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chore: Update README.md with installation instructions for Crawl4AI library and local server

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unclecode
2024-05-09 19:12:39 +08:00
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@@ -22,11 +22,32 @@ To get started with Crawl4AI, simply visit our web application at [https://crawl
## Installation 💻 ## Installation 💻
To install and run Crawl4AI locally or on your own server, follow these steps: There are two ways to use Crawl4AI: as a library in your Python projects or as a standalone local server.
### Using Crawl4AI as a Library 📚
To install Crawl4AI as a library, follow these steps:
1. Install the package from GitHub:
```
pip install git+https://github.com/unclecode/crawl4ai.git
```
2. Import the necessary modules in your Python script:
```python
from crawler.web_crawler import WebCrawler
from crawler.models import UrlModel
```
3. Use the Crawl4AI library in your project as needed. Refer to the [Usage with Python](#usage-with-python-) section for more details.
### Running Crawl4AI as a Local Server 🚀
To run Crawl4AI as a standalone local server, follow these steps:
1. Clone the repository: 1. Clone the repository:
``` ```
git clone https://github.com/your-username/crawl4ai.git git clone https://github.com/unclecode/crawl4ai.git
``` ```
2. Navigate to the project directory: 2. Navigate to the project directory:
@@ -55,7 +76,9 @@ docker run -p 8000:80 crawl4ai
6. Access the application at `http://localhost:8000`. 6. Access the application at `http://localhost:8000`.
For more detailed instructions and advanced configuration options, please refer to the [installation guide](https://github.com/your-username/crawl4ai/blob/main/INSTALL.md). For more detailed instructions and advanced configuration options, please refer to the [installation guide](https://github.com/unclecode/crawl4ai/blob/main/INSTALL.md).
Choose the approach that best suits your needs. If you want to integrate Crawl4AI into your existing Python projects, installing it as a library is the way to go. If you prefer to run Crawl4AI as a standalone service and interact with it via API endpoints, running it as a local server using Docker is the recommended approach.
## Usage with Python 🐍 ## Usage with Python 🐍