HNMailer - Hacker News AI Digest & Email Reporter

🇨🇳 中文文档

A Python crawler for Hacker News with AI-powered analysis and automated email delivery.

🚀 Features

• Web Interface: Modern responsive UI for browsing news and analysis results
• AI Analysis: Powered by DeepSeek LLM for intelligent news summarization
• Email Reports: Beautiful HTML email reports with daily digest
• Parallel Processing: Multi-threaded analysis for faster performance
• GitHub Actions: Automated daily execution and email delivery
• Multiple Email Providers: Support for Gmail, QQ Mail, 163 Mail, etc.

📦 Quick Start

Installation

pip install -r requirements.txt

Set Environment Variable

export DEEPSEEK_API_KEY="your_api_key_here"

Run Analysis

python example_llm_usage.py

---

🌐 Web Interface

Usage

cd web
python run_web.py

Open browser at http://localhost:8080

Features

• 🎨 Modern responsive UI design
• 📊 Real-time news and analysis display
• 🔄 One-click refresh
• 📱 Mobile-friendly
• ⚡ Live status updates
• 🎯 AI-powered insights

API Endpoints

Endpoint	Description
GET /	Homepage
GET /api/news	Get news data
GET /api/analysis	Get AI analysis results
POST /api/refresh	Refresh data
GET /api/status	Get processing status

---

🤖 LLM Analysis

The project includes an independent LLM analyzer module:

1. News Analysis: Automatic trend analysis and summarization
2. Parallel Processing: Multi-threaded for faster performance
3. Text Summarization: Intelligent content summarization
4. Translation: Multi-language support
5. Insights Generation: Deep analysis on specific topics

Usage

from llm_analyzer import LLMAnalyzer
from example_llm_usage import analyze_news_with_llm

# Parallel analysis (recommended)
analysis_results = analyze_news_with_llm(news_data, parallel=True, max_workers=3)

# Direct analyzer usage
analyzer = LLMAnalyzer()
analysis = analyzer.analyze_news(news_data)
summary = analyzer.summarize_text("Long text content")
translation = analyzer.translate_text("Hello World", "Chinese")

---

📧 GitHub Actions Deployment

Automate daily analysis and email delivery with GitHub Actions.

Setup Steps

1. Push to GitHub

2. Configure Repository Secrets

   Go to: Repository → Settings → Secrets and variables → Actions → New repository secret

   Add the following secrets:

   Secret Name	Description
   DEEPSEEK_API_KEY	DeepSeek API Key (Get here)
   EMAIL_SENDER	Sender email address (e.g., xxx@qq.com)
   EMAIL_PASSWORD	Email authorization code (not login password)
   EMAIL_RECIPIENTS	Recipient emails, comma-separated

3. Enable GitHub Actions

   Go to: Repository → Actions → Click "I understand my workflows, go ahead and enable them"

4. Execution

   • Automatic: Runs daily at 00:00 UTC (08:00 Beijing Time)
   • Manual: Actions page → "Daily HN Analysis" → "Run workflow"

Security

• email_config.ini is in .gitignore and won't be committed
• Sensitive data is securely stored in GitHub Secrets

---

⚙️ Configuration

Local Development

Create email_config.ini:

[qq]
smtp_server = smtp.qq.com
smtp_port = 587
sender_email = your_email@qq.com
sender_password = your_authorization_code
recipient_email = recipient1@example.com, recipient2@example.com

[app]
send_news_count = 20
max_workers = 3
max_comments = 30
topn = 100
model_name = deepseek-chat

Priority

1. Environment Variables (for CI/CD): EMAIL_SENDER, EMAIL_PASSWORD, EMAIL_RECIPIENTS
2. Config File (for local dev): email_config.ini

---

📊 Data Structure

Each news item contains:

Field	Description
id	News ID
rank	Ranking position
title	News title
url	Original link
domain	Source domain
score	Points
comments	Comment count

---

📝 Email Authorization

QQ Mail

1. Login → Settings → Account
2. Enable POP3/SMTP service
3. Generate authorization code

Gmail

1. Enable 2-Step Verification
2. Generate App Password

163 Mail

1. Settings → POP3/SMTP → Enable
2. Get authorization code

---

⚠️ Disclaimer

• Please respect the website's robots.txt rules
• Add appropriate delays to avoid server overload
• This project is for learning and research purposes only

📄 License

MIT License