This directory contains various example implementations of Scrapegraph-ai for different use cases. Each example demonstrates how to leverage the power of Scrapegraph-ai for specific scenarios.
Note: While these examples showcase implementations using OpenAI and Ollama, Scrapegraph-ai supports many other LLM providers! Check out our documentation for the full list of supported providers.
- 🧠
smart_scraper/- Advanced web scraping with intelligent content extraction - 🔎
search_graph/- Web search and data retrieval - ⚙️
script_generator_graph/- Automated script generation - 🌐
depth_search_graph/- Deep web crawling and content exploration - 📊
csv_scraper_graph/- Scraping and processing data into CSV format - 📑
xml_scraper_graph/- XML data extraction and processing - 🎤
speech_graph/- Speech processing and analysis - 🔄
omni_scraper_graph/- Universal web scraping for multiple data types - 🔍
omni_search_graph/- Comprehensive search across multiple sources - 📄
document_scraper_graph/- Document parsing and data extraction - 🛠️
custom_graph/- Custom graph implementation examples - 💻
code_generator_graph/- Code generation utilities - 📋
json_scraper_graph/- JSON data extraction and processing - 📋
colab example:
- Choose the example that best fits your use case
- Navigate to the corresponding directory
- Follow the README instructions in each directory
- Configure any required environment variables using the provided
.env.examplefiles
pip install scrapegraphai
playwright install
# choose an example
cd examples/smart_scraper_graph/openai
# run the example
python smart_scraper_openai.pyEach example may have its own specific requirements. Please refer to the individual README files in each directory for detailed setup instructions.
- Check out our documentation
- Join our Discord community
- Open an issue
⭐ Don't forget to star our repository if you find these examples helpful!