Merge branch 'main' into release/v0.7.3
This commit is contained in:
unclecode
7
.github/FUNDING.yml
vendored
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7
.github/FUNDING.yml
vendored
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@@ -0,0 +1,7 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
# GitHub Sponsors
|
||||
github: unclecode
|
||||
|
||||
# Custom links for enterprise inquiries (uncomment when ready)
|
||||
# custom: ["https://crawl4ai.com/enterprise"]
|
||||
809
README-first.md
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809
README-first.md
Normal file
@@ -0,0 +1,809 @@
|
||||
# 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper.
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://trendshift.io/repositories/11716" target="_blank"><img src="https://trendshift.io/api/badge/repositories/11716" alt="unclecode%2Fcrawl4ai | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
|
||||
|
||||
[](https://github.com/unclecode/crawl4ai/stargazers)
|
||||
[](https://github.com/unclecode/crawl4ai/network/members)
|
||||
|
||||
[](https://badge.fury.io/py/crawl4ai)
|
||||
[](https://pypi.org/project/crawl4ai/)
|
||||
[](https://pepy.tech/project/crawl4ai)
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
|
||||
<p align="center">
|
||||
<a href="https://x.com/crawl4ai">
|
||||
<img src="https://img.shields.io/badge/Follow%20on%20X-000000?style=for-the-badge&logo=x&logoColor=white" alt="Follow on X" />
|
||||
</a>
|
||||
<a href="https://www.linkedin.com/company/crawl4ai">
|
||||
<img src="https://img.shields.io/badge/Follow%20on%20LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white" alt="Follow on LinkedIn" />
|
||||
</a>
|
||||
<a href="https://discord.gg/jP8KfhDhyN">
|
||||
<img src="https://img.shields.io/badge/Join%20our%20Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white" alt="Join our Discord" />
|
||||
</a>
|
||||
</p>
|
||||
</div>
|
||||
|
||||
Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines. Open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.
|
||||
|
||||
[✨ Check out latest update v0.7.0](#-recent-updates)
|
||||
|
||||
🎉 **Version 0.7.0 is now available!** The Adaptive Intelligence Update introduces groundbreaking features: Adaptive Crawling that learns website patterns, Virtual Scroll support for infinite pages, intelligent Link Preview with 3-layer scoring, Async URL Seeder for massive discovery, and significant performance improvements. [Read the release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.0.md)
|
||||
|
||||
<details>
|
||||
<summary>🤓 <strong>My Personal Story</strong></summary>
|
||||
|
||||
My journey with computers started in childhood when my dad, a computer scientist, introduced me to an Amstrad computer. Those early days sparked a fascination with technology, leading me to pursue computer science and specialize in NLP during my postgraduate studies. It was during this time that I first delved into web crawling, building tools to help researchers organize papers and extract information from publications a challenging yet rewarding experience that honed my skills in data extraction.
|
||||
|
||||
Fast forward to 2023, I was working on a tool for a project and needed a crawler to convert a webpage into markdown. While exploring solutions, I found one that claimed to be open-source but required creating an account and generating an API token. Worse, it turned out to be a SaaS model charging $16, and its quality didn’t meet my standards. Frustrated, I realized this was a deeper problem. That frustration turned into turbo anger mode, and I decided to build my own solution. In just a few days, I created Crawl4AI. To my surprise, it went viral, earning thousands of GitHub stars and resonating with a global community.
|
||||
|
||||
I made Crawl4AI open-source for two reasons. First, it’s my way of giving back to the open-source community that has supported me throughout my career. Second, I believe data should be accessible to everyone, not locked behind paywalls or monopolized by a few. Open access to data lays the foundation for the democratization of AI, a vision where individuals can train their own models and take ownership of their information. This library is the first step in a larger journey to create the best open-source data extraction and generation tool the world has ever seen, built collaboratively by a passionate community.
|
||||
|
||||
Thank you to everyone who has supported this project, used it, and shared feedback. Your encouragement motivates me to dream even bigger. Join us, file issues, submit PRs, or spread the word. Together, we can build a tool that truly empowers people to access their own data and reshape the future of AI.
|
||||
</details>
|
||||
|
||||
## 🧐 Why Crawl4AI?
|
||||
|
||||
1. **Built for LLMs**: Creates smart, concise Markdown optimized for RAG and fine-tuning applications.
|
||||
2. **Lightning Fast**: Delivers results faster with real-time, cost-efficient performance.
|
||||
3. **Flexible Browser Control**: Offers session management, proxies, and custom hooks for seamless data access.
|
||||
4. **Heuristic Intelligence**: Uses advanced algorithms for efficient extraction, reducing reliance on costly models.
|
||||
5. **Open Source & Deployable**: Fully open-source with no API keys—ready for Docker and cloud integration.
|
||||
6. **Thriving Community**: Actively maintained by a vibrant community and the #1 trending GitHub repository.
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
1. Install Crawl4AI:
|
||||
```bash
|
||||
# Install the package
|
||||
pip install -U crawl4ai
|
||||
|
||||
# For pre release versions
|
||||
pip install crawl4ai --pre
|
||||
|
||||
# Run post-installation setup
|
||||
crawl4ai-setup
|
||||
|
||||
# Verify your installation
|
||||
crawl4ai-doctor
|
||||
```
|
||||
|
||||
If you encounter any browser-related issues, you can install them manually:
|
||||
```bash
|
||||
python -m playwright install --with-deps chromium
|
||||
```
|
||||
|
||||
2. Run a simple web crawl with Python:
|
||||
```python
|
||||
import asyncio
|
||||
from crawl4ai import *
|
||||
|
||||
async def main():
|
||||
async with AsyncWebCrawler() as crawler:
|
||||
result = await crawler.arun(
|
||||
url="https://www.nbcnews.com/business",
|
||||
)
|
||||
print(result.markdown)
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
```
|
||||
|
||||
3. Or use the new command-line interface:
|
||||
```bash
|
||||
# Basic crawl with markdown output
|
||||
crwl https://www.nbcnews.com/business -o markdown
|
||||
|
||||
# Deep crawl with BFS strategy, max 10 pages
|
||||
crwl https://docs.crawl4ai.com --deep-crawl bfs --max-pages 10
|
||||
|
||||
# Use LLM extraction with a specific question
|
||||
crwl https://www.example.com/products -q "Extract all product prices"
|
||||
```
|
||||
|
||||
## ✨ Features
|
||||
|
||||
<details>
|
||||
<summary>📝 <strong>Markdown Generation</strong></summary>
|
||||
|
||||
- 🧹 **Clean Markdown**: Generates clean, structured Markdown with accurate formatting.
|
||||
- 🎯 **Fit Markdown**: Heuristic-based filtering to remove noise and irrelevant parts for AI-friendly processing.
|
||||
- 🔗 **Citations and References**: Converts page links into a numbered reference list with clean citations.
|
||||
- 🛠️ **Custom Strategies**: Users can create their own Markdown generation strategies tailored to specific needs.
|
||||
- 📚 **BM25 Algorithm**: Employs BM25-based filtering for extracting core information and removing irrelevant content.
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>📊 <strong>Structured Data Extraction</strong></summary>
|
||||
|
||||
- 🤖 **LLM-Driven Extraction**: Supports all LLMs (open-source and proprietary) for structured data extraction.
|
||||
- 🧱 **Chunking Strategies**: Implements chunking (topic-based, regex, sentence-level) for targeted content processing.
|
||||
- 🌌 **Cosine Similarity**: Find relevant content chunks based on user queries for semantic extraction.
|
||||
- 🔎 **CSS-Based Extraction**: Fast schema-based data extraction using XPath and CSS selectors.
|
||||
- 🔧 **Schema Definition**: Define custom schemas for extracting structured JSON from repetitive patterns.
