`How I "Vibe Coded" an asyncio-first trading engine that bridges the gap between technical indicators and human-scale market context. In the world of algorithmic trading, we've been stuck in a loop. We rely on RSI, MACD, and Bollinger Bands—mathematical formulas designed for an era before high-frequency sentiment and global AI reasoning. While these indicators are foundational, they are blind to context. A human trader doesn't just buy because an RSI hits 30. They look at the shape of the wedge, they read the fear in the headlines, and they interpret the "vibe" of the order book. I wanted to build a bot that doesn't just calculate—it reasons. Meet LLM_Trader v2: An autonomous, vision-capable trading engine that turns market data, news, and chart context into structured BUY/SELL/HOLD/UPDATE decision. LLM_Trader v2 in action. 🏗️ The Architecture: A "Brain" for the Markets Most AI bots fail because they simply dump raw numbers into a prompt. LLM_Trader v2 uses a sophisticated multi-stage pipeline designed for confluence: The Muscles (Market Data): Using ccxt, the bot aggregates data from 5+ major exchanges (Binance, KuCoin, Gate.io, MEXC, Hyperliquid). But it doesn't stop at price—it analyzes: Technical Indicators: (Custom engine, built from scratch without pandas-ta). Order book depth & spread analysis. Trade flow (Buy/Sell ratio, trade velocity). Funding rates for perpetual futures. OHLCV across 7 timeframes: 4H, 12H, 24H, 3D, 7D, 30D, 365D. The Eyes (Vision Engine): The bot renders a ~150 candlestick chart using Plotly, optimized for AI pattern recognition. This image is sent directly...