Swarm intelligence engine for sports prediction - 6 AI agents analyze 971K+ matches across 57 years to forecast tennis outcomes. Built on MiroFish.
<div align="center"> <img src="./static/image/NemoFish_logo_compressed.jpeg" alt="NemoFish Logo" width="65%"/> ### Swarm Intelligence Engine for Predictive Analytics **Multi-agent reasoning · Consensus scoring · Autonomous execution** [](https://github.com/ASGCompute/NemoFish/stargazers) [](./LICENSE) [](https://asgcompute.com) [Quick Start](#-quick-start) · [How It Works](#-how-it-works) · [Dashboard](#-unified-control-room) · [Credits](#-credits) </div> --- ## Overview **NemoFish** is a swarm intelligence platform that coordinates multiple AI agents to generate probabilistic forecasts for competitive sports events. Each agent brings a different analytical lens — statistical modeling, psychological profiling, market signal analysis, scenario simulation — and they reach consensus through weighted voting. The system then scores opportunities by expected value and can execute positions on prediction markets autonomously. This project began as a fork of [**MiroFish**](https://github.com/666ghj/MiroFish), an open-source multi-agent simulation engine developed by the CAMEL-AI research community. We extended MiroFish with a full-stack sports analytics pipeline and a unified control room for real-time monitoring. > **An R&D project by [ASG Compute](https://asgcompute.com)** — exploring whether coordinated multi-agent reasoning can identify inefficiencies in prediction markets. --- ## 📊 Scale & Data Coverage <div align="center"> | Metric | Value | |:-------|------:| | **Historical matches analyzed** | **971,320** | | **Unique players profiled** | **33,962** | | **Tournaments covered** | **9,201** | | **Years of ATP data** | **1968 – 2026** (57 seasons) | | **Surfaces modeled** | Hard · Clay · G
HAL 分层混合模型工作流 — 强模型(Claude)负责理解/拆解/验收,低成本模型(DeepSeek)负责检索/提取/清洗。Hermes Agent skill。
An LLM agent fine-tuned on DeepSeek for spaced repetition, dynamically integrating knowledge points based on the Ebbinghaus forgetting curve.
基于 STM32F103 构建的端到端 AI 智能手表生态。自研“零重定位”原生机器码动态加载引擎与页面栈式 UI 框架;集成生产级 OTA 回滚保护机制与高带宽(921600 baud)串口协议栈。通过 Node.js 中继实现 DeepSeek AI 语义控制及 ASRPRO 语音全双工交互,是一个集成了分布式计算、现代存储管理与 AI Agent 的嵌入式全栈工程。
A Meta-Agent-Driven Self-Evolving Multi-Agent System for UAV Detection and Tracking
One command to run Hermes AI Agent with a browser UI. Zero prerequisites. 一行命令,AI 就位。
网页应用Agent,接入DeepSeek、Mimo等模型