details.

Running Hermes on DaDesktop

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

This setup is particularly beneficial when your desired model requires more VRAM than your local hardware can provide. You can select a GPU with sufficient VRAM, launch a DaDesktop instance, install Hermes, and run the model locally alongside the agent.

Additionally, you can keep the desktop active for scheduled tasks and long-running workflows, eliminating the need to maintain your personal computer in an active state.

Learn more about running local LLMs on DaDesktop.