I Built an Always-On AI Assistant for $6/Month — Here's the Full Setup Guide

From Telegram bot to a personal AI that never sleeps — powered by Hermes Agent and Z.AI's GLM-5 Turbo

Imagine having an AI assistant that lives in your Telegram, responds to voice messages, sends you daily stock market briefings, tracks your favorite cricket scores, and can execute code, browse the web, and manage your server — all running autonomously on a $6/month VPS.

That's exactly what I built. No OpenAI API bills. No complex cloud deployments. No subscriptions. Just a single server and a Telegram bot that became my always-on AI companion.

Here's how I did it, step by step.

Why I Wanted This

I was tired of opening ChatGPT in a browser every time I had a question. I wanted something that:

After trying ChatGPT API wrappers, custom LangChain setups, and even local LLMs — none gave me the full package. Then I discovered Hermes Agent.

What is Hermes Agent?

Hermes Agent is an open-source AI agent framework by Nous Research. Think of it as the "brain" that connects an LLM to real-world tools — terminal access, file operations, web browsing, cron scheduling, and messaging platforms like Telegram, Discord, Slack, and WhatsApp.

It's not just a chatbot. It's an agent — it can think, plan, and execute multi-step tasks autonomously.

Key features that sold me:

System Architecture Diagram

The system architecture: You → Telegram → Hermes Agent on VPS → Tools & Services

The Hardware: A $6/Month VPS

Here's the beauty — you don't need expensive hardware.

My setup:

That's it. No GPU. No fancy hardware. Just a basic VPS.

💡 Why no GPU? Hermes uses cloud LLM APIs for inference, so the VPS only runs the agent software itself (lightweight Python). The heavy lifting — model inference — happens on the provider's servers.

Step 1: Server Setup

SSH into your fresh VPS and update the system:

sudo apt update && sudo apt upgrade -y
sudo apt install -y python3 python3-pip python3-venv git curl

Create a dedicated user (don't run as root):

sudo useradd -m -s /bin/bash hermes
sudo usermod -aG sudo hermes
sudo su - hermes

Step 2: Install Hermes Agent

git clone https://github.com/nousresearch/hermes-agent.git ~/.hermes/hermes-agent
cd ~/.hermes/hermes-agent
python3 -m venv venv
source venv/bin/activate
pip install -e .

That's the core installation. Hermes Agent is now on your server.

Step 3: Choose Your LLM Provider

Hermes supports dozens of providers. Here are the main ones:

My choice: Z.AI Coding Plan — GLM-5 Turbo at a very affordable subscription price. Not pay-per-token.

Run the interactive setup wizard:

cd ~/.hermes/hermes-agent
source venv/bin/activate
hermes setup

This walks you through provider selection, API key entry, and model configuration. Credentials are stored securely in ~/.hermes/.env.

Step 4: Connect Telegram

This is where it gets fun — your AI now lives in your phone.

1. Create a Telegram Bot

  1. Open Telegram, search for @BotFather
  2. Send /newbot
  3. Pick a name and username
  4. Copy the bot token

2. Configure Hermes

hermes config set telegram.bot_token "YOUR_BOT_TOKEN"
hermes config set telegram.allowed_users "YOUR_TELEGRAM_ID"
hermes config set telegram.home_channel "YOUR_TELEGRAM_ID"

3. Start the Gateway

hermes gateway run

Message your bot on Telegram. It works!

4. Install as a systemd service

hermes gateway install

This creates a systemd service that auto-starts on boot and restarts if it crashes. Your AI assistant is now always-on.

Step 5: Enable Voice Messages

This was a game-changer. I send voice notes while driving and get voice responses back.

Speech-to-Text (STT) — faster-whisper running locally on CPU:

cd ~/.hermes/hermes-agent
source venv/bin/activate
pip install faster-whisper

In ~/.hermes/config.yaml:

stt:
  enabled: true
  provider: local
  local:
    model: base

The base model downloads automatically (~150 MB) and runs on CPU. Fast enough for real-time transcription.

Text-to-Speech (TTS) — Microsoft Edge TTS (free, no API key):

tts:
  provider: edge
  edge:
    voice: en-US-AriaNeural

voice:
  auto_tts: true
Voice Pipeline Diagram

The voice pipeline: Your Voice → Whisper (local STT) → GLM-5 Turbo → Edge TTS → Voice Reply

Step 6: Enable Tools

Hermes has a rich tool ecosystem. Enable them with:

hermes tools

This opens an interactive selector. For Telegram, I enabled:

After enabling tools, send /reset in Telegram to activate them.

Step 7: Automated Daily Briefings

This is where Hermes went from "cool toy" to "actually useful." I set up three automated daily briefings that arrive in my Telegram every morning:

1. US Stock Market Daily Briefing

hermes cron create \
  --name "US Market Daily Briefing" \
  --schedule "every 1440m" \
  --deliver telegram \
  --prompt "Generate a comprehensive US stock market briefing covering major indices, top movers, sector performance, and key economic indicators."

2. Daily GenAI Briefing

hermes cron create \
  --name "Daily GenAI Briefing" \
  --schedule "0 9 * * *" \
  --deliver telegram \
  --prompt "Search HackerNews, Reddit r/LocalLLaMA, GitHub trending, and arXiv for the latest GenAI news, model releases, and research papers."

