Crawl4AI - AI RAG and Search Tool
Overview
Crawl4AI is an open-source, LLM-friendly crawler and extraction toolkit purpose-built to gather web content for downstream AI workflows such as retrieval-augmented generation (RAG) and search. The project is presented on GitHub as a crawler that focuses on practical content aggregation: discovery, HTML/text extraction, basic cleaning, and producing structured output that can be consumed by embedding pipelines, vector stores, or downstream document stores. Designed for integration into ML/AI pipelines, Crawl4AI emphasizes being friendly to large-language-model use cases by producing chunked, metadata-rich documents suitable for vectorization and retrieval. The repository framing positions the tool as a bridge between noisy web data and structured inputs for RAG systems, intended for teams wanting an open-source alternative to proprietary crawlers. For details or the latest capabilities, consult the project repository at https://github.com/unclecode/crawl4ai.
Installation
Install via pip:
pip install git+https://github.com/unclecode/crawl4ai.gitgit clone https://github.com/unclecode/crawl4ai.git && cd crawl4ai && pip install -r requirements.txtdocker build -t crawl4ai . && docker run --rm -it crawl4ai Key Features
- Configurable web crawling with respect for robots.txt and rate limits
- HTML extraction and text normalization producing chunked documents for LLM inputs
- Metadata preservation (URL, timestamps, HTTP headers) alongside extracted text
- Exportable output formats to integrate with embedding/vector pipelines
- CLI and programmatic interfaces for scheduled or on-demand crawls
Community
Crawl4AI is an open-source GitHub project (https://github.com/unclecode/crawl4ai). The primary place for issues, feature requests, and contributions is the repository’s issue and pull request tracker. For up-to-date activity, contributors, and discussion threads, check the repository directly. Pricing: null.
Key Information
- Category: RAG and Search
- Type: AI RAG and Search Tool