Rezzecup

Agentic crypto trading bot powered by local Llama 3. Chain-of-Thought reasoning across RSI, MACD & live news. 100+ exchanges via CCXT.

16
1
69% credibility
Found Mar 19, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This repository is an open-source AI agent that analyzes cryptocurrency and stock market data, news sentiment, and technical signals to autonomously decide on buy, sell, or hold actions in paper or live trading modes.

How It Works

1
🔍 Discover the Smart Trader

You find this free GitHub tool that acts like a pro trader, using AI to watch crypto and stock markets for you.

2
💻 Bring It Home to Your Computer

Download the files and prepare everything so it's ready to work on your own machine.

3
⚙️ Pick Your Trading Setup

Choose what to trade like Bitcoin, your exchange, and start with pretend money for safety.

4
🧪 Test in Safe Pretend Mode

Start it up and watch it practice trading without using any real money.

5
🧠 Watch It Think and Decide

See it gather price signals, check news feelings, think step-by-step like a human expert, and choose buy, sell, or wait – with full explanations.

6
🚀 Switch to Real Money Trading

Once you're confident from tests, turn on live mode to make actual trades.

📈 Relax with Auto-Trading

Your AI helper now runs by itself, spotting opportunities and handling trades so you can sit back.

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Star Growth

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AI-Generated Review

What is autonomous-ai-trading-agent-llama3?

This Python repo builds an agentic AI crypto trading bot powered by Llama 3, running a perceive-reason-act loop to scan RSI, MACD, EMA crossovers, Bollinger Bands, and live news sentiment for buy/sell/hold calls on crypto pairs. It hooks into 100+ exchanges across Binance, Bybit, OKX, and more via CCXT, with paper trading for safe tests and live mode for real execution—all using local Ollama or Chutes AI for zero-cloud reasoning. Traders get detailed chain-of-thought logs per cycle, solving the black-box problem of rule-based bots.

Why is it gaining traction?

Agentic AI crypto trading shines here with transparent LLM reasoning traces, blending technicals and sentiment without hidden logic, unlike rigid indicator scripts. CLI simplicity—`python agent.py --symbol BTC/USDT --exchange binance --mode paper`—plus YAML config for timeframes and position sizes hooks devs fast. Local fallback and 100+ exchange support make agentic crypto workflows accessible on consumer GPUs.

Who should use this?

Crypto day traders testing agentic AI crypto tokens and coins beyond basic alerts. Devs building github agentic workflows or prototyping crypto agentic AI agents. Quants exploring LLM-driven signals for spot pairs before scaling to portfolios.

Verdict

Worth forking for agentic crypto trading experiments—clean setup, strong README, daily commits despite 16 stars and 0.7% credibility score. Early beta lacks backtesting and dashboard, so paper trade first; production folks wait for v0.4+.

(198 words)

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