awesome-llm-apps-source/starter_ai_agents/web_scraping_ai_agent
xiaowei 5efcd70b4f awesome-llm-apps: 100+ AI Agent & RAG apps (Shubhamsaboo)
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README.md awesome-llm-apps: 100+ AI Agent & RAG apps (Shubhamsaboo) 2026-07-13 19:45:03 +08:00
ai_scrapper.py awesome-llm-apps: 100+ AI Agent & RAG apps (Shubhamsaboo) 2026-07-13 19:45:03 +08:00
local_ai_scrapper.py awesome-llm-apps: 100+ AI Agent & RAG apps (Shubhamsaboo) 2026-07-13 19:45:03 +08:00
requirements.txt awesome-llm-apps: 100+ AI Agent & RAG apps (Shubhamsaboo) 2026-07-13 19:45:03 +08:00

README.md

🕷️ Web Scraping AI Agent

🎓 FREE Step-by-Step Tutorial

👉 Click here to follow our complete step-by-step tutorial and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.

AI-powered web scraping using ScrapeGraphAI - extract structured data from websites using natural language prompts. This agent runs locally with the open-source scrapegraphai library.


📁 What's Inside

Files: ai_scrapper.py, local_ai_scrapper.py

Use the open-source ScrapeGraphAI library that runs on your local machine.

Pros:

  • Free to use (no API costs)
  • Full control over execution
  • Privacy-friendly (all data stays local)

Cons:

  • Requires local installation and dependencies
  • Limited by your hardware
  • Need to manage updates

🚀 Getting Started

  1. Clone the repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/starter_ai_agents/web_scraping_ai_agent
  1. Install dependencies
pip install -r requirements.txt
  1. Get your OpenAI API Key
  1. Run the Streamlit App
streamlit run ai_scrapper.py
# Or for local models:
streamlit run local_ai_scrapper.py

💡 Use Cases

E-commerce Scraping

# Extract product information
prompt = "Extract product names, prices, and availability"

Content Aggregation

# Convert articles to structured data
prompt = "Extract article title, author, date, and main content"

Competitive Intelligence

# Monitor competitor websites
prompt = "Extract pricing, features, and updates"

Lead Generation

# Extract contact information
prompt = "Find company names, emails, and phone numbers"

🔧 How It Works

  1. You provide your OpenAI API key
  2. Select the model (GPT-4o, GPT-5, or local models)
  3. Enter the URL and extraction prompt
  4. The app uses ScrapeGraphAI to scrape and extract data locally
  5. Results are displayed in the app

📖 Documentation