ScrapeGraphAI/Scrapegraph-ai

What it solves

ScrapeGraphAI is a Python library designed to simplify web scraping by replacing manual selector-based scraping with natural language prompts. It allows users to extract specific information from websites or local documents (XML, HTML, JSON, Markdown) without needing to write complex parsing logic for every site.

How it works

The library uses a combination of Large Language Models (LLMs) and direct graph logic to create scraping pipelines. Users provide a prompt describing the data they want and a source URL or file. The system then processes the page content and uses the LLM to extract the requested information into a structured format, such as JSON.

Who it’s for

It is intended for developers and data researchers who need to extract structured data from the web or local files and want to avoid the maintenance burden of traditional scraping scripts.

Highlights

• Multiple Pipeline Types: Includes specialized graphs for single-page extraction (SmartScraperGraph), multi-page extraction (SearchGraph, SmartScraperMultiGraph), and generating Python scripts or audio files (ScriptCreatorGraph, SpeechGraph).
• LLM Flexibility: Supports a wide range of models via APIs (OpenAI, Groq, Gemini, Azure) or locally via Ollama.
• Broad Integration: Integrates with LLM frameworks like LangChain, LlamaIndex, Crew.ai, and low-code tools like Zapier and n8n.
• Local Document Support: Capable of scraping not just websites, but also local files in formats like XML and JSON.