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Alexey Polyakov
Alexey Polyakov

Posted on • Originally published at poliakarmai.github.io

I Built an AI-Native Trading Engine in Python. Here's How It Works

#python #cryptocurrency #trading #opensource

I Built an AI-Native Trading Engine in Python. Here's How It Works

9 strategies, 24/7 WebSocket monitoring, AI scoring, and full agent-based orchestration. Open source, MIT.

Why I Built This

Trading bots are either black-box subscriptions at $50/month, or DIY scripts that break at 3 AM. I wanted a system that:

  • Runs unattended — fire and forget
  • Understands context — not just "RSI < 30 = buy", but scoring across 9 metrics
  • Responds to voice/text — "go AVAX x10" and the AI agent executes everything
  • Is open source — so anyone can fork and customize

That's how bybit-ws was born — an AI-native trading engine for Bybit.

Architecture at a Glance 

┌─────────────────────────────────────────────────┐
│                  Hermes Agent                     │
│  (AI orchestrator: voice, text, auto-entry)      │
└──────────────┬──────────────────────────────────┘
               │ MCP / REST
┌──────────────▼──────────────────────────────────┐
│              bybit-ws (systemd)                   │
│  main.py → 30s cycle                             │
│  ├── auto_entry.py   (LONG via scoring)           │
│  ├── auto_short.py   (SHORT Tier A/B + junk)      │
│  ├── auto_sl.py      (BB-based stop-loss)         │
│  ├── auto_tp.py      (auto take-profit)           │
│  ├── bb_scalp.py     (⚡ x10 M5 scalping)         │
│  ├── mean_revert.py  (⚡ x10 extreme reversals)    │
│  ├── funding_entry.py(⚡ x10 funding momentum)     │
│  ├── dca.py          (ladder entries)              │
│  ├── rpc.py          (HTTP-RPC on port 8766)      │
│  └── dashboard.py    (SVG dashboard)              │
└──────────────┬──────────────────────────────────┘
               │ WebSocket
┌──────────────▼──────────────────────────────────┐
│               Bybit API v5                        │
└─────────────────────────────────────────────────┘
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Core principle: one module = one file. Not a 5,000-line monolith, but 30+ files with clear responsibilities.

9 Strategies — From Conservative to Extreme

Strategy Leverage Timeframe Signal
Bollinger Grid LONG 3x Daily Lower BB −3%
Bollinger Grid SHORT 3x Daily BB >85%
Junk Short 3x Daily Pump ≥80%
SL Re-entry 3x Daily Lower BB after stop
DCA Ladder 3x — −5/−10/−15% from entry
⚡ BB Scalping 10x M5 Band touch + RSI filter
⚡ Mean Reversion 10x Daily BB% <5% or >95%
⚡ Funding Momentum 10x Daily Extreme funding rate
⚡ ATR Risk Sizing layer 15m Validation: SL = 1.5×ATR

The golden rule: the system doesn't guess. Every entry passes through scoring across 8+ metrics:

  • Tier bonus (S/A/B/C/D token)
  • BB% position (0–100%)
  • 24h volume
  • RSI(14)
  • Funding rate
  • BB Squeeze (band compression)
  • Consecutive down days
  • Weekly/monthly BB%

Minimum threshold: 5.5/10. Anything below — the system silently skips.

AI Integration: More Than Buttons

The interesting part is the AI layer. I use Hermes Agent (by Nous Research) as the orchestrator:

  • MCP Server: the agent sees positions, orders, and metrics through a standardized protocol
  • REST API: port 8766, CORS, rate-limiting, RPC token
  • Auto-entry: the agent decides on entries based on scoring
  • GridSignal Bot (@GridSignalBot on Telegram): real-time scanner, LONG/SHORT/x10 buttons

Example interaction:

Me: "go AVAX x10 at market"
Agent: checks BB%, RSI, funding, correlations
       → scoring 7.2/10 → OK
       → calculates: margin=$5, qty=15.1, SL=−5%
       → order placed: 53e99c39
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All via voice or text. While driving, on shift, in the shower — doesn't matter.

Numbers & Hardware

  • Python 3.11, systemd service
  • WebSocket — real-time data from Bybit
  • 30-second light cycle — positions, orders, health
  • 7-minute heavy cycle — scoring, BB, RSI, squeeze, auto-entry
  • Memory: ~200 MB at runtime
  • Uptime: weeks without restart

Roadmap

  • 🔜 Telegram Mini App — dashboard right in Telegram
  • 🔜 Paper trading mode — risk-free testing
  • 🔜 Docker one-liner — docker run and done
  • 🔮 OKX/Binance support — multi-exchange

Try It 

git clone https://github.com/poliakarmai/bybit-ws
cd bybit-ws
cp config.example.yaml config.yaml
# insert your Bybit API keys
systemctl --user enable --now bybit-ws
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GitHub: poliakarmai/bybit-ws
Bot: @GridSignalBot
License: MIT

Questions? Open an issue, message the Telegram bot, or fork and customize. The code is alive, trades real money, and improves every day.

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