CryptoTradingAgents
Multi-Agents AI LLM Crypto Financial Trading Framework. 开源多代理加密货币交易决策框架。
System Structure
저장소별 전략/실행 조건 확인 필요
백테스트/분석 결과를 바탕으로 수동 판단
Editor Summary저장소 설명과 공개 메타데이터 기준으로 AI/LLM 또는 머신러닝 활용, Python 기반 구현, 거래소 API/프레임워크, 기술적 분석 성격의 프로젝트로 파악했습니다. 확인 근거는 README, 저장소 토픽, 저장소 설명, GitHub 지표, 파이프라인 필드이며, 주요 데이터는 Binance, OHLCV/호가/체결 데이터입니다. 전략/실행 조건은 저장소별 문서와 코드 확인이 필요하며, 실행 방식은 "백테스트/분석 결과를 바탕으로 수동 판단"라고 보수적으로 기록했습니다. GitHub 지표는 별 270개, 포크 42개입니다.
| Repository | Tomortec/CryptoTradingAgents |
|---|---|
| Creator | Tomortec |
| Stars / Forks | ★ 270 / 42 |
| License | Apache-2.0 |
| Last Updated | 2025-12-22 |
| Snapshot Date | 2026-07-08 (README below is a copy from this date) |
This is third-party open-source code. QuantField does not guarantee its behavior or safety. Review the code before installing or running it.
README
Crypto Trading Agents
🙏 Acknowledgements
This project is based on TradingAgents by the Tauric Research team, as well as the paper arxiv.org/pdf/2412.20138. We extend our sincere thanks for their contributions!
In addition, the following authors and repositories also inspired this project:
| Author | Repository |
|---|---|
| @delenzhang | TradingAgents |
| @hsliuping | TradingAgents-CN |
✨ Key Features
💰 Crypto-Focused
Built upon the TradingAgents framework, specifically adjusted for cryptocurrency assets.
📈 Integrated Technical Analysis
Pulls data from professional technical analysis platforms instead of relying solely on LLM interpretation, reducing unreliable qualitative fluff. Supported Infomation Sources
📰 Targeted News Sources
Collects data from sources frequently used by crypto traders — reliable, relevant, and free! Supported Infomation Sources
❤️ Tailored to Your Trading Style
You can define custom investment preferences—whether you're an aggressive trader or a long-term investor, your style and strategy will be reflected in the report. Configure Investment Preferences
🚀 Incorporate External Reports
You can provide external researches or opinions for consideration—more context leads to better insights. Steps to Use
📄 PDF or Markdown Report Generation
Analysis reports are generated in readable formats.
📧 Scheduled Email Delivery
Combine with OS-level task schedulers to automatically generate and email reports - get market updates like you're the head of a trading desk.
🎥 Real-Time Report Logging
Generated reports are written to log files under ./logs in real time. Even if the process is interrupted or encounters an error, the partial report remains available—ensuring your API usage is never wasted.
⚙️ Fully Customizable
Easily modify or add new data sources. A detailed guide is provided to help you quickly adapt the tool to your needs. Customization
🛠️ Usage Guide
Installation
Clone the repository:
git clone https://github.com/Tomortec/CryptoTradingAgents.git
cd TradingAgents
Create a virtual environment:
conda create -n tradingagents python=3.13
conda activate tradingagents
Install dependencies:
pip install -r requirements.txt
Configuration
1. Configure LLM API Key
Create a .env file under the ./cli directory using `.