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🌐 <strong>Browser Integration</strong></summary>
|
||||
|
||||
- 🖥️ **Managed Browser**: Use user-owned browsers with full control, avoiding bot detection.
|
||||
- 🔄 **Remote Browser Control**: Connect to Chrome Developer Tools Protocol for remote, large-scale data extraction.
|
||||
- 👤 **Browser Profiler**: Create and manage persistent profiles with saved authentication states, cookies, and settings.
|
||||
- 🔒 **Session Management**: Preserve browser states and reuse them for multi-step crawling.
|
||||
- 🧩 **Proxy Support**: Seamlessly connect to proxies with authentication for secure access.
|
||||
- ⚙️ **Full Browser Control**: Modify headers, cookies, user agents, and more for tailored crawling setups.
|
||||
- 🌍 **Multi-Browser Support**: Compatible with Chromium, Firefox, and WebKit.
|
||||
- 📐 **Dynamic Viewport Adjustment**: Automatically adjusts the browser viewport to match page content, ensuring complete rendering and capturing of all elements.
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🔎 <strong>Crawling & Scraping</strong></summary>
|
||||
|
||||
- 🖼️ **Media Support**: Extract images, audio, videos, and responsive image formats like `srcset` and `picture`.
|
||||
- 🚀 **Dynamic Crawling**: Execute JS and wait for async or sync for dynamic content extraction.
|
||||
- 📸 **Screenshots**: Capture page screenshots during crawling for debugging or analysis.
|
||||
- 📂 **Raw Data Crawling**: Directly process raw HTML (`raw:`) or local files (`file://`).
|
||||
- 🔗 **Comprehensive Link Extraction**: Extracts internal, external links, and embedded iframe content.
|
||||
- 🛠️ **Customizable Hooks**: Define hooks at every step to customize crawling behavior.
|
||||
- 💾 **Caching**: Cache data for improved speed and to avoid redundant fetches.
|
||||
- 📄 **Metadata Extraction**: Retrieve structured metadata from web pages.
|
||||
- 📡 **IFrame Content Extraction**: Seamless extraction from embedded iframe content.
|
||||
- 🕵️ **Lazy Load Handling**: Waits for images to fully load, ensuring no content is missed due to lazy loading.
|
||||
- 🔄 **Full-Page Scanning**: Simulates scrolling to load and capture all dynamic content, perfect for infinite scroll pages.
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🚀 <strong>Deployment</strong></summary>
|
||||
|
||||
- 🐳 **Dockerized Setup**: Optimized Docker image with FastAPI server for easy deployment.
|
||||
- 🔑 **Secure Authentication**: Built-in JWT token authentication for API security.
|
||||
- 🔄 **API Gateway**: One-click deployment with secure token authentication for API-based workflows.
|
||||
- 🌐 **Scalable Architecture**: Designed for mass-scale production and optimized server performance.
|
||||
- ☁️ **Cloud Deployment**: Ready-to-deploy configurations for major cloud platforms.
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🎯 <strong>Additional Features</strong></summary>
|
||||
|
||||
- 🕶️ **Stealth Mode**: Avoid bot detection by mimicking real users.
|
||||
- 🏷️ **Tag-Based Content Extraction**: Refine crawling based on custom tags, headers, or metadata.
|
||||
- 🔗 **Link Analysis**: Extract and analyze all links for detailed data exploration.
|
||||
- 🛡️ **Error Handling**: Robust error management for seamless execution.
|
||||
- 🔐 **CORS & Static Serving**: Supports filesystem-based caching and cross-origin requests.
|
||||
- 📖 **Clear Documentation**: Simplified and updated guides for onboarding and advanced usage.
|
||||
- 🙌 **Community Recognition**: Acknowledges contributors and pull requests for transparency.
|
||||
|
||||
</details>
|
||||
|
||||
## Try it Now!
|
||||
|
||||
✨ Play around with this [](https://colab.research.google.com/drive/1SgRPrByQLzjRfwoRNq1wSGE9nYY_EE8C?usp=sharing)
|
||||
|
||||
✨ Visit our [Documentation Website](https://docs.crawl4ai.com/)
|
||||
|
||||
## Installation 🛠️
|
||||
|
||||
Crawl4AI offers flexible installation options to suit various use cases. You can install it as a Python package or use Docker.
|
||||
|
||||
<details>
|
||||
<summary>🐍 <strong>Using pip</strong></summary>
|
||||
|
||||
Choose the installation option that best fits your needs:
|
||||
|
||||
### Basic Installation
|
||||
|
||||
For basic web crawling and scraping tasks:
|
||||
|
||||
```bash
|
||||
pip install crawl4ai
|
||||
crawl4ai-setup # Setup the browser
|
||||
```
|
||||
|
||||
By default, this will install the asynchronous version of Crawl4AI, using Playwright for web crawling.
|
||||
|
||||
👉 **Note**: When you install Crawl4AI, the `crawl4ai-setup` should automatically install and set up Playwright. However, if you encounter any Playwright-related errors, you can manually install it using one of these methods:
|
||||
|
||||
1. Through the command line:
|
||||
|
||||
```bash
|
||||
playwright install
|
||||
```
|
||||
|
||||
2. If the above doesn't work, try this more specific command:
|
||||
|
||||
```bash
|
||||
python -m playwright install chromium
|
||||
```
|
||||
|
||||
This second method has proven to be more reliable in some cases.
|
||||
|
||||
---
|
||||
|
||||
### Installation with Synchronous Version
|
||||
|
||||
The sync version is deprecated and will be removed in future versions. If you need the synchronous version using Selenium:
|
||||
|
||||
```bash
|
||||
pip install crawl4ai[sync]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Development Installation
|
||||
|
||||
For contributors who plan to modify the source code:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/unclecode/crawl4ai.git
|
||||
cd crawl4ai
|
||||
pip install -e . # Basic installation in editable mode
|
||||
```
|
||||
|
||||
Install optional features:
|
||||
|
||||
```bash
|
||||
pip install -e ".[torch]" # With PyTorch features
|
||||
pip install -e ".[transformer]" # With Transformer features
|
||||
pip install -e ".[cosine]" # With cosine similarity features
|
||||
pip install -e ".[sync]" # With synchronous crawling (Selenium)
|
||||
pip install -e ".[all]" # Install all optional features
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🐳 <strong>Docker Deployment</strong></summary>
|
||||
|
||||
> 🚀 **Now Available!** Our completely redesigned Docker implementation is here! This new solution makes deployment more efficient and seamless than ever.
|
||||
|
||||
### New Docker Features
|
||||
|
||||
The new Docker implementation includes:
|
||||
- **Browser pooling** with page pre-warming for faster response times
|
||||
- **Interactive playground** to test and generate request code
|
||||
- **MCP integration** for direct connection to AI tools like Claude Code
|
||||
- **Comprehensive API endpoints** including HTML extraction, screenshots, PDF generation, and JavaScript execution
|
||||
- **Multi-architecture support** with automatic detection (AMD64/ARM64)
|
||||
- **Optimized resources** with improved memory management
|
||||
|
||||
### Getting Started
|
||||
|
||||
```bash
|
||||
# Pull and run the latest release candidate
|
||||
docker pull unclecode/crawl4ai:0.7.0
|
||||
docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:0.7.0
|
||||
|
||||
# Visit the playground at http://localhost:11235/playground
|
||||
```
|
||||
|
||||
For complete documentation, see our [Docker Deployment Guide](https://docs.crawl4ai.com/core/docker-deployment/).
