Update Documentation

docs/details/features.md

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+### 1. Basic Web Crawling
+```python
+async with AsyncWebCrawler() as crawler:
+    result = await crawler.arun(url="https://example.com")
+    print(result.markdown)  # Get clean markdown content
+    print(result.html)      # Get raw HTML
+    print(result.cleaned_html)  # Get cleaned HTML
+```
+
+### 2. Browser Control Options
+- Multiple Browser Support
+```python
+# Choose between different browser engines
+crawler = AsyncWebCrawler(browser_type="firefox")  # or "chromium", "webkit"
+crawler = AsyncWebCrawler(headless=False)  # For visible browser
+```
+
+- Proxy Configuration
+```python
+crawler = AsyncWebCrawler(proxy="http://proxy.example.com:8080")
+# Or with authentication
+crawler = AsyncWebCrawler(proxy_config={
+    "server": "http://proxy.example.com:8080",
+    "username": "user",
+    "password": "pass"
+})
+```
+
+### 3. Content Selection & Filtering
+- CSS Selector Support
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    css_selector=".main-content"  # Extract specific content
+)
+```
+
+- Content Filtering Options
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    word_count_threshold=10,  # Minimum words per block
+    excluded_tags=['form', 'header'],  # Tags to exclude
+    exclude_external_links=True,  # Remove external links
+    exclude_social_media_links=True,  # Remove social media links
+    exclude_external_images=True  # Remove external images
+)
+```
+
+### 4. Dynamic Content Handling
+- JavaScript Execution
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    js_code="window.scrollTo(0, document.body.scrollHeight)"  # Execute custom JS
+)
+```
+
+- Wait Conditions
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    wait_for="css:.my-element",  # Wait for element
+    wait_for="js:() => document.readyState === 'complete'"  # Wait for condition
+)
+```
+
+### 5. Anti-Bot Protection Handling
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    simulate_user=True,  # Simulate human behavior
+    override_navigator=True,  # Mask automation signals
+    magic=True  # Enable all anti-detection features
+)
+```
+
+### 6. