🌐 Global Tech Intelligence

English | 中文

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📖 Introduction

Global Tech Intelligence is an automated information aggregation pipeline designed to track the latest global technology trends. It fetches data from high-quality tech sources, utilizes Google Gemini AI for deep content summarization, and generates structured Daily Briefing reports.

🚀 Key Features

• Multi-Source Aggregation:
  • Hacker News: Fetches top stories and discussions.
  • GitHub: Tracks trending repositories and latest projects (supports filtering by time range).
  • ArXiv: Retrieves the latest academic papers in AI & Computer Vision (cs.CV).
• AI-Powered Summarization: Uses gemini-2.5-flash-lite to generate concise summaries for articles, READMEs, and paper abstracts.
• Automated Reporting: Generates polished Markdown reports in both English and Chinese.
• High Performance: Implements asynchronous concurrent fetching for efficient data processing.

🛠️ Tech Stack

• Core: Python 3.12+
• Network: httpx, BeautifulSoup4
• AI Integration: Google Gemini API
• Utilities: python-dotenv (Config), tenacity (Retries), DeepL (Translation support)

⚙️ Installation & Setup

1. Clone the repository

   git clone https://github.com/AtomChen0425/Global_Trends.git
   cd Global_Trends

2. Install dependencies

pip install httpx beautifulsoup4 python-dotenv tenacity deepl

3. Configure Environment Variables

Create a .env file in the root directory and add your API keys:

GITHUB_TOKEN=your_github_token
GEMINI_API_KEY=your_gemini_api_key
DEEPL_API_KEY=your_deepl_api_key

📝 Usage

Run the main collection script:

python collect_daily_information.py

📂 Project Structure

Global_Trends/
├── collect_daily_information.py  # Main entry point
├── src/
│   ├── FetchPipeline/            # Scrapers for HN, GitHub, ArXiv
│   ├── Generators/               # Markdown report generators
│   ├── utils/                    # AI Agent, Prompt Loader, Translator
│   └── start_work.py             # Orchestration logic
├── prompts/                      # Prompt templates for Gemini
└── reports/                      # Output directory for briefings

GitHub Action Automation

A daily report has been generated in the issue.

Historical data can be found in the reports folder.