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Project Overview:

Describe the purpose of the RAG application and the crawling features (page, site, local) that have been implemented. Mention the use of Crawl4AI, FastAPI, and asynchronous processing. • Project Structure: Provide a brief directory tree similar to:

. ├── README.md ├── requirements.txt ├── config.py ├── main.py ├── crawlers │ ├── local │ │ └── crawl_local.py │ ├── page │ │ └── crawl_page.py │ └── site │ └── crawl_site.py └── utils └── logging_config.py

•	Setup and Installation:

Explain how to install dependencies (e.g., pip install -r requirements.txt) and how to set the PYTHONPATH if needed. Include instructions for setting up Playwright:

python -m playwright install chromium

•	Running the Application:

Describe how to start the FastAPI server:

python main.py --mode page --url "https://docs.crawl4ai.com/" --verbose

Also include how to use curl or Postman to send requests to the /crawl endpoint.

•	Testing:

Outline how to run unit tests using pytest:

pytest tests/

  1. Docker

docker run -p 8000:8000 lcl-stewie

3.	Test the Endpoint:

Use curl or Postman to send a POST request to http://localhost:8000/crawl as before.

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