|
||||
|
||||
</details>
|
||||
|
||||
---
|
||||
|
||||
### Quick Test
|
||||
|
||||
Run a quick test (works for both Docker options):
|
||||
|
||||
```python
|
||||
import requests
|
||||
|
||||
# Submit a crawl job
|
||||
response = requests.post(
|
||||
"http://localhost:11235/crawl",
|
||||
json={"urls": ["https://example.com"], "priority": 10}
|
||||
)
|
||||
if response.status_code == 200:
|
||||
print("Crawl job submitted successfully.")
|
||||
|
||||
if "results" in response.json():
|
||||
results = response.json()["results"]
|
||||
print("Crawl job completed. Results:")
|
||||
for result in results:
|
||||
print(result)
|
||||
else:
|
||||
task_id = response.json()["task_id"]
|
||||
print(f"Crawl job submitted. Task ID:: {task_id}")
|
||||
result = requests.get(f"http://localhost:11235/task/{task_id}")
|
||||
```
|
||||
|
||||
For more examples, see our [Docker Examples](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/docker_example.py). For advanced configuration, environment variables, and usage examples, see our [Docker Deployment Guide](https://docs.crawl4ai.com/basic/docker-deployment/).
|
||||
|
||||
</details>
|
||||
|
||||
|
||||
## 🔬 Advanced Usage Examples 🔬
|
||||
|
||||
You can check the project structure in the directory [docs/examples](https://github.com/unclecode/crawl4ai/tree/main/docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.
|
||||
|
||||
<details>
|
||||
<summary>📝 <strong>Heuristic Markdown Generation with Clean and Fit Markdown</strong></summary>
|
||||
|
||||
```python
|
||||
import asyncio
|
||||
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
|
||||
from crawl4ai.content_filter_strategy import PruningContentFilter, BM25ContentFilter
|
||||
from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
|
||||
|
||||
async def main():
|
||||
browser_config = BrowserConfig(
|
||||
headless=True,
|
||||
verbose=True,
|
||||
)
|
||||
run_config = CrawlerRunConfig(
|
||||
cache_mode=CacheMode.ENABLED,
|
||||
markdown_generator=DefaultMarkdownGenerator(
|
||||
content_filter=PruningContentFilter(threshold=0.48, threshold_type="fixed", min_word_threshold=0)
|
||||
),
|
||||
# markdown_generator=DefaultMarkdownGenerator(
|
||||
# content_filter=BM25ContentFilter(user_query="WHEN_WE_FOCUS_BASED_ON_A_USER_QUERY", bm25_threshold=1.0)
|
||||
# ),
|
||||
)
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
result = await crawler.arun(
|
||||
url="https://docs.micronaut.io/4.7.6/guide/",
|
||||
config=run_config
|
||||
)
|
||||
print(len(result.markdown.raw_markdown))
|
||||
print(len(result.markdown.fit_markdown))
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🖥️ <strong>Executing JavaScript & Extract Structured Data without LLMs</strong></summary>
|
||||
|
||||
```python
|
||||
import asyncio
|
||||
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
|
||||
from crawl4ai import JsonCssExtractionStrategy
|
||||
import json
|
||||
|
||||
async def main():
|
||||
schema = {
|
||||
"name": "KidoCode Courses",
|
||||
"baseSelector": "section.charge-methodology .w-tab-content > div",
|
||||
"fields": [
|
||||
{
|
||||
"name": "section_title",
|
||||
"selector": "h3.heading-50",
|
||||
"type": "text",
|
||||
},
|
||||
{
|
||||
"name": "section_description",
|
||||
"selector": ".charge-content",
|
||||
"type": "text",
|
||||
},
|
||||
{
|
||||
"name": "course_name",
|
||||
"selector": ".text-block-93",
|
||||
"type": "text",
|
||||
},
|
||||
{
|
||||
"name": "course_description",
|
||||
"selector": ".course-content-text",
|
||||
"type": "text",
|
||||
},
|
||||
{
|
||||
"name": "course_icon",
|
||||
"selector": ".image-92",
|
||||
"type": "attribute",
|
||||
"attribute": "src"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
extraction_strategy = JsonCssExtractionStrategy(schema, verbose=True)
|
||||
|
||||
browser_config = BrowserConfig(
|
||||
headless=False,
|
||||
verbose=True
|
||||
)
|
||||
run_config = CrawlerRunConfig(
|
||||
extraction_strategy=extraction_strategy,
|
||||
js_code=["""(async () => {const tabs = document.querySelectorAll("section.charge-methodology .tabs-menu-3 > div");for(let tab of tabs) {tab.scrollIntoView();tab.click();await new Promise(r => setTimeout(r, 500));}})();"""],
|
||||
cache_mode=CacheMode.BYPASS
|
||||
)
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
|
||||
result = await crawler.arun(
|
||||
url="https://www.kidocode.com/degrees/technology",
|
||||
config=run_config
|
||||
)
|
||||
|
||||
companies = json.loads(result.extracted_content)
|
||||
print(f"Successfully extracted {len(companies)} companies")
|
||||
print(json.dumps(companies[0], indent=2))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>📚 <strong>Extracting Structured Data with LLMs</strong></summary>
|
||||
|
||||
```python
|
||||
import os
|
||||
import asyncio
|
||||
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode, LLMConfig
|
||||
from crawl4ai import LLMExtractionStrategy
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
class OpenAIModelFee(BaseModel):
|
||||
model_name: str = Field(..., description="Name of the OpenAI model.")
|
||||
input_fee: str = Field(..., description="Fee for input token for the OpenAI model.")
|
||||
output_fee: str = Field(..., description="Fee for output token for the OpenAI model.")
|
||||
|
||||
async def main():
|
||||
browser_config = BrowserConfig(verbose=True)
|
||||
run_config = CrawlerRunConfig(
|
||||
word_count_threshold=1,
|
||||
extraction_strategy=LLMExtractionStrategy(
|
||||
# Here you can use any provider that Litellm library supports, for instance: ollama/qwen2
|
||||
# provider="ollama/qwen2", api_token="no-token",
|
||||
llm_config = LLMConfig(provider="openai/gpt-4o", api_token=os.getenv('OPENAI_API_KEY')),
|
||||
schema=OpenAIModelFee.schema(),
|
||||
extraction_type="schema",
|
||||
instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens.
|
||||
Do not miss any models in the entire content. One extracted model JSON format should look like this:
|
||||
{"model_name": "GPT-4", "input_fee": "US$10.00 / 1M tokens", "output_fee": "US$30.00 / 1M tokens"}."""
