ScrapeGraphAI
An open-source Python library for AI-powered web scraping using LLMs
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
Demo Video
Video Reviews
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User Reviews 4
Jason Touleyrou
LinkedInMy first attempt with Scrapegraph-ai was a breeze. It took less than five minutes to set up, and the results were immediate and impressive.
2026-06-03Mehandi Islam
LinkedInThis tool has revolutionized how we approach data collection.
2026-06-03Kuldeep Singh Sidhu
LinkedInAre you tired of writing scripts to scrape data from the web? ScrapeGraphAI is here for you! It's an absolute game-changer.
2026-06-03Thomas Janssen
LinkedInMeet ScrapeGraphAI - a REVOLUTION in Web Scraping. No more hours spent debugging selectors!
2026-06-03Frequently Asked Questions
- 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)
Details
- Category: Productivity
- Industry: Technology
- Access: Open Source
- Pricing: Free
- Created By: Marco Perini, Lorenzo Padoan, and Marco Vinciguerr