Trend Tracker ⚡️

Discover trending content from top companies in AI and LLMs, along with insights from your preferred content creators on Twitter or YouTube — all customized for you.

Trend Collector gathers and analyzes content from leading company websites, influential Twitter figures, and popular YouTube channels. Stay ahead with real-time notifications via Slack or Telegram, making this a must-have tool for creators, marketers, and industry professionals.

• Save time by automating data collection and analysis
• Stay informed with updates from your preferred content sources
• Act fast with instant notifications about trends and opportunities

This project was inspired by trendFinder using FireCrawl

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How It Works

1. Data Collection 📥

   • Scrapes news and updates directly from top company websites using Playwright.
   • Monitors tweets from influential figures on Twitter/X.
   • Tracks content from known YouTube channels.
   • Allows users to add custom companies, creators, or channels for personalized monitoring.

2. AI Analysis 🤖

   • Processes collected data with GPT-4o, Gemini or LLAMA3.3.
   • Identify emerging trends and relevant topics.
   • Craft tailored trend insights.

3. Notification System 📢

   • Sends notifications via Slack or Telegram when significant trends are detected.

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Features

• 🤖 AI-powered trend detection
• 🔍 Website monitoring with Playwright
• 🎥 Monitor your loved YouTube channels
• 🔤 Follow influential Twitter
• 💬 Notifications on Slack or Telegram

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Tech Stack

• Runtime: Python 3.10+
• AI/LLM: Litellm for multi-llm access (OpenAI, Gemini, Groq,...)
• Data Sources:
  • Website scraping with Playwright
  • Twitter/X API
  • YouTube Google Data API
• Notifications:
  • Slack Webhooks
  • Telegram Bot API

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Prerequisites

• Python (3.10 or higher)
• Virtual environment manager (e.g., venv, conda)
• API keys for required services

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Environment Variables

Copy .env.example to .env and configure the following variables:

# Required: API key from an LLM providers
OPENAI_API_KEY=your_openai_api_key_here
GEMINI_API_KEY=your_gemini_api_key_here
GROQ_API_KEY=your_groq_api_key

# Required if monitoring Twitter/X trends
X_API_BEARER_TOKEN=your_twitter_api_bearer_token_here

# Required for YouTube channel monitoring
YOUTUBE_API_KEY=your_youtube_api_key_here

# Optional: Slack bot token and channel name for sending slack messages
SLACK_BOT_TOKEN=your_slack_token
SLACK_CHANNEL=your_slack_channel

# Optional: Telegram Bot API token and chat ID
TELEGRAM_BOT_TOKEN=your_telegram_bot_token_here
TELEGRAM_CHAT_ID=your_telegram_chat_id_here

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Getting Started

1. Clone the repository:

   git clone https://github.com/kaymen99/trendTracker.git
   cd trendTracker

2. Set up a virtual environment:

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

3. Install dependencies:

   pip install -r requirements.txt

4. Configure environment variables:

   cp .env.example .env
   # Edit .env with your configuration

5. Run the application:

   python main.py

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Project Structure

trend-collector/
├── src/
│   ├── channels/        # Notification handlers via Slack or Telegram
│   ├── scrapers/        # Scraping and data collection logic
│   ├── constants.py     # File containing all sources links
│   └── trend_tracker.py # Main class for content scraping and AI analysis  
├── .env.example         # Environment variables template
├── requirements.txt     # Python dependencies
└── main.py              # Application entry point

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Contributing

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/amazing-feature).
3. Commit your changes (git commit -m 'Add some amazing feature').
4. Push to the branch (git push origin feature/amazing-feature).
5. Open a Pull Request.

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Contact

If you have any questions or suggestions, feel free to contact me at aymenMir1001@gmail.com.