<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This project offers a framework for experimental cryptocurrency trading using the DeepSeek AI model. It targets users interested in exploring AI-driven trading strategies, emphasizing risk awareness and personal use over production readiness. The core benefit is enabling integration of DeepSeek's capabilities into automated trading workflows.

How It Works

<2-4 sentences on core approach / design (key algorithms, models, data flow, or architectural choices) and why this approach is advantageous or novel.> The system connects to cryptocurrency exchanges like Binance and OKX via API keys, utilizing DeepSeek for trade signal generation. User API credentials and configurations are managed through a .env file. The approach is described as a "black box" strategy, focusing on the AI's output for execution rather than exposing internal decision logic.

Quick Start & Requirements

• Installation: Requires an Ubuntu server. Setup involves installing Anaconda, creating a Python 3.10 environment (conda create -n ds python=3.10), activating it (conda activate ds), installing dependencies (pip install -r requirements.txt), and globally installing pm2 via npm.
• Prerequisites: DeepSeek API Key, Binance API Key/Secret, OKX API Key/Secret/Password. Ubuntu server environment.
• Links: Video tutorial: https://www.youtube.com/watch?v=Yv-AMVaWUVg.

Highlighted Details

• AI-powered automated trading strategy leveraging DeepSeek.
• Exchange integration for Binance and OKX.
• Configuration via .env file.
• Includes a video tutorial for setup.

Maintenance & Community

The provided README content does not contain information regarding project maintenance, contributor activity, community channels (e.g., Discord, Slack), or a public roadmap.

Licensing & Compatibility

No software license is specified in the README. Consequently, its suitability for commercial use or integration within closed-source projects remains undetermined.

Limitations & Caveats

<1-3 sentences on caveats: unsupported platforms, missing features, alpha status, known bugs, breaking changes, bus factor, deprecation, etc. Avoid vague non-statements and judgments.> The project is explicitly positioned as experimental ("搞着玩", "注意风险", "别上头") and employs a "black box" AI methodology, suggesting potential opacity in decision-making. Setup necessitates a dedicated Ubuntu server and the acquisition of exchange-specific API credentials. A minor inconsistency notes Python 3.10 for environment creation but mentions Python 4.10 later (likely a typo).