GitHub Trending Reporter

Automatically fetch GitHub Trending data, perform intelligent analysis using LLM, and generate a visualized report website.

中文文档 | English

Online Access

Website: https://wayyoungboy.github.io/github-trending-reporter/

Features

• Automatic Scraping - Automatically fetch GitHub Trending hot projects daily
• AI Analysis - Use LLM for deep analysis and trend insights on projects
• Visual Display - Generate beautiful report websites using Docusaurus
• Automated Scheduling - Fully automated through GitHub Actions

Project Structure

github-trending-reporter/
├── .github/workflows/
│   └── daily_report.yml     # Automated workflow
├── src/                     # Docusaurus frontend source
├── reports/                 # Markdown reports
├── data/                    # JSON raw data
├── scripts/                 # Utility scripts
├── main.py                  # Main program
├── trending_scraper.py      # Scraper module
├── llm_analyzer.py          # LLM analysis module
├── data_pusher.py           # Data push module
├── config.py                # Configuration file
├── docusaurus.config.js     # Docusaurus configuration
├── package.json             # Node.js dependencies
└── requirements.txt         # Python dependencies

Quick Start

Local Run (Report Generation Only)

# Install Python dependencies
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env
# Edit .env and fill in API Key

# Generate report
python main.py --local --no-push

Local Preview Website

# Install Node.js dependencies
npm install

# Start development server
npm start

Configuration

Environment Variables

Variable	Description
LLM_API_KEY	LLM API key
LLM_BASE_URL	LLM API URL
LLM_MODEL	Model name
GITHUB_API_TOKEN	GitHub API Token (for fetching detailed info)
GITHUB_TOKEN	GitHub Token (for pushing data)

GitHub Actions Secrets

Configure in repository Settings → Secrets:

• LLM_API_KEY
• LLM_BASE_URL
• LLM_MODEL
• GITHUB_API_TOKEN

Automation Workflow

1. Scheduled Trigger - Runs automatically every day
2. Data Collection - Scrape GitHub Trending page
3. API Enhancement - Fetch detailed info via GitHub API
4. LLM Analysis - AI deep analysis of projects
5. Report Generation - Output Markdown format reports
6. Website Deployment - Automatically build and deploy to GitHub Pages

Command Line Options

python main.py [OPTIONS]

Options:
  -l, --language TEXT    Filter by programming language (e.g., python, javascript)
  -s, --since TEXT       Time range: daily, weekly, monthly (default: daily)
  --no-push              Don't push to GitHub repository
  --local                Save to local files
  --date TEXT            Specify date (format: YYYY-MM-DD)
  --no-detailed          Skip detailed project analysis

Inspiration

This project is inspired by ai-git-trending, an automated bot for analyzing GitHub Trending. During development, we referenced the project's core architecture and implementation ideas, including:

• GitHub Trending data scraping mechanism
• LLM intelligent analysis workflow
• Automated report generation solution
• Overall project architecture design

We appreciate the excellent work of the original project author for providing valuable reference and inspiration for this project.

Related Links

• GitHub Trending
• Docusaurus
• ai-git-trending - Inspiration Source

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Built with Python + Docusaurus