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# Crawl4AI CLI Guide
## Table of Contents
- [Installation](#installation)
- [Basic Usage](#basic-usage)
- [Configuration](#configuration)
- [Browser Configuration](#browser-configuration)
- [Crawler Configuration](#crawler-configuration)
- [Extraction Configuration](#extraction-configuration)
- [Content Filtering](#content-filtering)
- [Advanced Features](#advanced-features)
- [LLM Q&A](#llm-qa)
- [Structured Data Extraction](#structured-data-extraction)
- [Content Filtering](#content-filtering-1)
- [Output Formats](#output-formats)
- [Examples](#examples)
- [Configuration Reference](#configuration-reference)
- [Best Practices & Tips](#best-practices--tips)
## Basic Usage
The Crawl4AI CLI (`crwl`) provides a simple interface to the Crawl4AI library:
```bash
# Basic crawling
crwl https://example.com
# Get markdown output
crwl https://example.com -o markdown
# Verbose JSON output with cache bypass
crwl https://example.com -o json -v --bypass-cache
# See usage examples
crwl --example
```
## Quick Example of Advanced Usage
If you clone the repository and run the following command, you will receive the content of the page in JSON format according to a JSON-CSS schema:
```bash
crwl "https://www.infoq.com/ai-ml-data-eng/" -e docs/examples/cli/extract_css.yml -s docs/examples/cli/css_schema.json -o json;
```
## Configuration
### Browser Configuration
Browser settings can be configured via YAML file or command line parameters:
```yaml
# browser.yml
headless: true
viewport_width: 1280
user_agent_mode: "random"
verbose: true
ignore_https_errors: true
```
```bash
# Using config file
crwl https://example.com -B browser.yml
# Using direct parameters
crwl https://example.com -b "headless=true,viewport_width=1280,user_agent_mode=random"
```
### Crawler Configuration
Control crawling behavior:
```yaml
# crawler.yml
cache_mode: "bypass"
wait_until: "networkidle"
page_timeout: 30000
delay_before_return_html: 0.5
word_count_threshold: 100
scan_full_page: true
scroll_delay: 0.3
process_iframes: false
remove_overlay_elements: true
magic: true
verbose: true
```
```bash
# Using config file
crwl https://example.com -C crawler.yml
# Using direct parameters
crwl https://example.com -c "css_selector=#main,delay_before_return_html=2,scan_full_page=true"
```
### Extraction Configuration
Two types of extraction are supported:
1. CSS/XPath-based extraction:
```yaml
# extract_css.yml
type: "json-css"
params:
verbose: true
```
```json
// css_schema.json
{
"name": "ArticleExtractor",
"baseSelector": ".article",
"fields": [
{
"name": "title",
"selector": "h1.title",
"type": "text"
},
{
"name": "link",
"selector": "a.read-more",
"type": "attribute",
"attribute": "href"
}
]
}
```
2. LLM-based extraction:
```yaml
# extract_llm.yml
type: "llm"
provider: "openai/gpt-4"
instruction: "Extract all articles with their titles and links"
api_token: "your-token"
params:
temperature: 0.3
max_tokens: 1000
```
```json
// llm_schema.json
{
"title": "Article",
"type": "object",
"properties": {
"title": {
"type": "string",
"description": "The title of the article"
},
"link": {
"type": "string",
"description": "URL to the full article"
}
}
}
```
## Advanced Features
### LLM Q&A
Ask questions about crawled content:
```bash
# Simple question
crwl https://example.com -q "What is the main topic discussed?"
# View content then ask questions
crwl https://example.com -o markdown # See content first
crwl https://example.com -q "Summarize the key points"
crwl https://example.com -q "What are the conclusions?"
# Combined with advanced crawling
crwl https://example.com \
-B browser.yml \
-c "css_selector=article,scan_full_page=true" \
-q "What are the pros and cons mentioned?"
```
First-time setup:
- Prompts for LLM provider and API token
- Saves configuration in `~/.crawl4ai/global.yml`
- Supports various providers (openai/gpt-4, anthropic/claude-3-sonnet, etc.)
- For case of `ollama` you do not need to provide API token.
- See [LiteLLM Providers](https://docs.litellm.ai/docs/providers) for full list
### Structured Data Extraction
Extract structured data using CSS selectors:
```bash
crwl https://example.com \
-e extract_css.yml \
-s css_schema.json \
-o json
```
Or using LLM-based extraction:
```bash
crwl https://example.com \
-e extract_llm.yml \
-s llm_schema.json \
-o json
```
### Content Filtering
Filter content for relevance:
```yaml
# filter_bm25.yml
type: "bm25"
query: "target content"
threshold: 1.0
# filter_pruning.yml
type: "pruning"
query: "focus topic"
threshold: 0.48
```
```bash
crwl https://example.com -f filter_bm25.yml -o markdown-fit
```
## Output Formats
- `all` - Full crawl result including metadata
- `json` - Extracted structured data (when using extraction)
- `markdown` / `md` - Raw markdown output
- `markdown-fit` / `md-fit` - Filtered markdown for better readability
## Complete Examples
1. Basic Extraction:
```bash
crwl https://example.com \
-B browser.yml \
-C crawler.yml \
-o json
```
2. Structured Data Extraction:
```bash
crwl https://example.com \
-e extract_css.yml \
-s css_schema.json \
-o json \
-v
```
3. LLM Extraction with Filtering:
```bash
crwl https://example.com \
-B browser.yml \
-e extract_llm.yml \
-s llm_schema.json \
-f filter_bm25.yml \
-o json
```
4. Interactive Q&A:
```bash
# First crawl and view
crwl https://example.com -o markdown
# Then ask questions
crwl https://example.com -q "What are the main points?"
crwl https://example.com -q "Summarize the conclusions"
```
## Best Practices & Tips
1. **Configuration Management**:
- Keep common configurations in YAML files
- Use CLI parameters for quick overrides
- Store sensitive data (API tokens) in `~/.crawl4ai/global.yml`
2. **Performance Optimization**:
- Use `--bypass-cache` for fresh content
- Enable `scan_full_page` for infinite scroll pages
- Adjust `delay_before_return_html` for dynamic content
3. **Content Extraction**:
- Use CSS extraction for structured content
- Use LLM extraction for unstructured content
- Combine with filters for focused results
4. **Q&A Workflow**:
- View content first with `-o markdown`
- Ask specific questions
- Use broader context with appropriate selectors
## Recap
The Crawl4AI CLI provides:
- Flexible configuration via files and parameters
- Multiple extraction strategies (CSS, XPath, LLM)
- Content filtering and optimization
- Interactive Q&A capabilities
- Various output formats