This project streamlines the end-to-end workflow for creating and publishing LinkedIn posts from trending AI news.
It automatically:
- Fetches trending AI news
- Analyzes and ranks relevance
- Generates LinkedIn posts using LLMs
- Validates and improves structure
- Scores posts using AI
- Selects the best post
- Publishes to LinkedIn from local execution (manual login step)
- Automated news aggregation
- AI-powered content generation
- Semantic duplicate filtering
- Post validation and rewriting
- AI scoring system
- LinkedIn posting using Playwright
- Python
- OpenRouter (LLMs)
- Sentence Transformers (semantic similarity)
- Playwright (browser automation)
News -> Scrape -> Rank -> Filter -> Generate -> Validate -> Score -> Post
- Clone repo
git clone <your-repo-url>
cd LinkedIn-Automation- Create virtual environment
python -m venv .venv
source .venv/bin/activate- Install dependencies
pip install -r requirements.txt- Set environment variable
export OPENROUTER_API_KEY="your_api_key"- Run
python main.pycookies.jsonis not included for security.- API keys must be set via environment variables.
- Project runs locally and requires LinkedIn login in the browser.
- GitHub Actions automation
- Scheduled posting
- Database integration
- Multi-platform posting
This project is for educational purposes. Use responsibly and respect LinkedIn's terms.