explaingit

python-telegrambot/ai-auto-trading

Analysis updated 2026-05-18

163TypeScriptAudience · developerComplexity · 5/5LicenseSetup · hard

TLDR

An AI-driven crypto trading bot that lets a language model analyze markets and automatically execute perpetual futures trades on Gate.io and Binance.

Mindmap

mindmap
  root((NexusQuant))
    What it does
      AI Trading Bot
      Crypto Futures
      Automated Decisions
    Exchanges
      Gate.io
      Binance
      Testnet Support
    Risk Management
      ATR Stop Loss
      Partial Profit Taking
      Trade Scoring
    Monitoring
      Health Dashboard
      SQLite Logging
      Multiple AI Models

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Test an AI-driven trading strategy safely on Gate.io or Binance testnets before risking real money.

USE CASE 2

Let a large language model analyze markets and decide trade entries, exits, and position sizing automatically.

USE CASE 3

Use dynamic ATR-based stop-losses and partial profit taking to manage risk on open positions.

USE CASE 4

Monitor the bot's live status and trade history through a health dashboard and local SQLite logs.

What is it built with?

TypeScriptNode.jsSQLite

How does it compare?

python-telegrambot/ai-auto-tradingtsukamg/polymarket-weather-trading-enginesinotrade/shioaji-pro-app
Stars163168157
LanguageTypeScriptTypeScriptTypeScript
Setup difficultyhardmoderatehard
Complexity5/54/54/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires exchange API keys, an AI model API, and careful testnet validation before any live trading.

You can use and modify this freely, but if you run a modified version as a network service, you must offer its source code to users of that service (AGPL-3.0).

In plain English

NexusQuant is an AI-powered cryptocurrency trading bot written in TypeScript that connects to crypto exchanges and executes trades automatically based on market analysis performed by a large language model. The bot treats the AI model as the core decision-maker, it reads market data, selects trading strategies, manages open positions, and controls risk without requiring manual input. It connects to Gate.io and Binance for perpetual futures trading (contracts that let you bet on whether a crypto asset will go up or down). Before trading live, both exchanges offer testnets (simulated environments with fake money) where you can verify the bot's behavior safely. The risk management system is a notable focus: stop-losses are calculated dynamically based on recent volatility (using the ATR, Average True Range, metric), positions are only partially closed at each profit target rather than all at once, and stop-losses are automatically moved to break-even once a trade is sufficiently profitable. The bot also scores each potential trade across four factors before entering, and only acts on trades that meet a minimum threshold. A health monitoring dashboard tracks the system's status in real time. Multiple AI models are supported through a compatible API, including options from various providers. The bot logs all decisions, trades, and account history to a local SQLite database. Node.js 20.19 or newer is required. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
Help me set up NexusQuant to run on a Gate.io testnet so I can safely evaluate the AI trading strategy first.
Prompt 2
Explain how the bot's ATR-based dynamic stop-loss and partial profit-taking system works.
Prompt 3
How does the bot score potential trades across four factors before deciding whether to enter a position?
Prompt 4
Show me how to configure a different AI model provider for NexusQuant's market analysis.
Prompt 5
What does AGPL-3.0 require of me if I modify NexusQuant and run it as a hosted service for others?

Frequently asked questions

What is ai-auto-trading?

An AI-driven crypto trading bot that lets a language model analyze markets and automatically execute perpetual futures trades on Gate.io and Binance.

What language is ai-auto-trading written in?

Mainly TypeScript. The stack also includes TypeScript, Node.js, SQLite.

What license does ai-auto-trading use?

You can use and modify this freely, but if you run a modified version as a network service, you must offer its source code to users of that service (AGPL-3.0).

How hard is ai-auto-trading to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is ai-auto-trading for?

Mainly developer.

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