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Quantifying Wisdom. Your personal AI investment boardroom with master personas and professional quantitative scoring tools.

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# 🚀 HiStock AI

"Quantifying Wisdom, Democratizing Alpha."

<a href="./README_zh.md">中文文档</a> •
 <a href="#-quick-start">Quick Start</a> •
 <a href="#-features">Features</a> •
 <a href="#-architecture">Architecture</a>

---

**HiStock AI** is a next-generation **Multi-Agent Investment Research & Debate Platform** tailored for the A-share market. It's your personal "AI Investment Boardroom" — simulating professional debates between legendary investors (Buffett, Munger, Soros, and more) to help you navigate market noise and uncover hidden risks and opportunities.

---

![home_page](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/home_page.png)

## ✨ Features

### 🎯 Multi-Agent Investment Debate
- **AI Boardroom**: Multi-round debates moderated by an AI Host with diverse investment personas

- **Master Personas**: Pre-configured legendary investors including Buffett, Wood, Soros, Lynch, and more

- **Context-Aware Dialog**: Agents respond to each other, forming a dynamic "think tank"

![boardroom](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/boardroom.png)

### 📊 Quantitative Factor Analysis Agent
- **Percentile-Based Scoring**: Factors scored relative to market distribution (0-100), objectively reflecting stock position

- **Weighted Factors**: Configurable weights for PE, ROE, Debt Ratio, etc., supporting personalized scoring models

- **Multi-Dimension Analysis**: Value, Growth, Quality dimensions with customizable weights

- **Industry Normalization**: (In Development) Relative scoring within industry sectors to eliminate valuation bias

![factor_analysis](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/factor_analysis.png)

### 🔍 Factor Market
- **Real-Time Data**: Integrated with AkShare and BaoStock for quotes, valuations, and news

- **Factor Analysis**: Technical indicators (MA, RSI, MACD) and fundamental metrics (PE/PB, ROE)

- **Custom Factors**: Create your own quantitative factors using formula DSL

![market](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/market.png)

### 🧩 Other Specialized Agents
- **News Agent**: Tracks real-time market dynamics and extracts key bullish/bearish signals from massive information

![news_agent](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/news_agent.png)

- **Research Agent**: Deep dives into company filings and financial reports to provide comprehensive fundamental analysis

![research_agent](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/research_agent.png)

- **Master Agent**: Support custom personas, simulating the thinking style and investment logic of legendary investors

![master_agent](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/master_agent.png)

![yz_master_agent](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/yz_master_agent.png)

### ⚙️ Comprehensive Settings
- **Model Management**: Configure DeepSeek, OpenAI, Google, and more with custom Base URL support

- **Agent Configuration**: Visually configure agent parameters and prompts

- **Appearance**: Red/Green up/down color switching to suit different market habits

- **Privacy First**: All API keys stored locally, with one-click factory reset

![model_setting](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/model_setting.png)

![setting](https://raw.githubusercontent.com/xiangking/HiStock/main/assets/setting.png)

### ⚡️ Ultimate User Experience
- **Streaming Response**: Real-time debate stream with progress indicators, making the thinking process visible
- **Dark Mode**: Carefully designed Dark/Light themes that perfectly adapt to system settings
- **Interaction Optimized**: Interface and workflows tailored for A-share investors

---

## 🚀 Quick Start

### Prerequisites
- Python 3.12+
- [uv](https://astral.sh/uv) (Recommended package manager)
- Node.js 18+ (for frontend)

### Installation

```bash
# Clone the repository
git clone https://github.com/HiStock-ai/histock.git
cd histock

# Install Python dependencies
uv sync --group dev

# Install frontend dependencies (optional, for development)
cd frontend && npm install && cd ..
```

### Launch

```bash
# Mac / Linux
bash start.sh

# Windows (PowerShell)
.\start.ps1
```

Access the application at **http://localhost:1420**

### Configure LLM

HiStock AI supports multiple LLM providers:
- **DeepSeek** (Recommended for cost-performance)
- **OpenAI** (GPT-4o, GPT-4)
- **Google** (Gemini)
- **Anthropic** (Claude)

1. Go to **Settings** (bottom left)
2. Add your **API Key**

---

## 🏗️ Architecture

```
histock/
├── python/                    # Backend (Python)
│   └── histock/
│       ├── agents/            # AI Agents (Master, Quantitative, News)
│       ├── core/              # Core Framework (Agent, Session, Message)
│       ├── services/          # Business Services (Factor, Scoring, Stream)
│       ├── server/            # FastAPI Application & Routes
│       ├── adapters/          # Data Adapters (AkShare, BaoStock)
│       ├── config/            # Configuration Management
│       └── utils/             # Utility Functions
├── frontend/                  # Frontend (React)
│   ├── src/app/               # App Routes & Pages
│   ├── src/components/        # UI Components
│   └── src/lib/               # Frontend Utilities
└── assets/                    # Branding Assets
```

### Tech Stack

| Layer | Technology |
|-------|------------|
| Backend | FastAPI, Agno Framework, SQLAlchemy |
| Frontend | React Router 7, Vite, Tailwind CSS, shadcn/ui, Zustand |
| Data | AkShare, BaoStock, TA-Lib |
| AI | Multi-Agent Orchestration, Streaming SSE |

---

## 🔮 Roadmap

- [ ] **Industry Normalization**: Relative scoring within industry sectors (SW/CITIC classification)
- [ ] **Backtesting Module**: Historical factor performance analysis
- [ ] **Portfolio Optimization**: Multi-stock portfolio construction
- [ ] **Mobile App**: React Native companion app

---

## 🙏 Acknowledgements

HiStock AI is proudly built upon the foundation of the **[ValueCell](https://github.com/ValueCell-ai/valuecell)** project. We extend our gratitude to the original creators for their pioneering contributions to the AI investment community.

---

## 🤝 Contributing

We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

---

## ⚠️ Disclaimer

HiStock AI is for **educational and technical research purposes only**. All insights are generated by AI models and do not constitute financial advice. Investing in the stock market involves significant risk.

---

## 📄 License

This project is licensed under the **Apache License 2.0**.

---

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