Add English README file for MiroFish project
- Introduced a new README-EN.md file to provide English documentation for the MiroFish project. - Included an overview of the project, vision, demo videos, quick start guide, and environment variable configuration. - Updated the existing README.md to link to the new English documentation.
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README-EN.md
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<div align="center">
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<img src="./static/image/MiroFish_logo_compressed.jpeg" alt="MiroFish Logo" width="75%"/>
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<strong>简洁通用的群体智能引擎,预测万物</strong>
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<em>A Simple and Universal Swarm Intelligence Engine, Predicting Anything</em>
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[English](./README-EN.md) | [中文文档](./README.md)
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</div>
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## ⚡ Overview
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**MiroFish** is a next-generation AI prediction engine powered by multi-agent technology. By extracting seed information from the real world (such as breaking news, policy drafts, or financial signals), it automatically constructs a high-fidelity parallel digital world. Within this space, thousands of intelligent agents with independent personalities, long-term memory, and behavioral logic freely interact and undergo social evolution. You can inject variables dynamically from a "God's-eye view" to precisely deduce future trajectories — **rehearse the future in a digital sandbox, and win decisions after countless simulations**.
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> You only need to: Upload seed materials (data analysis reports or interesting novel stories) and describe your prediction requirements in natural language
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> MiroFish will return: A detailed prediction report and a deeply interactive high-fidelity digital world
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#### Our Vision
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MiroFish is dedicated to creating a swarm intelligence mirror that maps reality. By capturing the "collective emergence" triggered by individual interactions, we break through the limitations of traditional prediction:
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- **At the Macro Level**: We are a rehearsal laboratory for decision-makers, allowing policies and public relations to be tested at zero risk
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- **At the Micro Level**: We are a creative sandbox for individual users — whether deducing novel endings or exploring imaginative scenarios, everything can be fun, playful, and accessible
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From serious predictions to playful simulations, we let every "what if" see its outcome, making it possible to predict anything.
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## 🎬 Demo Videos - Coming Soon
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1. Complete demo video for prediction based on BettaFish-generated public opinion report
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2. Complete demo video for "Dream of the Red Chamber" ending prediction
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3. Complete demo video for financial prediction
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## 🚀 Quick Start
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### Prerequisites
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| Tool | Version | Description | Check Installation |
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|------|---------|-------------|-------------------|
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| **Node.js** | 18+ | Frontend runtime, includes npm | `node -v` |
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| **Python** | 3.11+ | Backend runtime | `python --version` |
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| **uv** | Latest | Python package manager (pip alternative) | `uv --version` |
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### 1. Configure Environment Variables
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```bash
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# Copy the example configuration file
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cp .env.example .env
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# Edit the .env file and fill in the required API keys
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```
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**Required Environment Variables:**
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```env
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# LLM API Configuration (supports any LLM with OpenAI SDK format)
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# Recommended: Alibaba Qwen-plus model via DashScope: https://dashscope.aliyun.com/
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LLM_API_KEY=your_api_key
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LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
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LLM_MODEL_NAME=qwen-plus
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# Zep Cloud Configuration
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# Free monthly quota is sufficient for usage: https://app.getzep.com/
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ZEP_API_KEY=your_zep_api_key
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```
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### 2. Install Dependencies
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```bash
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# One-click installation of all dependencies (root + frontend + backend)
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npm run setup:all
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```
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Or install step by step:
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```bash
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# Install Node dependencies (root + frontend)
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npm run setup
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# Install Python dependencies (auto-creates virtual environment)
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npm run setup:backend
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```
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### 3. Start Services
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```bash
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# Start both frontend and backend (run from project root)
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npm run dev
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```
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**Service URLs:**
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- Frontend: `http://localhost:3000`
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- Backend API: `http://localhost:5001`
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**Start Individually:**
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```bash
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npm run backend # Start backend only
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npm run frontend # Start frontend only
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```
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## 📄 License
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This project is licensed under the [Apache-2.0 License](./LICENSE).
