What is the Hermes Agent? | DaDesktop Brasil

The Hermes Agent is an open-source AI framework developed by Nous Research, designed to execute tasks, retain learned knowledge, and enhance performance over time. Unlike systems that merely generate responses, Hermes utilizes tools such as terminals, browsers, file systems, web search, and code execution to actively complete work.

What defines an AI agent?

An AI agent extends beyond simple text generation. When provided with a goal, it can determine the necessary actions, utilize available tools, observe outcomes, and persist in working toward the objective.

While many AI agents can already leverage tools and handle multi-step tasks, the key distinction lies in post-task behavior. Some agents treat every task as an isolated incident. In contrast, Hermes is engineered to preserve valuable knowledge and procedures, allowing it to grow more effective with time. Explore Agentic AI to understand how this approach applies to running agents on DaDesktop.

What sets Hermes apart?

Hermes features an integrated learning loop. It develops skills from experience, refines those skills during operation, retains useful data, and can search past sessions when it requires context from previous work.

Persistent Memory

Hermes retains relevant information about you, your projects, and your environment across multiple sessions.

Evolving Skills

Hermes transforms effective workflows into reusable skills, continuously refining them as it discovers more efficient methods for task execution.

Historical Session Access

Hermes can query previous conversations to retrieve information pertinent to its current activities.

Why choose the Hermes Agent?

Hermes is particularly valuable for tasks involving multiple steps, tools, or applications. Rather than manually switching between AI chats, terminals, browsers, and files, you can assign the overarching task to Hermes and allow it to coordinate the workflow.

Execute Comprehensive Tasks: Provide Hermes with a broad 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 repeating the same problem-solving process from scratch.
Automate Recurring Duties: Schedule tasks to execute automatically in the background.
Delegate Responsibilities: Utilize dedicated subagents for different components of larger projects.
Select Your Model: Connect Hermes to local models or supported cloud-based model providers.

Capabilities of Hermes

Software Development: Analyze code, debug issues, implement changes, run tests, and manage repositories.
Research: Conduct web searches, review sources, gather data, and organize findings.
Automation: Execute scripts and schedule routine tasks such as reporting, monitoring, and other regular operations.
System Administration: Operate via the terminal, install software, configure systems, and resolve issues.
Browser Operations: Navigate websites, interact with pages, and extract information.
File Management: Read, create, edit, search, and organize files.
Tool Integrations: Connect additional services and tools via MCP.

How Hermes evolves through use

Consider a complex task requiring multiple steps. As Hermes solves it, it 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 later, Hermes can leverage that skill as a foundation. If the workflow requires refinement, the skill can be updated. Additionally, its memory retains key facts and lessons from prior engagements.

Memory and skills serve distinct functions. Memory holds contextual information, while skills store procedural steps. Together, they enable Hermes to accumulate knowledge regarding both what it knows and how to execute recurring tasks.

Background 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 new session initiation.

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

Utilizing Local or Cloud Models

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 workflows.

Running a local model offers greater control over the model, hardware, and data processing location. It also allows Hermes to work with your files and local resources without transmitting them to an external provider.

Installing Hermes

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

For 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

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

hermes setup

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

Running Hermes on DaDesktop

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

This setup is beneficial when the desired model requires more VRAM than your personal machine possesses. Select a GPU with sufficient VRAM, launch a DaDesktop instance, install Hermes, and run the model locally with 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.

Discover more about running local LLMs on DaDesktop.