Introduction to Hermes Agent

Hermes Agent is an open-source AI agent developed by Nous Research, designed to execute tasks, retain learned knowledge, and evolve its capabilities over time. Rather than simply generating responses, it leverages tools such as the terminal, browser, file system, web search, and code execution to perform substantive work.

Defining an AI agent

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

While many current AI agents can utilize tools and complete multi-step processes, the critical distinction lies in post-task behavior. Some agents treat every interaction as an isolated event. In contrast, Hermes is architected to preserve valuable knowledge and procedures, allowing it to become increasingly effective over time. For insights on deploying such agents on DaDesktop, refer to Agentic AI.

Hermes's unique advantages

Hermes features an integrated learning loop that enables it to generate skills from experience, refine those skills during execution, memorize relevant information, and retrieve data from prior sessions when needed.

Reasons to utilize Hermes Agent

Hermes is particularly valuable for tasks requiring multiple steps, tools, or applications. Instead of manually toggling between an AI chat interface, terminal, browser, and file directories, you can assign the entire objective to Hermes and allow it to manage the coordination.

• End-to-end task execution: Assign a high-level objective rather than requesting individual instructions.
• Sustained context: Maintain relevant information across separate sessions.
• Reusable workflows: Store effective strategies as skills to avoid re-solving identical problems.
• Automated recurring tasks: Schedule processes to execute automatically in the background.
• Task delegation: Utilize distinct subagents for various components of complex tasks.
• Model flexibility: Integrate Hermes with local models or compatible cloud-based providers.

Hermes's capabilities

• Software engineering: Analyze code, debug issues, implement changes, execute tests, and manage repositories.
• Information research: Search the web, review sources, aggregate data, and structure findings.
• Process automation: Execute scripts and schedule recurring duties like reporting, monitoring, and standard routines.
• System management: Operate the terminal, install software, configure systems, and resolve technical issues.
• Web navigation: Browse websites, interact with pages, and extract data.
• File management: Read, create, modify, search, and organize files.
• Service integration: Connect external services and tools via MCP.

Continuous improvement through use

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

When a similar task arises later, Hermes can leverage this skill as a foundation. Should the workflow require refinement, the skill can be updated. Additionally, its memory retains key facts and lessons learned from previous activities.

Memory and skills fulfill distinct roles: memory preserves information and context, whereas skills retain procedural knowledge. Combined, they enable Hermes to accumulate understanding of both its knowledge base and how to execute recurring tasks efficiently.

Background automation

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

This functionality supports reporting, monitoring, backups, research, and other regular duties. Scheduled tasks also maintain continuity between executions, enabling them to build upon prior work.

Local and cloud model support

Hermes is not restricted to a single Large Language Model (LLM). It can be connected to local models or supported cloud providers, allowing model changes without altering the agent’s tools, memory, or workflows.

Deploying local models offers greater control over hardware and data processing locations. It also allows Hermes to access local files and resources without transmitting them to external providers.

Installing Hermes

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

For 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

Post-installation, launch the setup wizard to configure your model provider and other preferences:

hermes setup

Consult the Hermes documentation for detailed installation and configuration options.

Deploying Hermes on DaDesktop

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

This is advantageous when the desired model demands more VRAM than your local hardware provides. 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-term workflows without needing to maintain your personal computer in an active state.

Discover more about running local LLMs on DaDesktop.