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25
README.md
25
README.md
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<p align="center">
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<div align="center">
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<img src="./static/image/MiroFish_logo_compressed.jpeg" alt="MiroFish Logo" width="75%"/>
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</p>
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<p align="center">
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<img src="./static/image/MiroFish_logo_compressed.jpeg" alt="MiroFish Logo" width="75%"/>
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<strong>简洁通用的群体智能引擎,预测万物</strong>
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<br />
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<strong>简洁通用的群体智能引擎,预测万物</strong>
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<em>A Simple and Universal Swarm Intelligence Engine, Predicting Anything</em>
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<em>A Simple and Universal Swarm Intelligence Engine, Predicting Anything</em>
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</p>
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[English](./README-EN.md) | [中文文档](./README.md)
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</div>
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## ⚡ 项目概述
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## ⚡ 项目概述
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**MiroFish** 是一款基于多智能体技术的新一代 AI 预测引擎。通过提取现实世界的种子信息(如突发新闻、政策草案、金融信号),自动构建出高保真的平行数字世界。在此空间内,成千上万个具备独立人格、长期记忆与行为逻辑的智能体进行自由交互与社会演化。你可透过「上帝视角」动态注入变量,精准推演未来走向——**让未来在数字沙盘中预演,助决策在百战模拟后胜出**。
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**MiroFish** 是一款基于多智能体技术的新一代 AI 预测引擎。通过提取现实世界的种子信息(如突发新闻、政策草案、金融信号),自动构建出高保真的平行数字世界。在此空间内,成千上万个具备独立人格、长期记忆与行为逻辑的智能体进行自由交互与社会演化。你可透过「上帝视角」动态注入变量,精准推演未来走向——**让未来在数字沙盘中预演,助决策在百战模拟后胜出**。
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> 你只需:上传一份或多份「种子材料」(舆情分析报告、量化分析报告,甚至有趣的小说故事),并用自然语言描述你的模拟/预测需求
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> 你只需:上传种子材料(数据分析报告或者有趣的小说故事),并用自然语言描述预测需求
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> MiroFish 将返回:一份详尽的模拟/预测报告,以及一个可深度交互、可按你意愿持续推演的高保真数字世界
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> MiroFish 将返回:一份详尽的预测报告,以及一个可深度交互的高保真数字世界
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#### 我们的愿景
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#### 我们的愿景
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@ -22,7 +23,7 @@ MiroFish 致力于打造映射现实的群体智能镜像,通过捕捉个体
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- **于宏观**:我们是决策者的预演实验室,让政策与公关在零风险中试错
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- **于宏观**:我们是决策者的预演实验室,让政策与公关在零风险中试错
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- **于微观**:我们是个人用户的创意沙盘,无论是推演小说结局还是探索脑洞,皆可有趣、好玩、触手可及
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- **于微观**:我们是个人用户的创意沙盘,无论是推演小说结局还是探索脑洞,皆可有趣、好玩、触手可及
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从严肃预测到趣味仿真,我们让每一个「如果」都能看见结果,让**预测万物**成为可能。
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从严肃预测到趣味仿真,我们让每一个如果都能看见结果,让预测万物成为可能。
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## 🎬 演示视频-待上传
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## 🎬 演示视频-待上传
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```env
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```env
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# LLM API配置(支持 OpenAI SDK 格式的任意 LLM)
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# LLM API配置(支持 OpenAI SDK 格式的任意 LLM)
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# 推荐使用阿里百炼平台Qwen-plus模型:https://bailian.console.aliyun.com/
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# 推荐使用阿里百炼平台qwen-plus模型:https://bailian.console.aliyun.com/
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LLM_API_KEY=your_api_key
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LLM_API_KEY=your_api_key
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LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
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LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
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LLM_MODEL_NAME=qwen-plus
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LLM_MODEL_NAME=qwen-plus
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