Commit Message:

Enhance Crawl4AI with CLI and documentation updates
  - Implemented Command-Line Interface (CLI) in `crawl4ai/cli.py`
  - Added chunking strategies and their documentation in `llm.txt`

docs/llm.txt/8_content_selection.sm.md

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+# Crawl4AI Content Selection (LLM-Friendly Reference)
+
+> Minimal, code-oriented reference for selecting and filtering webpage content using Crawl4AI.
+
+## Quick Start
+
+```python
+from crawl4ai.async_configs import CrawlerRunConfig, AsyncWebCrawler
+
+async def run():
+    config = CrawlerRunConfig(css_selector=".main-article")
+    async with AsyncWebCrawler() as crawler:
+        result = await crawler.arun(url="https://example.com", config=config)
+        print(result.extracted_content)
+```
+
+## CSS Selectors
+
+- Use `css_selector="selector"` to target specific content.
+
+```python
+config = CrawlerRunConfig(css_selector="article h1, article .content")
+result = await crawler.arun(url="...", config=config)
+```
+
+## Content Filtering
+
+- `word_count_threshold`: int
+- `excluded_tags`: list of tags
+- `exclude_external_links`: bool
+- `exclude_social_media_links`: bool
+- `exclude_external_images`: bool
+
+```python
+config = CrawlerRunConfig(
+    word_count_threshold=10,
+    excluded_tags=["form","header","footer","nav"],
+    exclude_external_links=True,
+    exclude_social_media_links=True,
+    exclude_external_images=True
+)
+```
+
+## Iframe Content
+
+- `process_iframes`: bool
+- `remove_overlay_elements`: bool
+
+```python
+config = CrawlerRunConfig(
+    process_iframes=True,
+    remove_overlay_elements=True
+)
+```
+
+## LLM-Based Extraction
+
+- Use `LLMExtractionStrategy(provider="...")` with `schema=...` and `instruction="..."`
+
+```python
+from crawl4ai.extraction_strategy import LLMExtractionStrategy
+from pydantic import BaseModel
+
+class ArticleContent(BaseModel):
+    title: str
+    main_points: list[str]
+    conclusion: str
+
+strategy = LLMExtractionStrategy(
+    provider="ollama/nemotron",
+    schema=ArticleContent.schema(),
+    instruction="Extract title, points, conclusion"
+)
+
+config = CrawlerRunConfig(extraction_strategy=strategy)
+```
+
+## Pattern-Based Selection (JsonCssExtractionStrategy)
+
+```python
+from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
+
+schema = {
+    "name": "News Articles",
+    "baseSelector": "article.news-item",
+    "fields": [
+        {"name":"headline","selector":"h2","type":"text"},
+        {"name":"summary","selector":".summary","type":"text"},
+        {"name":"category","selector":".category","type":"text"},
+        {
+            "name":"metadata",
+            "type":"nested",
+            "fields":[
+                {"name":"author","selector":".author","type":"text"},
+                {"name":"date","selector":".date","type":"text"}
+            ]
+        }
+    ]
+}
+
+config = CrawlerRunConfig(extraction_strategy=JsonCssExtractionStrategy(schema))
+```
+
+## Combined Example
+
+```python
+from crawl4ai.async_configs import CrawlerRunConfig, AsyncWebCrawler
+from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
+
+article_schema = {
+    "name":"Article",
+    "baseSelector":"article.main",
+    "fields":[
+        {"name":"title","selector":"h1","type":"text"},
+        {"name":"content","selector":".content","type":"text"}
+    ]
+}
+
+config = CrawlerRunConfig(
+    extraction_strategy=JsonCssExtractionStrategy(article_schema),
+    word_count_threshold=10,
+    excluded_tags=["nav","footer"],
+    exclude_external_links=True
+)
+```
+
+## Optional
+
+- [async_webcrawler.py](https://github.com/unclecode/crawl4ai/blob/main/crawl4ai/async_webcrawler.py)
+- [async_crawler_strategy.py](https://github.com/unclecode/crawl4ai/blob/main/crawl4ai/async_crawler_strategy.py)