Hey everyone! 🚀 For the past few months, I've been building and open-sourcing **Lumina Capital (v6.0.0)**—a fully autonomous multi-agent quantitative hedge fund engine that you can run locally, designed to bridge qualitative LLM reasoning with deterministic quant computation. Unlike toy setups that feed raw charts directly into LLMs (causing massive hallucinations and latency), Lumina strictly separates probabilistic reasoning from deterministic execution: ### 🛠️ Key Highlights: - **7-Persona Anti-Sycophancy Council (LangGraph)**: Personas (Buffett, Soros, Burry, Cathie Wood, etc.) conduct independent parallel analysis, followed by an adversarial bull-vs-bear cross-debate. A dedicated Chief Risk Officer (CRO) agent has absolute veto power over tail risks. - **Pure Python Qlib Alpha158 + LightGBM**: Complete vectorized implementation of Microsoft Qlib's 158 quantitative factors for local stock screening. - **10-Second High-Speed Sentinel Thread**: A deterministic background thread executing immediate physical exits/trailing stops without waiting for LLM inference loops. - **Google TimesFM**: 5-day probabilistic forecasting fan charts with 80% confidence bands and crash probability. - **Works Out-of-the-Box**: CPU-only and lightweight local execution supported via Streamlit dashboard, containerized with 1-click Docker Compose. Available for research, education, and simulation under CC BY-NC 4.0. 🔗 **GitHub**: https://github.com/ramuza0113-sketch/lumina-ai-hedge-fund Would love to hear your thoughts, feedback, or ideas on the local agent architecture!   submitted by   /u/OpenComplaint524 [link]   [comments]