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Web Scraping with Llama 3.18 Guide

Sep 16, 2024

Lecture Notes: Scraping Websites Using Llama 3.18

Overview

  • Main Topic: Using Llama 3.18 for web scraping instead of GPT models.
  • Example Website: scrape me.if, a dummy website for testing scraping scripts.
  • Scraping Target: Names and prices of Pokémon.

Scraping Process

  • Steps Involved:
    1. Obtain the URL.
    2. Identify fields to scrape.
    3. Initiate the scraping process.
  • Outcome: JSON file generated for use on websites.
  • Cost: Free, with the process occurring on the local machine.

Setting Up Your Environment

  • Code Availability:
    • GitHub account suspension issues.
    • Code setup guidance is available.
  • Setup Steps:
    1. Create a new project folder (e.g., Scrap Master 2.0).
    2. Use VS Code with Python configured.
    3. Create a virtual environment using Python.
    4. Install necessary libraries from a requirements file.
    5. Setup API keys in a .env file.
    6. Download and install the Chrome driver specific to your OS.
    7. Create necessary script files:
      • assets.py
      • scraper.py
      • streamlit_app.py

Running the Application

  • Command: streamlit run app.py
  • Scraping Models:
    • Use different models like GPT, Gro, and Gemini Flash.
  • Model Comparisons:
    • Gro offers speed benefits.
    • Gemini Flash provides cost-effective options.
    • Local models like Llama 3.18 offer flexibility.

Discussion on Models

  • Gro:

    • Enhances speed for scraping multiple websites.
    • Reduces wait times compared to traditional scrapers.

  • Gemini Flash:

    • Offers free and affordable pricing tiers.
    • Suitable for non-commercial, personal scraping needs.

Troubleshooting and Tips

  • Error Handling:
    • Ensure the server for Llama 3 is running.
    • Use LM Studio for setting up Llama 3 servers; it’s user-friendly and free.

Pagination Feature

  • Challenges:

    • Implementing pagination universally across websites.
    • Possible solution: detect URL patterns for multiple pages.

  • Feedback Request:

    • Open for ideas on universal pagination handling.

Conclusion

  • Future Enhancements:

    • Incorporating user feedback for pagination.
    • Exploring more models and features.

  • Call to Action:

    • Engage with the project by providing feedback and ideas.

Note: This session emphasizes practical steps in setting up a web scraping environment using Llama 3.18 and related technologies, focusing on cost-saving and efficiency in scraping operations.

Full transcript