|
||||
),
|
||||
cache_mode=CacheMode.BYPASS,
|
||||
)
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
result = await crawler.arun(
|
||||
url='https://openai.com/api/pricing/',
|
||||
config=run_config
|
||||
)
|
||||
print(result.extracted_content)
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🤖 <strong>Using Your own Browser with Custom User Profile</strong></summary>
|
||||
|
||||
```python
|
||||
import os, sys
|
||||
from pathlib import Path
|
||||
import asyncio, time
|
||||
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
|
||||
|
||||
async def test_news_crawl():
|
||||
# Create a persistent user data directory
|
||||
user_data_dir = os.path.join(Path.home(), ".crawl4ai", "browser_profile")
|
||||
os.makedirs(user_data_dir, exist_ok=True)
|
||||
|
||||
browser_config = BrowserConfig(
|
||||
verbose=True,
|
||||
headless=True,
|
||||
user_data_dir=user_data_dir,
|
||||
use_persistent_context=True,
|
||||
)
|
||||
run_config = CrawlerRunConfig(
|
||||
cache_mode=CacheMode.BYPASS
|
||||
)
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
url = "ADDRESS_OF_A_CHALLENGING_WEBSITE"
|
||||
|
||||
result = await crawler.arun(
|
||||
url,
|
||||
config=run_config,
|
||||
magic=True,
|
||||
)
|
||||
|
||||
print(f"Successfully crawled {url}")
|
||||
print(f"Content length: {len(result.markdown)}")
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
## ✨ Recent Updates
|
||||
|
||||
### Version 0.7.0 Release Highlights - The Adaptive Intelligence Update
|
||||
|
||||
- **🧠 Adaptive Crawling**: Your crawler now learns and adapts to website patterns automatically:
|
||||
```python
|
||||
config = AdaptiveConfig(
|
||||
confidence_threshold=0.7, # Min confidence to stop crawling
|
||||
max_depth=5, # Maximum crawl depth
|
||||
max_pages=20, # Maximum number of pages to crawl
|
||||
strategy="statistical"
|
||||
)
|
||||
|
||||
async with AsyncWebCrawler() as crawler:
|
||||
adaptive_crawler = AdaptiveCrawler(crawler, config)
|
||||
state = await adaptive_crawler.digest(
|
||||
start_url="https://news.example.com",
|
||||
query="latest news content"
|
||||
)
|
||||
# Crawler learns patterns and improves extraction over time
|
||||
```
|
||||
|
||||
- **🌊 Virtual Scroll Support**: Complete content extraction from infinite scroll pages:
|
||||
```python
|
||||
scroll_config = VirtualScrollConfig(
|
||||
container_selector="[data-testid='feed']",
|
||||
scroll_count=20,
|
||||
scroll_by="container_height",
|
||||
wait_after_scroll=1.0
|
||||
)
|
||||
|
||||
result = await crawler.arun(url, config=CrawlerRunConfig(
|
||||
virtual_scroll_config=scroll_config
|
||||
))
|
||||
```
|
||||
|
||||
- **🔗 Intelligent Link Analysis**: 3-layer scoring system for smart link prioritization:
|
||||
```python
|
||||
link_config = LinkPreviewConfig(
|
||||
query="machine learning tutorials",
|
||||
score_threshold=0.3,
|
||||
concurrent_requests=10
|
||||
)
|
||||
|
||||
result = await crawler.arun(url, config=CrawlerRunConfig(
|
||||
link_preview_config=link_config,
|
||||
score_links=True
|
||||
))
|
||||
# Links ranked by relevance and quality
|
||||
```
|
||||
|
||||
- **🎣 Async URL Seeder**: Discover thousands of URLs in seconds:
|
||||
```python
|
||||
seeder = AsyncUrlSeeder(SeedingConfig(
|
||||
source="sitemap+cc",
|
||||
pattern="*/blog/*",
|
||||
query="python tutorials",
|
||||
score_threshold=0.4
|
||||
))
|
||||
|
||||
urls = await seeder.discover("https://example.com")
|
||||
```
|
||||
|
||||
- **⚡ Performance Boost**: Up to 3x faster with optimized resource handling and memory efficiency
|
||||
|
||||
Read the full details in our [0.7.0 Release Notes](https://docs.crawl4ai.com/blog/release-v0.7.0) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).
|
||||
|
||||
## Version Numbering in Crawl4AI
|
||||
|
||||
Crawl4AI follows standard Python version numbering conventions (PEP 440) to help users understand the stability and features of each release.
|
||||
|
||||
### Version Numbers Explained
|
||||
|
||||
Our version numbers follow this pattern: `MAJOR.MINOR.PATCH` (e.g., 0.4.3)
|
||||
|
||||
#### Pre-release Versions
|
||||
We use different suffixes to indicate development stages:
|
||||
|
||||
- `dev` (0.4.3dev1): Development versions, unstable
|
||||
- `a` (0.4.3a1): Alpha releases, experimental features
|
||||
- `b` (0.4.3b1): Beta releases, feature complete but needs testing
|
||||
- `rc` (0.4.3): Release candidates, potential final version
|
||||
|
||||
#### Installation
|
||||
- Regular installation (stable version):
|
||||
```bash
|
||||
pip install -U crawl4ai
|
||||
```
|
||||
|
||||
- Install pre-release versions:
|
||||
```bash
|
||||
pip install crawl4ai --pre
|
||||
```
|
||||
|
||||
- Install specific version:
|
||||
```bash
|
||||
pip install crawl4ai==0.4.3b1
|
||||
```
|
||||
|
||||
#### Why Pre-releases?
|
||||
We use pre-releases to:
|
||||
- Test new features in real-world scenarios
|
||||
- Gather feedback before final releases
|
||||
- Ensure stability for production users
|
||||
- Allow early adopters to try new features
|
||||
|
||||
For production environments, we recommend using the stable version. For testing new features, you can opt-in to pre-releases using the `--pre` flag.
|
||||
|
||||
## 📖 Documentation & Roadmap
|
||||
|
||||
> 🚨 **Documentation Update Alert**: We're undertaking a major documentation overhaul next week to reflect recent updates and improvements. Stay tuned for a more comprehensive and up-to-date guide!
|
||||
|
||||
For current documentation, including installation instructions, advanced features, and API reference, visit our [Documentation Website](https://docs.crawl4ai.com/).
|
||||
|
||||
To check our development plans and upcoming features, visit our [Roadmap](https://github.com/unclecode/crawl4ai/blob/main/ROADMAP.md).
|
||||
|
||||
<details>
|
||||
<summary>📈 <strong>Development TODOs</strong></summary>
|
||||
|
||||
- [x] 0. Graph Crawler: Smart website traversal using graph search algorithms for comprehensive nested page extraction
|
||||
- [ ] 1. Question-Based Crawler: Natural language driven web discovery and content extraction
|
||||
- [ ] 2. Knowledge-Optimal Crawler: Smart crawling that maximizes knowledge while minimizing data extraction
|
||||
- [ ] 3. Agentic Crawler: Autonomous system for complex multi-step crawling operations
|
||||
- [ ] 4. Automated Schema Generator: Convert natural language to extraction schemas
|
||||
- [ ] 5. Domain-Specific Scrapers: Pre-configured extractors for common platforms (academic, e-commerce)
|
||||
- [ ] 6. Web Embedding Index: Semantic search infrastructure for crawled content
|
||||
- [ ] 7. Interactive Playground: Web UI for testing, comparing strategies with AI assistance
|
||||
- [ ] 8. Performance Monitor: Real-time insights into crawler operations
|
||||
- [ ] 9. Cloud Integration: One-click deployment solutions across cloud providers
|
||||
- [ ] 10. Sponsorship Program: Structured support system with tiered benefits
|
||||
- [ ] 11. Educational Content: "How to Crawl" video series and interactive tutorials
|
||||
|
||||
</details>
|
||||
|
||||
## 🤝 Contributing
|
||||
|
||||
We welcome contributions from the open-source community. Check out our [contribution guidelines](https://github.com/unclecode/crawl4ai/blob/main/CONTRIBUTORS.md) for more information.
