TrendRadar AI

TrendRadar AI is a professional market-intelligence workstation designed for collecting signals, scoring risk and opportunity, and generating daily strategy reports from multiple news and macro data sources. It features an advanced AI fallback chain for autonomous report generation and flexible usage interfaces.

🌟 Key Features

• Multi-Source Data Collectors: Seamlessly aggregate macro, policy, and developer-signal feeds.
• AI-Powered Generation: Local CLI-based AI fallback chain for accurate daily report synthesis.
• Risk & Opportunity Scoring: Automated evaluation metrics to guide your strategy decisions.
• Multiple Interfaces: Includes a lightweight Streamlit-style UI, a desktop GUI, and CLI support.
• Structured Output: Generates clean daily Markdown and JSON reports stored securely under reports/.

🛠️ Tech Stack

• Language: Python 3.9+
• Data & Parsing: pandas, beautifulsoup4, feedparser
• Network & APIs: requests, aiohttp, yfinance
• User Interface: streamlit, customtkinter, matplotlib
• Code Quality: ruff, black, pytest

🚀 Installation & Setup

1. Clone the Repository

   git clone https://github.com/huangruiran666/TrendRadarAI.git
   cd TrendRadarAI

2. Create a Virtual Environment

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install Dependencies

   pip install -r requirements.txt
   # Alternatively, use the new pyproject.toml
   # pip install -e .

4. Configuration (Optional) You can override default AI commands using environment variables:

   • TRENDRADAR_QWEN_CMD
   • TRENDRADAR_GEMINI_CMD

   If not set, the application will attempt to use qwen chat and gemini chat from your system PATH.

💻 Usage Guide

TrendRadar AI offers multiple modes of operation depending on your workflow.

CLI Mode (Automated Pipeline)

Run the core reporting pipeline directly from your terminal:

python -m src.main

Streamlit Web UI

Launch the browser-based dashboard for interactive data exploration:

python -m src.app_ui

Desktop GUI

Open the native desktop interface (requires a display environment):

python -m src.app_gui

Note: For Windows users, shortcut scripts are available in the scripts/ directory (e.g., scripts/start_gui.bat).

📂 Directory Structure

TrendRadarAI/
├── .github/workflows/    # CI/CD pipelines
├── docs/                 # Documentation files
├── scripts/              # Helper scripts and batch files
├── src/                  # Main application source code
│   ├── app_gui.py        # Desktop GUI application
│   ├── app_ui.py         # Streamlit UI dashboard
│   ├── collectors.py     # Data collection modules
│   ├── engine.py         # AI command & orchestration engine
│   ├── logic.py          # Core processing logic
│   ├── main.py           # CLI entry point
│   ├── parser.py         # Feed & signal parsers
│   └── scoring.py        # Risk and opportunity scoring metrics
├── tests/                # Test suites (runtime and regression)
├── pyproject.toml        # Project metadata and configuration
├── requirements.txt      # Dependency lock file
├── README.md             # This document
└── LICENSE               # MIT License

🤝 Contributing Guidelines

We welcome contributions to TrendRadar AI! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix (git checkout -b feature/your-feature-name).
3. Make your changes and ensure tests pass.
4. Format your code using ruff: ruff format src tests and ruff check src tests.
5. Commit with conventional commit messages (e.g., feat: add new collector for alternative data).
6. Push to your branch and open a Pull Request.

📄 License

This project is licensed under the MIT License.