Overview of the Hermes Agent

Hermes Agent, an open-source AI agent developed by Nous Research, is engineered to execute complex tasks, retain learned information, and evolve over time. Beyond simple response generation, it leverages tools like terminals, browsers, file systems, web search, and code execution environments to perform substantive work.

Understanding AI Agents

An AI agent extends functionality beyond text generation. When provided with a specific objective, the agent autonomously determines the necessary actions, utilizes available tools, monitors outcomes, and iterates toward the goal.

While many AI agents can handle multi-step processes and tool usage, the critical distinction lies in post-task continuity. Unlike agents that treat every interaction as a standalone problem, Hermes is architected to retain valuable knowledge and procedural insights, enhancing its utility over time. Explore Agentic AI to understand how these capabilities apply to running agents on DaDesktop.

Key Differentiators of Hermes

Hermes features an integrated learning loop that enables it to derive skills from experience, refine those skills during operation, retain critical information, and retrieve details from prior sessions when required.

Benefits of Using Hermes Agent

Hermes is particularly valuable for tasks involving multiple steps, tools, or applications. Instead of manually coordinating between AI chats, terminals, browsers, and files, you can delegate the overall objective to Hermes and allow it to manage the workflow.

• Execute Complete Tasks: Assign broad objectives rather than requesting isolated instructions.
• Maintain Long-Term Context: Retain essential information across distinct sessions.
• Create Reusable Workflows: Store successful strategies as skills to avoid re-solving identical problems.
• Automate Recurring Duties: Schedule tasks to execute automatically in the background.
• Delegate Subtasks: Utilize separate subagents for different components of a larger project.
• Select Your Model: Integrate Hermes with local models or supported cloud model providers.

Capabilities of Hermes

• Software Development: Examine code, debug issues, implement changes, execute tests, and manage repositories.
• Research: Perform web searches, analyze sources, gather data, and structure findings.
• Automation: Execute scripts and manage recurring routines such as reporting and monitoring.
• System Administration: Operate terminals, 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.

Continuous Improvement Through Use

When assigned a complex, multi-step task, Hermes may identify an effective workflow during execution. Instead of discarding this knowledge after completion, it can save the workflow as a skill.

In future similar scenarios, Hermes can leverage this saved skill as a foundation. If the process requires refinement, the skill can be updated. Additionally, its memory retains key facts and lessons learned from previous engagements.

Memory and skills serve complementary roles: memory preserves contextual information, while skills store procedural methods. Together, they enable Hermes to accumulate knowledge about both its understanding and its execution capabilities.

Background Automation

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

This feature is ideal for reports, monitoring, backups, research, and other routine tasks. Scheduled jobs can also maintain continuity, building upon previous iterations.

Local and Cloud Model Support

Hermes is not restricted to a specific LLM. You can connect it to local models or supported cloud providers, switching models without altering the agent’s tools, memory, or workflows.

Utilizing local models offers greater control over hardware and data processing locations. It also enables Hermes to interact with local files and resources without transmitting data to external model providers.

Installing Hermes

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:

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 preferences:

hermes setup

Refer to the Hermes documentation for detailed installation and configuration instructions.

Running Hermes on DaDesktop

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

This is particularly beneficial when the desired model exceeds your local machine’s VRAM capacity. Select a GPU with sufficient VRAM, launch a DaDesktop instance, install Hermes, and run the model locally within that environment.

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

Explore running local LLMs on DaDesktop.