|
||||
|
||||
I'll help modify the license section with badges. For the halftone effect, here's a version with it:
|
||||
|
||||
Here's the updated license section:
|
||||
|
||||
## 📄 License & Attribution
|
||||
|
||||
This project is licensed under the Apache License 2.0, attribution is recommended via the badges below. See the [Apache 2.0 License](https://github.com/unclecode/crawl4ai/blob/main/LICENSE) file for details.
|
||||
|
||||
### 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:
|
||||
|
||||
| Theme | Badge |
|
||||
|-------|-------|
|
||||
| **Disco Theme (Animated)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-disco.svg" alt="Powered by Crawl4AI" width="200"/></a> |
|
||||
| **Night Theme (Dark with Neon)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-night.svg" alt="Powered by Crawl4AI" width="200"/></a> |
|
||||
| **Dark Theme (Classic)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-dark.svg" alt="Powered by Crawl4AI" width="200"/></a> |
|
||||
| **Light Theme (Classic)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-light.svg" alt="Powered by Crawl4AI" width="200"/></a> |
|
||||
|
||||
|
||||
HTML code for adding the badges:
|
||||
```html
|
||||
<!-- Disco Theme (Animated) -->
|
||||
<a href="https://github.com/unclecode/crawl4ai">
|
||||
<img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-disco.svg" alt="Powered by Crawl4AI" width="200"/>
|
||||
</a>
|
||||
|
||||
<!-- Night Theme (Dark with Neon) -->
|
||||
<a href="https://github.com/unclecode/crawl4ai">
|
||||
<img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-night.svg" alt="Powered by Crawl4AI" width="200"/>
|
||||
</a>
|
||||
|
||||
<!-- Dark Theme (Classic) -->
|
||||
<a href="https://github.com/unclecode/crawl4ai">
|
||||
<img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-dark.svg" alt="Powered by Crawl4AI" width="200"/>
|
||||
</a>
|
||||
|
||||
<!-- Light Theme (Classic) -->
|
||||
<a href="https://github.com/unclecode/crawl4ai">
|
||||
<img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-light.svg" alt="Powered by Crawl4AI" width="200"/>
|
||||
</a>
|
||||
|
||||
<!-- Simple Shield Badge -->
|
||||
<a href="https://github.com/unclecode/crawl4ai">
|
||||
<img src="https://img.shields.io/badge/Powered%20by-Crawl4AI-blue?style=flat-square" alt="Powered by Crawl4AI"/>
|
||||
</a>
|
||||
```
|
||||
|
||||
#### 2. Text Attribution
|
||||
Add this line to your documentation:
|
||||
```
|
||||
This project uses Crawl4AI (https://github.com/unclecode/crawl4ai) for web data extraction.
|
||||
```
|
||||
|
||||
## 📚 Citation
|
||||
|
||||
If you use Crawl4AI in your research or project, please cite:
|
||||
|
||||
```bibtex
|
||||
@software{crawl4ai2024,
|
||||
author = {UncleCode},
|
||||
title = {Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper},
|
||||
year = {2024},
|
||||
publisher = {GitHub},
|
||||
journal = {GitHub Repository},
|
||||
howpublished = {\url{https://github.com/unclecode/crawl4ai}},
|
||||
commit = {Please use the commit hash you're working with}
|
||||
}
|
||||
```
|
||||
|
||||
Text citation format:
|
||||
```
|
||||
UncleCode. (2024). Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper [Computer software].
|
||||
GitHub. https://github.com/unclecode/crawl4ai
|
||||
```
|
||||
|
||||
## 📧 Contact
|
||||
|
||||
For questions, suggestions, or feedback, feel free to reach out:
|
||||
|
||||
- GitHub: [unclecode](https://github.com/unclecode)
|
||||
- Twitter: [@unclecode](https://twitter.com/unclecode)
|
||||
- Website: [crawl4ai.com](https://crawl4ai.com)
|
||||
|
||||
Happy Crawling! 🕸️🚀
|
||||
|
||||
## 💖 Support Crawl4AI
|
||||
|
||||
> 🎉 **Sponsorship Program Just Launched!** Be among the first 50 **Founding Sponsors** and get permanent recognition in our Hall of Fame!
|
||||
|
||||
Crawl4AI is the #1 trending open-source web crawler with 51K+ stars. Your support ensures we stay independent, innovative, and free forever.
|
||||
|
||||
<div align="center">
|
||||
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
|
||||
</div>
|
||||
|
||||
### 🤝 Sponsorship Tiers
|
||||
|
||||
- **🌱 Believer ($5/mo)**: Join the movement for data democratization
|
||||
- **🚀 Builder ($50/mo)**: Get priority support and early feature access
|
||||
- **💼 Growing Team ($500/mo)**: Bi-weekly syncs and optimization help
|
||||
- **🏢 Data Infrastructure Partner ($2000/mo)**: Full partnership with dedicated support
|
||||
|
||||
**Why sponsor?** Every tier includes real benefits. No more rate-limited APIs. Own your data pipeline. Build data sovereignty together.
|
||||
|
||||
[View All Tiers & Benefits →](https://github.com/sponsors/unclecode)
|
||||
|
||||
### 🏆 Our Sponsors
|
||||
|
||||
#### 👑 Founding Sponsors (First 50)
|
||||
*Be part of history - [Become a Founding Sponsor](https://github.com/sponsors/unclecode)*
|
||||
|
||||
<!-- Founding sponsors will be permanently recognized here -->
|
||||
|
||||
#### Current Sponsors
|
||||
Thank you to all our sponsors who make this project possible!
|
||||
|
||||
<!-- Sponsors will be automatically added here -->
|
||||
|
||||
## 🗾 Mission
|
||||
|
||||
Our mission is to unlock the value of personal and enterprise data by transforming digital footprints into structured, tradeable assets. Crawl4AI empowers individuals and organizations with open-source tools to extract and structure data, fostering a shared data economy.
|
||||
|
||||
We envision a future where AI is powered by real human knowledge, ensuring data creators directly benefit from their contributions. By democratizing data and enabling ethical sharing, we are laying the foundation for authentic AI advancement.
|
||||
|
||||
<details>
|
||||
<summary>🔑 <strong>Key Opportunities</strong></summary>
|
||||
|
||||
- **Data Capitalization**: Transform digital footprints into measurable, valuable assets.
|
||||
- **Authentic AI Data**: Provide AI systems with real human insights.
|
||||
- **Shared Economy**: Create a fair data marketplace that benefits data creators.
