hermes agent - Moses Yebei

The Problem

Managing AI agents that can learn and adapt over time is a headache. You want an agent that grows with your needs, but most solutions either lock you into a specific platform or require constant manual intervention. If you're tired of babysitting your bots, you need something that self-improves and keeps pace with your workflow.

What This Does

Enter the hermes-agent. This bad boy allows you to run a self-improving AI agent across various platforms like Telegram, Discord, and Slack, all managed through a single gateway process. The gateway folder contains the core logic for communication across these channels, while the agent directory holds all the heavy lifting for skill creation, context management, and session handling.

The built-in learning loop is a standout feature. It creates skills from experience and nudges itself to retain knowledge. Check out acp_adapter for the adapters that connect your agent's brain to different APIs and tools. The cron folder even handles scheduled tasks, automating daily reports or backups without your intervention.

Real-World Use

Imagine you want to automate daily status reports in Slack and track user interactions over time. You can set up your cron/jobs.py to run a job that pulls data and sends messages. A simple command like hermes report can trigger a skill that compiles the necessary information, leveraging the agent's memory to ensure it uses the most relevant data. If you need to adjust the reporting frequency, just tweak the YAML config in cli-config.yaml.example.

The Bottom Line

hermes-agent is a solid choice for anyone looking to build a scalable AI assistant without the usual vendor lock-in. The combination of a full terminal interface, multi-platform support, and self-improving capabilities is impressive for a project still gaining traction. However, if you’re just looking for a simple bot to handle basic tasks, this might feel like overkill. Save it for when your needs evolve beyond the ordinary.

What the analyser found

Deployment readiness

3/7

Container image
CI pipeline
Lockfile committed
Test suite
README
License
No committed secrets

Composition

200 files

Python117
Markdown32
YAML16
Shell6
JSON3
HTML2

ReactFlask

Architecture

Top-level areas of the codebase, sized by module count. Arrows show how many imports cross from one area into another.

graph TD g0["tests 199 modules"] g1["tools 46 modules"] g2["environments 30 modules"] g3["hermes_cli 26 modules"] g4["gateway 20 modules"] g5["skills 18 modules"] g6["(root) 14 modules"] g0 -->|96| g4 g0 -->|85| g1 g0 -->|49| g3 g0 -->|47| g6 g6 -->|26| g1 g1 -->|14| g3 g6 -->|13| g3 g4 -->|12| g3 g4 -->|12| g1 g3 -->|12| g6 g1 -->|10| g6 g3 -->|7| g1

Module dependencies

The 10 most depended-upon modules of 389, from static import analysis. Red outline marks a module in an import cycle.

graph LR n0_hermes_cli_config["config"] n1_gateway_config["config"] n2_tools_registry["registry"] n3_gateway_platforms_base["base"] n4_run_agent["run_agent"] n5_tools_terminal_tool["terminal_tool"] n6_gateway_session["session"] n7_hermes_cli_auth["auth"] n8_tools_interrupt["interrupt"] n9_cli["cli"] n9_cli --> n4_run_agent n9_cli --> n5_tools_terminal_tool n9_cli --> n7_hermes_cli_auth n9_cli --> n1_gateway_config n1_gateway_config --> n0_hermes_cli_config n3_gateway_platforms_base --> n1_gateway_config n3_gateway_platforms_base --> n6_gateway_session n3_gateway_platforms_base --> n0_hermes_cli_config n6_gateway_session --> n1_gateway_config n7_hermes_cli_auth --> n0_hermes_cli_config n4_run_agent --> n5_tools_terminal_tool n4_run_agent --> n8_tools_interrupt n4_run_agent --> n0_hermes_cli_config n4_run_agent --> n7_hermes_cli_auth n5_tools_terminal_tool --> n8_tools_interrupt n5_tools_terminal_tool --> n2_tools_registry classDef cyc stroke:#ef4444,stroke-width:2px; class n2_tools_registry,n4_run_agent,n5_tools_terminal_tool,n9_cli cyc;