最近推送 2026-10-28 21:26(0 天前),属于活跃维护
unclecode/crawl4ai
GITHUB项目档案主语言 Python · 86,455 星 · Apache-2.0 · 创建于 2024-05-09
Open-source web crawler and scraper for LLMs and AI agents: any website into clean, LLM-ready Markdown. Run it yourself, or use Crawl4AI Cloud with one key.
仓库健康度
5 个维度开放 Issue 286 个 · Fork 8,999 个
star 记录还不够天数,增量算不出来
许可证 Apache-2.0 · 8 个 topics · 开了 Wiki
这一项暂无数据,不代表项目没有发布
「证据不足」表示这项数据暂时没有取到,不能读成「项目有问题」;「部分数据」表示只拿到一部分信号。版本发布要额外调 Releases 接口,下一版补。
Star 趋势
1 天记录趋势要至少两天的记录才画得出来。站内从 2026-10-23 开始每天记一次,明天这里就有线了。现在是 1 个点(86455 星)。
README 原文细节
5 个板块核心功能README 里列出来的能力清单
✨ Features
☁️ Same in the cloud: POST /scrape returns this Markdown, with no browser to run. Docs →
☁️ Same in the cloud: POST /extract, with no LLM key of your own. Docs →
☁️ Same in the cloud: up to 50 URLs in one streamed call, or 10,000 in a background job. Docs →
☁️ Rather not run a server? The cloud is the same idea, hosted. Get a key →
- 🧹 Clean Markdown: headings, lists, tables and code blocks, in a structure an LLM reads well.
- 🎯 Fit Markdown: filters remove menus, footers and boilerplate: PruningContentFilterLXML, BM25ContentFilter (for a query) and LLMContentFilter.
- 🔗 Citations: page links become a numbered reference list.
- 🛠️ Your own strategy: plug in a custom Markdown generator.
- 🔎 CSS and XPath schemas: fast extraction with no LLM (JsonCssExtractionStrategy, JsonXPathExtractionStrategy, RegexExtractionStrategy).
- 🪄 Schema generator: describe what you want once; generateschema writes a reusable schema.
- 🤖 LLM extraction: any LLM provider, open-source or hosted, into a typed JSON schema (LLMExtractionStrategy).
- 🧱 Chunking: topic, regex and sentence chunking for long pages.
- 🌌 Cosine similarity: find the chunks that match a query (CosineStrategy).
- 🖥️ Your own browser: persistent profiles with saved logins, cookies and settings.
- 🔄 Remote browsers: connect over the Chrome DevTools Protocol (CDP).
- 🔒 Sessions: keep a browser state across multi-step crawls.
- 🧩 Proxies: with authentication and rotation.
- 🕶️ Stealth mode: enablestealth, and an undetected-browser adapter for sites that detect automation.
怎么安装从零跑起来的步骤
🛠️ Installation
The server needs a token. Without one it answers only inside its container.
The dashboard is at http://localhost:11235/dashboard, the playground at http://localhost:11235/playground. LLM keys, MCP and every setting: Self-hosting guide.
pip install -U crawl4ai
crawl4ai-setup # installs and sets up the browser
crawl4ai-doctor # checks the installation
怎么用最典型的用法与示例
🔬 Advanced usage examples
import asyncio
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
from crawl4ai.content_filter_strategy import PruningContentFilterLXML
from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
async def main():
run_config = CrawlerRunConfig(
cache_mode=CacheMode.BYPASS,
markdown_generator=DefaultMarkdownGenerator(
content_filter=PruningContentFilterLXML(threshold=0.48, threshold_type="fixed", min_word_threshold=0)
环境与依赖跑它之前要准备什么
Attribution Requirements
When using Crawl4AI, you must include one of the following attribution methods:
📈 1. Badge Attribution (Recommended) Add one of these badges to your README, documentation, or website:
- Disco Theme (Animated)
- Night Theme (Dark with Neon)
- Dark Theme (Classic)
- Light Theme (Classic)
其它说明README 里剩下的内容
☁️ Or use the cloud: no browsers, no proxies
The same key works for /extract, /search, /serp, /answer and many URLs at once (/scrape/batch, /scrape/jobs). Pay as you go: live prices. 3. Give it to your AI agent. Claude Code shown; Codex, Cursor and OpenCode →
- Verify your email and 1,000 free credits are yours every month. No card.