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🚀 <strong>Development Pathway</strong></summary>
|
||||
|
||||
1. **Open-Source Tools**: Community-driven platforms for transparent data extraction.
|
||||
2. **Digital Asset Structuring**: Tools to organize and value digital knowledge.
|
||||
3. **Ethical Data Marketplace**: A secure, fair platform for exchanging structured data.
|
||||
|
||||
For more details, see our [full mission statement](./MISSION.md).
|
||||
</details>
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#unclecode/crawl4ai&Date)
|
||||
230
README.md
230
README.md
@@ -10,6 +10,7 @@
|
||||
[](https://badge.fury.io/py/crawl4ai)
|
||||
[](https://pypi.org/project/crawl4ai/)
|
||||
[](https://pepy.tech/project/crawl4ai)
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
|
||||
<p align="center">
|
||||
<a href="https://x.com/crawl4ai">
|
||||
@@ -24,32 +25,33 @@
|
||||
</p>
|
||||
</div>
|
||||
|
||||
Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines. Open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.
|
||||
Crawl4AI turns the web into clean, LLM ready Markdown for RAG, agents, and data pipelines. Fast, controllable, battle tested by a 50k+ star community.
|
||||
|
||||
[✨ Check out latest update v0.7.3](#-recent-updates)
|
||||
[✨ Check out latest update v0.7.0](#-recent-updates)
|
||||
|
||||
🎉 **Version 0.7.3 is now available!** The Multi-Config Intelligence Update brings URL-specific configurations for mixed content crawling, flexible Docker LLM providers, critical bug fixes, and improved documentation. Configure different strategies for docs, blogs, and APIs in a single crawl! [Read the release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/md_v2/blog/releases/0.7.3.md)
|
||||
✨ New in v0.7.0, Adaptive Crawling, Virtual Scroll, Link Preview scoring, Async URL Seeder, big performance gains. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.0.md)
|
||||
|
||||
<details>
|
||||
<summary>🤓 <strong>My Personal Story</strong></summary>
|
||||
|
||||
My journey with computers started in childhood when my dad, a computer scientist, introduced me to an Amstrad computer. Those early days sparked a fascination with technology, leading me to pursue computer science and specialize in NLP during my postgraduate studies. It was during this time that I first delved into web crawling, building tools to help researchers organize papers and extract information from publications a challenging yet rewarding experience that honed my skills in data extraction.
|
||||
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.
|
||||
|
||||
Fast forward to 2023, I was working on a tool for a project and needed a crawler to convert a webpage into markdown. While exploring solutions, I found one that claimed to be open-source but required creating an account and generating an API token. Worse, it turned out to be a SaaS model charging $16, and its quality didn’t meet my standards. Frustrated, I realized this was a deeper problem. That frustration turned into turbo anger mode, and I decided to build my own solution. In just a few days, I created Crawl4AI. To my surprise, it went viral, earning thousands of GitHub stars and resonating with a global community.
|
||||
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 Crawl4AI open-source for two reasons. First, it’s my way of giving back to the open-source community that has supported me throughout my career. Second, I believe data should be accessible to everyone, not locked behind paywalls or monopolized by a few. Open access to data lays the foundation for the democratization of AI, a vision where individuals can train their own models and take ownership of their information. This library is the first step in a larger journey to create the best open-source data extraction and generation tool the world has ever seen, built collaboratively by a passionate community.
|
||||
|
||||
Thank you to everyone who has supported this project, used it, and shared feedback. Your encouragement motivates me to dream even bigger. Join us, file issues, submit PRs, or spread the word. Together, we can build a tool that truly empowers people to access their own data and reshape the future of AI.
|
||||
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.
|
||||
</details>
|
||||
|
||||
## 🧐 Why Crawl4AI?
|
||||
|
||||
1. **Built for LLMs**: Creates smart, concise Markdown optimized for RAG and fine-tuning applications.
|
||||
2. **Lightning Fast**: Delivers results 6x faster with real-time, cost-efficient performance.
|
||||
3. **Flexible Browser Control**: Offers session management, proxies, and custom hooks for seamless data access.
|
||||
4. **Heuristic Intelligence**: Uses advanced algorithms for efficient extraction, reducing reliance on costly models.
|
||||
5. **Open Source & Deployable**: Fully open-source with no API keys—ready for Docker and cloud integration.
|
||||
6. **Thriving Community**: Actively maintained by a vibrant community and the #1 trending GitHub repository.
|
||||
<details>
|
||||
<summary>Why developers pick Crawl4AI</summary>
|
||||
|
||||
- **LLM ready output**, smart Markdown with headings, tables, code, 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**, zero keys, CLI and Docker, cloud friendly
|
||||
</details>
|
||||
|
||||
|
||||
## 🚀 Quick Start
|
||||
|
||||
@@ -101,6 +103,32 @@ crwl https://docs.crawl4ai.com --deep-crawl bfs --max-pages 10
|
||||
crwl https://www.example.com/products -q "Extract all product prices"
|
||||
```
|
||||
|
||||
## 💖 Support Crawl4AI
|
||||
|
||||
> 🎉 **Sponsorship Program Now Open!** After powering 51K+ developers and 1 year of growth, Crawl4AI is launching dedicated support for **startups** and **enterprises**. Be among the first 50 **Founding Sponsors** for permanent recognition in our Hall of Fame.
|
||||
|
||||
Crawl4AI is the #1 trending open-source web crawler on GitHub. Your support keeps it independent, innovative, and free for the community — while giving you direct access to premium benefits.
|
||||
|
||||
<div align="">
|
||||
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
[](https://github.com/sponsors/unclecode)
|
||||
|
||||
</div>
|
||||
|
||||
### 🤝 Sponsorship Tiers
|
||||
|
||||
- **🌱 Believer ($5/mo)** — Join the movement for data democratization
|
||||
- **🚀 Builder ($50/mo)** — Priority support & early access to features
|
||||
- **💼 Growing Team ($500/mo)** — Bi-weekly syncs & optimization help
|
||||
- **🏢 Data Infrastructure Partner ($2000/mo)** — Full partnership with dedicated support
|
||||
|
||||
**Why sponsor?**
|
||||
No rate-limited APIs. No lock-in. Build and own your data pipeline with direct guidance from the creator of Crawl4AI.
|
||||
|
||||
[See All Tiers & Benefits →](https://github.com/sponsors/unclecode)
|
||||
|
||||
|
||||
## ✨ Features
|
||||
|
||||
<details>
|
||||
@@ -273,19 +301,13 @@ The new Docker implementation includes:
|
||||
### Getting Started
|
||||
|
||||
```bash
|
||||
# Pull and run the latest release
|
||||
docker pull unclecode/crawl4ai:0.7.3
|
||||
docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:0.7.3
|
||||
# Pull and run the latest release candidate
|
||||
docker pull unclecode/crawl4ai:0.7.0
|
||||
docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:0.7.0
|
||||
|
||||
# Visit the playground at http://localhost:11235/playground
|
||||
```
|
||||
|
||||
For complete documentation, see our [Docker Deployment Guide](https://docs.crawl4ai.com/core/docker-deployment/).
|
||||
|
||||
</details>
|
||||
|
||||
---
|
||||
|
||||
### Quick Test
|
||||
|
||||
Run a quick test (works for both Docker options):
|
||||
@@ -316,10 +338,11 @@ For more examples, see our [Docker Examples](https://github.com/unclecode/crawl4
|
||||
|
||||
</details>
|
||||
|
||||
---
|
||||
|
||||
## 🔬 Advanced Usage Examples 🔬
|
||||
|
||||
You can check the project structure in the directory [https://github.com/unclecode/crawl4ai/docs/examples](docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.
|
||||
You can check the project structure in the directory [docs/examples](https://github.com/unclecode/crawl4ai/tree/main/docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.
