ScrapeGraphAI
by Marco Perini, Lorenzo Padoan, and Marco Vinciguerr
An open-source Python library for AI-powered web scraping using LLMs
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About ScrapeGraphAI
ScrapeGraphAI is a Python library that leverages LLMs and graph logic to automate the creation of scraping pipelines for websites, local documents (XML, HTML, JSON), and other data sources. It aims to simplify web scraping by allowing users to specify the information they need in natural language, and the AI handles the extraction process. The library supports multiple LLMs including GPT, Gemini, Groq, Azure, and local models via Ollama.
Key Features
- Integration with various LLMs,
- Graph-based scraping pipelines,
- Adaptive scraping that can handle website structure changes,
- Support for multiple document formats (HTML XML JSON),
- Easy-to-use API with natural language prompts,
- Flexible deployment options (on-premises cloud)
Use Cases
- Automated web scraping for data collection,
- Extracting information from local documents,
- Market research and data analysis,
- Content aggregation,
- Building datasets for machine learning
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