3. Indian Market Daily Briefing

hermes cron create \
  --name "Indian Market Daily Briefing" \
  --schedule "every 1440m" \
  --deliver telegram \
  --prompt "Generate a comprehensive Indian stock market briefing covering Sensex, Nifty 50, top gainers/losers, and sector performance."

These run autonomously — Hermes wakes up, does the research, writes the briefing, and delivers it to my Telegram. I wake up to fresh market news every morning.

Plus, I have an IPL cricket score updater that checks scores every 6 hours during match days and sends updates to my Telegram. Because priorities.

Step 8: Persistent Memory

One feature that makes Hermes feel like a real assistant is its persistent memory system.

It remembers:

This memory carries across sessions. I don't have to repeat myself. It's like having an assistant who actually pays attention.

Memory types: User profile (who I am, preferences) + Agent notes (environment facts, lessons learned, tool quirks). Both are stored locally and injected into every conversation automatically.

Step 9: Skills System

Hermes has a skills system that extends its capabilities. Think of skills as reusable recipes for common tasks.

Some of my favorites:

Install skills from the hub:

hermes skills search "docker"
hermes skills install docker-management

Step 10: Maintenance and Monitoring

To keep everything running smoothly, I set up automated maintenance:

# Maintenance script runs every 5 minutes via system crontab
crontab -e
# Add: */5 * * * * /home/hermes/.hermes/scripts/maintenance.sh

The maintenance script handles:

Monitoring commands:

hermes status    # Full system status
hermes doctor    # Diagnostic checks
hermes cron list # View scheduled jobs
hermes update    # Update to latest version

My Daily Workflow

Daily Workflow Infographic

A typical day with Hermes Agent — from morning briefings to evening automation.

Morning: Wake up to three briefing messages — US markets, Indian markets, and GenAI news — already waiting in Telegram. If there's an IPL match, cricket updates too.

Throughout the day:

Evening: No need to check anything. If something important happened, Hermes already told me.

Cost Breakdown

Cost Comparison Chart

Monthly cost comparison — Hermes vs commercial AI subscriptions.

Here's what it costs me:

Compare that to:

The Admin Dashboard: Full Control From Your Browser

One thing I realized after running Hermes for a few weeks — I was SSH'd into my VPS constantly. Checking gateway status. Editing config files. Reading logs. Managing cron jobs. It worked, but it wasn't scalable.

So I built a full admin dashboard.

Hermes Admin Dashboard is a Next.js 16 web application that gives you complete control over your agent from any browser. No additional database, no Docker, no Redis — it reads directly from Hermes' existing data sources (SQLite, YAML, log files).

15 pages. 52 source files. 23 API routes. 74MB RAM.

What you can do from the dashboard:

Exposed through a Cloudflare Tunnel — zero open ports, auto HTTPS, DDoS protection.

Hermes Admin Dashboard - Main overview page

The main dashboard — live system stats, gateway status, connected platforms, and quick action buttons.

Configuration Editor

The configuration editor — structured form for config.yaml with tabs for Models, API Keys, Display, and Gateway.

Cron Jobs Manager

Cron Jobs Manager — create, run, pause, and delete scheduled jobs with one click.

I wrote a detailed article about building the dashboard — architecture, the bugs I hit, security, and performance. Read the full breakdown: "I Built a Full Admin Dashboard for My AI Agent — Here's How" on Medium

Dashboard code: github.com/vinoth12940/hermes-dashboard

Lessons Learned

1. Match your endpoint to your plan. Z.AI has two different API URLs — standard vs coding plan. Using the wrong one gives cryptic "Unknown Model" errors.

2. Never set api_key: '' in config.yaml. An empty string overrides environment variables and breaks everything silently. This caused hours of debugging.

3. Gateway restarts need proper permissions. Running as a systemd service requires passwordless sudoers for the restart command.

4. Local Whisper model names matter. The config should use "base", "tiny", "small" — not OpenAI's "whisper-1" which is an API-only model name.

5. Compression is your friend. Long conversations eat up context windows. Hermes auto-compresses old messages while protecting recent ones.

6. Start simple, then automate. Get the basic chatbot working first. Add voice, then cron jobs, then memory. Don't try to set up everything at once.

What's Next

The beauty of Hermes is that it's extensible. Whatever you can imagine your AI assistant doing, there's probably a way to make it happen.

Final Thoughts

Building an always-on AI assistant used to require a team of engineers, expensive cloud infrastructure, and months of development. Today, with tools like Hermes Agent, a single developer can set up a powerful, autonomous AI assistant in a few hours on a $6/month VPS.

The result isn't just a chatbot. It's a genuine assistant that understands context, remembers preferences, executes tasks, and proactively delivers information. It's the closest thing to having JARVIS in your pocket.

If you're interested in building something similar, the Hermes Agent GitHub repo has excellent documentation and an active community. The setup I've described here took me from zero to a fully functional AI assistant in one afternoon.

The future of personal AI isn't in browser tabs. It's in your messaging apps, running autonomously, always ready.

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