|
||||
|
||||
<details>
|
||||
<summary>📝 <strong>Heuristic Markdown Generation with Clean and Fit Markdown</strong></summary>
|
||||
@@ -478,7 +501,7 @@ if __name__ == "__main__":
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>🤖 <strong>Using You own Browser with Custom User Profile</strong></summary>
|
||||
<summary>🤖 <strong>Using Your own Browser with Custom User Profile</strong></summary>
|
||||
|
||||
```python
|
||||
import os, sys
|
||||
@@ -518,40 +541,7 @@ async def test_news_crawl():
|
||||
|
||||
## ✨ Recent Updates
|
||||
|
||||
### Version 0.7.3 Release Highlights - The Multi-Config Intelligence Update
|
||||
|
||||
- **🎨 Multi-URL Configurations**: Different crawling strategies for different URL patterns in a single batch:
|
||||
```python
|
||||
configs = [
|
||||
# Documentation sites - aggressive caching
|
||||
CrawlerRunConfig(
|
||||
url_matcher=["*docs*", "*documentation*"],
|
||||
cache_mode="write"
|
||||
),
|
||||
# News sites - fresh content, scroll for lazy loading
|
||||
CrawlerRunConfig(
|
||||
url_matcher=lambda url: 'blog' in url or 'news' in url,
|
||||
cache_mode="bypass",
|
||||
js_code="window.scrollTo(0, document.body.scrollHeight/2);"
|
||||
),
|
||||
# Default fallback
|
||||
CrawlerRunConfig()
|
||||
]
|
||||
|
||||
results = await crawler.arun_many(urls, config=configs)
|
||||
```
|
||||
|
||||
- **🐳 Flexible Docker LLM Providers**: Configure LLM providers via environment variables:
|
||||
```bash
|
||||
# Using .llm.env file (recommended)
|
||||
docker run -d --env-file .llm.env -p 11235:11235 unclecode/crawl4ai:latest
|
||||
```
|
||||
|
||||
- **🔧 Bug Fixes & Improvements**: Critical stability fixes for production deployments
|
||||
|
||||
Read the full details in our [0.7.3 Release Notes](https://github.com/unclecode/crawl4ai/blob/main/docs/md_v2/blog/releases/0.7.3.md).
|
||||
|
||||
### Previous Version: 0.7.0 Release Highlights - The Adaptive Intelligence Update
|
||||
### Version 0.7.0 Release Highlights - The Adaptive Intelligence Update
|
||||
|
||||
- **🧠 Adaptive Crawling**: Your crawler now learns and adapts to website patterns automatically:
|
||||
```python
|
||||
@@ -616,97 +606,12 @@ Read the full details in our [0.7.3 Release Notes](https://github.com/unclecode/
|
||||
|
||||
Read the full details in our [0.7.0 Release Notes](https://docs.crawl4ai.com/blog/release-v0.7.0) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).
|
||||
|
||||
### Previous Version: 0.6.0 Release Highlights
|
||||
|
||||
- **🌎 World-aware Crawling**: Set geolocation, language, and timezone for authentic locale-specific content:
|
||||
```python
|
||||
crun_cfg = CrawlerRunConfig(
|
||||
url="https://browserleaks.com/geo", # test page that shows your location
|
||||
locale="en-US", # Accept-Language & UI locale
|
||||
timezone_id="America/Los_Angeles", # JS Date()/Intl timezone
|
||||
geolocation=GeolocationConfig( # override GPS coords
|
||||
latitude=34.0522,
|
||||
longitude=-118.2437,
|
||||
accuracy=10.0,
|
||||
)
|
||||
)
|
||||
```
|
||||
|
||||
- **📊 Table-to-DataFrame Extraction**: Extract HTML tables directly to CSV or pandas DataFrames:
|
||||
```python
|
||||
crawler = AsyncWebCrawler(config=browser_config)
|
||||
await crawler.start()
|
||||
|
||||
try:
|
||||
# Set up scraping parameters
|
||||
crawl_config = CrawlerRunConfig(
|
||||
table_score_threshold=8, # Strict table detection
|
||||
)
|
||||
|
||||
# Execute market data extraction
|
||||
results: List[CrawlResult] = await crawler.arun(
|
||||
url="https://coinmarketcap.com/?page=1", config=crawl_config
|
||||
)
|
||||
|
||||
# Process results
|
||||
raw_df = pd.DataFrame()
|
||||
for result in results:
|
||||
if result.success and result.tables:
|
||||
raw_df = pd.DataFrame(
|
||||
result.tables[0]["rows"],
|
||||
columns=result.tables[0]["headers"],
|
||||
)
|
||||
break
|
||||
print(raw_df.head())
|
||||
|
||||
finally:
|
||||
await crawler.close()
|
||||
```
|
||||
|
||||
- **🚀 Browser Pooling**: Pages launch hot with pre-warmed browser instances for lower latency and memory usage
|
||||
|
||||
- **🕸️ Network and Console Capture**: Full traffic logs and MHTML snapshots for debugging:
|
||||
```python
|
||||
crawler_config = CrawlerRunConfig(
|
||||
capture_network=True,
|
||||
capture_console=True,
|
||||
mhtml=True
|
||||
)
|
||||
```
|
||||
|
||||
- **🔌 MCP Integration**: Connect to AI tools like Claude Code through the Model Context Protocol
|
||||
```bash
|
||||
# Add Crawl4AI to Claude Code
|
||||
claude mcp add --transport sse c4ai-sse http://localhost:11235/mcp/sse
|
||||
```
|
||||
|
||||
- **🖥️ Interactive Playground**: Test configurations and generate API requests with the built-in web interface at `http://localhost:11235//playground`
|
||||
|
||||
- **🐳 Revamped Docker Deployment**: Streamlined multi-architecture Docker image with improved resource efficiency
|
||||
|
||||
- **📱 Multi-stage Build System**: Optimized Dockerfile with platform-specific performance enhancements
|
||||
|
||||
|
||||
### Previous Version: 0.5.0 Major Release Highlights
|
||||
|
||||
- **🚀 Deep Crawling System**: Explore websites beyond initial URLs with BFS, DFS, and BestFirst strategies
|
||||
- **⚡ Memory-Adaptive Dispatcher**: Dynamically adjusts concurrency based on system memory
|
||||
- **🔄 Multiple Crawling Strategies**: Browser-based and lightweight HTTP-only crawlers
|
||||
- **💻 Command-Line Interface**: New `crwl` CLI provides convenient terminal access
|
||||
- **👤 Browser Profiler**: Create and manage persistent browser profiles
|
||||
- **🧠 Crawl4AI Coding Assistant**: AI-powered coding assistant
|
||||
- **🏎️ LXML Scraping Mode**: Fast HTML parsing using the `lxml` library
|
||||
- **🌐 Proxy Rotation**: Built-in support for proxy switching
|
||||
- **🤖 LLM Content Filter**: Intelligent markdown generation using LLMs
|
||||
- **📄 PDF Processing**: Extract text, images, and metadata from PDF files
|
||||
|
||||
Read the full details in our [0.5.0 Release Notes](https://docs.crawl4ai.com/blog/releases/0.5.0.html).
|
||||
|
||||
## Version Numbering in Crawl4AI
|
||||
|
||||
Crawl4AI follows standard Python version numbering conventions (PEP 440) to help users understand the stability and features of each release.
|
||||
|
||||
### Version Numbers Explained
|
||||
<details>
|
||||
<summary>📈 <strong>Version Numbers Explained</strong></summary>
|
||||
|
||||
Our version numbers follow this pattern: `MAJOR.MINOR.PATCH` (e.g., 0.4.3)
|
||||
|
||||
@@ -743,6 +648,8 @@ We use pre-releases to:
|
||||
|
||||
For production environments, we recommend using the stable version. For testing new features, you can opt-in to pre-releases using the `--pre` flag.