- Get any page as Markdown:
Which one?
I grew up on an Amstrad, thanks to my dad, and never stopped building. In grad school I specialized in NLP and built crawlers for research. That’s where I learned how much extraction matters.
In 2023, I needed web-to-Markdown. The “open source” option wanted an account, API token, and $16, and still under-delivered. I went turbo anger mode, built Crawl4AI in days, and it went viral. Now it’s the most-starred crawler on GitHub.
I made it open source for availability, anyone can use it without a gate. Now I’m building the platform for affordability, anyone can run serious crawls without breaking the bank. If that resonates, join in, send feedback, or just crawl something amazing.
- Runs the browsers — you, in your Python process — you, in Docker on your machine — we do
- JS-heavy pages and bot walls — your settings, your proxies — your settings, your proxies — handled for you, automatically
- Web search — – — – — /search, /serp and /answer
- Price — free, forever — free (your hosting) — 1,000 free credits a month; plans from $10
- LLM-ready output: smart Markdown with headings, tables, code and citation hints
- Fast in practice: async browser pool, caching, minimal hops
- Full control: sessions, proxies, cookies, user scripts, hooks
- Adaptive intelligence: learns site patterns, explores only what matters
- Deploy anywhere: no keys needed, CLI and Docker, or the hosted cloud
📖 Documentation
- Library docs, guides and API reference: docs.crawl4ai.com
- Cloud docs: crawl4ai.com/docs
- Release notes: releases · Roadmap: ROADMAP.md
关于 crawl4ai 的常见问题
5 个问题crawl4ai 是做什么的?
unclecode/crawl4ai 是 GitHub 上的开源项目:Open-source web crawler and scraper for LLMs and AI agents: any website into clean, LLM-ready Markdown. Run it yourself, or use Crawl4AI Cloud with one key. Join our Discord https://discord.gg/VuxzM8mtf。README 里的说明是:Crawl4AI turns any website into clean, LLM-ready Markdown for RAG, AI agents and data pipelines. Run the open-source web crawler and scraper yourself, free forever, or use it hosted with one key: /scrape a page to Markdown, /extract it to JSON, /search the…
crawl4ai 有哪些功能?
项目 README 列出的能力包括:🧹 Clean Markdown: headings, lists, tables and code blocks, in a structure an LLM reads well.;🎯 Fit Markdown: filters remove menus, footers and boilerplate: PruningContentFilterLXML, BM25ContentFilter (for a query) and LLMContentFilter.;🔗 Citations: page links become a numbered reference list.;🛠️ Your own strategy: plug in a custom Markdown generator.;🔎 CSS and XPath schemas: fast extraction with no LLM (JsonCssExtractionStrategy, JsonXPathExtractionStrategy, RegexExtractionStrategy).;🪄 Schema generator: describe what you want once; generateschema writes a reusable schema.。
怎么安装 crawl4ai?
按项目 README 的说明:The server needs a token. Without one it answers only inside its container.;The dashboard is at http://localhost:11235/dashboard, the playground at http://localhost:11235/playground. LLM keys, MCP and every setting: 。完整命令见下方「怎么安装」一节或 GitHub 仓库的 README。
运行 crawl4ai 需要什么环境?
README 写明的依赖:Disco Theme (Animated);Night Theme (Dark with Neon);Dark Theme (Classic);Light Theme (Classic)。
crawl4ai 现在还在维护吗?数据怎么样?
目前 86,455 星,8,999 个 Fork,主语言 Python,创建于 2024-05-09,最近一次推送 2026-10-28 21:26,许可证 Apache-2.0。星数、Fork、推送时间都是 GitHub 返回的实时数据,「最近推送」离现在越近说明越活跃;长期不动要留意是否已停止维护。
这些内容来自哪
读法说明项目数据取自 GitHub 官方接口与项目 README;星数、Fork、语言与时间以 GitHub 页面为准,档案更新于 2026-10-28 23:56。
