crawl4ai/docs/md_v2/basic/installation.md

# Installation 💻

Crawl4AI offers flexible installation options to suit various use cases. You can install it as a Python package, use it with Docker, or run it as a local server.

## Option 1: Python Package Installation (Recommended)

Crawl4AI is now available on PyPI, making installation easier than ever. Choose the option that best fits your needs:

### Basic Installation

For basic web crawling and scraping tasks:

```bash
pip install crawl4ai
playwright install # Install Playwright dependencies
```

### Installation with PyTorch

For advanced text clustering (includes CosineSimilarity cluster strategy):

```bash
pip install crawl4ai[torch]
```

### Installation with Transformers

For text summarization and Hugging Face models:

```bash
pip install crawl4ai[transformer]
```

### Full Installation

For all features:

```bash
pip install crawl4ai[all]
```

### 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 ".[all]"
playwright install # Install Playwright dependencies
```

💡 After installation with "torch", "transformer", or "all" options, it's recommended to run the following CLI command to load the required models:

```bash
crawl4ai-download-models
```

This is optional but will boost the performance and speed of the crawler. You only need to do this once after installation.

## Option 2: Using Docker (Coming Soon)

Docker support for Crawl4AI is currently in progress and will be available soon. This will allow you to run Crawl4AI in a containerized environment, ensuring consistency across different systems.

## Option 3: Local Server Installation

For those who prefer to run Crawl4AI as a local server, instructions will be provided once the Docker implementation is complete.

## Verifying Your Installation

After installation, you can verify that Crawl4AI is working correctly by running a simple Python script:

```python
import asyncio
from crawl4ai import AsyncWebCrawler

async def main():
    async with AsyncWebCrawler(verbose=True) as crawler:
        result = await crawler.arun(url="https://www.example.com")
        print(result.markdown[:500])  # Print first 500 characters

if __name__ == "__main__":
    asyncio.run(main())
```

This script should successfully crawl the example website and print the first 500 characters of the extracted content.

## Getting Help

If you encounter any issues during installation or usage, please check the [documentation](https://crawl4ai.com/mkdocs/) or raise an issue on the [GitHub repository](https://github.com/unclecode/crawl4ai/issues).

Happy crawling! 🕷️🤖