|
||||
|
||||
</details>
|
||||
|
||||
## 📖 Documentation & Roadmap
|
||||
|
||||
> 🚨 **Documentation Update Alert**: We're undertaking a major documentation overhaul next week to reflect recent updates and improvements. Stay tuned for a more comprehensive and up-to-date guide!
|
||||
@@ -755,16 +662,16 @@ To check our development plans and upcoming features, visit our [Roadmap](https:
|
||||
<summary>📈 <strong>Development TODOs</strong></summary>
|
||||
|
||||
- [x] 0. Graph Crawler: Smart website traversal using graph search algorithms for comprehensive nested page extraction
|
||||
- [ ] 1. Question-Based Crawler: Natural language driven web discovery and content extraction
|
||||
- [ ] 2. Knowledge-Optimal Crawler: Smart crawling that maximizes knowledge while minimizing data extraction
|
||||
- [ ] 3. Agentic Crawler: Autonomous system for complex multi-step crawling operations
|
||||
- [ ] 4. Automated Schema Generator: Convert natural language to extraction schemas
|
||||
- [ ] 5. Domain-Specific Scrapers: Pre-configured extractors for common platforms (academic, e-commerce)
|
||||
- [ ] 6. Web Embedding Index: Semantic search infrastructure for crawled content
|
||||
- [ ] 7. Interactive Playground: Web UI for testing, comparing strategies with AI assistance
|
||||
- [ ] 8. Performance Monitor: Real-time insights into crawler operations
|
||||
- [x] 1. Question-Based Crawler: Natural language driven web discovery and content extraction
|
||||
- [x] 2. Knowledge-Optimal Crawler: Smart crawling that maximizes knowledge while minimizing data extraction
|
||||
- [x] 3. Agentic Crawler: Autonomous system for complex multi-step crawling operations
|
||||
- [x] 4. Automated Schema Generator: Convert natural language to extraction schemas
|
||||
- [x] 5. Domain-Specific Scrapers: Pre-configured extractors for common platforms (academic, e-commerce)
|
||||
- [x] 6. Web Embedding Index: Semantic search infrastructure for crawled content
|
||||
- [x] 7. Interactive Playground: Web UI for testing, comparing strategies with AI assistance
|
||||
- [x] 8. Performance Monitor: Real-time insights into crawler operations
|
||||
- [ ] 9. Cloud Integration: One-click deployment solutions across cloud providers
|
||||
- [ ] 10. Sponsorship Program: Structured support system with tiered benefits
|
||||
- [x] 10. Sponsorship Program: Structured support system with tiered benefits
|
||||
- [ ] 11. Educational Content: "How to Crawl" video series and interactive tutorials
|
||||
|
||||
</details>
|
||||
@@ -779,12 +686,13 @@ Here's the updated license section:
|
||||
|
||||
## 📄 License & Attribution
|
||||
|
||||
This project is licensed under the Apache License 2.0 with a required attribution clause. See the [Apache 2.0 License](https://github.com/unclecode/crawl4ai/blob/main/LICENSE) file for details.
|
||||
This project is licensed under the Apache License 2.0, attribution is recommended via the badges below. See the [Apache 2.0 License](https://github.com/unclecode/crawl4ai/blob/main/LICENSE) file for details.
|
||||
|
||||
### Attribution Requirements
|
||||
When using Crawl4AI, you must include one of the following attribution methods:
|
||||
|
||||
#### 1. Badge Attribution (Recommended)
|
||||
<details>
|
||||
<summary>📈 <strong>1. Badge Attribution (Recommended)</strong></summary>
|
||||
Add one of these badges to your README, documentation, or website:
|
||||
|
||||
| Theme | Badge |
|
||||
@@ -823,11 +731,15 @@ HTML code for adding the badges:
|
||||
</a>
|
||||
```
|
||||
|
||||
#### 2. Text Attribution
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>📖 <strong>2. Text Attribution</strong></summary>
|
||||
Add this line to your documentation:
|
||||
```
|
||||
This project uses Crawl4AI (https://github.com/unclecode/crawl4ai) for web data extraction.
|
||||
```
|
||||
</details>
|
||||
|
||||
## 📚 Citation
|
||||
|
||||
|
||||
65
SPONSORS.md
Normal file
65
SPONSORS.md
Normal file
@@ -0,0 +1,65 @@
|
||||
# 💖 Sponsors & Supporters
|
||||
|
||||
Thank you to everyone supporting Crawl4AI! Your sponsorship helps keep this project open-source and actively maintained.
|
||||
|
||||
## 👑 Founding Sponsors
|
||||
*The first 50 sponsors who believed in our vision - permanently recognized*
|
||||
|
||||
<!-- Founding sponsors will be listed here with special recognition -->
|
||||
🎉 **Become a Founding Sponsor!** Only [X/50] spots remaining! [Join now →](https://github.com/sponsors/unclecode)
|
||||
|
||||
---
|
||||
|
||||
## 🏢 Data Infrastructure Partners ($2000/month)
|
||||
*These organizations are building their data sovereignty with Crawl4AI at the core*
|
||||
|
||||
<!-- Data Infrastructure Partners will be listed here -->
|
||||
*Be the first Data Infrastructure Partner! [Join us →](https://github.com/sponsors/unclecode)*
|
||||
|
||||
---
|
||||
|
||||
## 💼 Growing Teams ($500/month)
|
||||
*Teams scaling their data extraction with Crawl4AI*
|
||||
|
||||
<!-- Growing Teams will be listed here -->
|
||||
*Your team could be here! [Become a sponsor →](https://github.com/sponsors/unclecode)*
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Builders ($50/month)
|
||||
*Developers and entrepreneurs building with Crawl4AI*
|
||||
|
||||
<!-- Builders will be listed here -->
|
||||
*Join the builders! [Start sponsoring →](https://github.com/sponsors/unclecode)*
|
||||
|
||||
---
|
||||
|
||||
## 🌱 Believers ($5/month)
|
||||
*The community supporting data democratization*
|
||||
|
||||
<!-- Believers will be listed here -->
|
||||
*Thank you to all our community believers!*
|
||||
|
||||
---
|
||||
|
||||
## 🤝 Want to Sponsor?
|
||||
|
||||
Crawl4AI is the #1 trending open-source web crawler. We're building the future of data extraction - where organizations own their data pipelines instead of relying on rate-limited APIs.
|
||||
|
||||
### Available Sponsorship Tiers:
|
||||
- **🌱 Believer** ($5/mo) - Support the movement
|
||||
- **🚀 Builder** ($50/mo) - Priority support & early access
|
||||
- **💼 Growing Team** ($500/mo) - Bi-weekly syncs & optimization
|
||||
- **🏢 Data Infrastructure Partner** ($2000/mo) - Full partnership & dedicated support
|
||||
|
||||
[View all tiers and benefits →](https://github.com/sponsors/unclecode)
|
||||
|
||||
### Enterprise & Custom Partnerships
|
||||
|
||||
Building data extraction at scale? Need dedicated support or infrastructure? Let's talk about a custom partnership.
|
||||
|
||||
📧 Contact: [hello@crawl4ai.com](mailto:hello@crawl4ai.com)
|
||||
|
||||
---
|
||||
|
||||
*This list is updated regularly. Sponsors at $50+ tiers can submit their logos via [hello@crawl4ai.com](mailto:hello@crawl4ai.com)*
|
||||
Reference in New Issue
Block a user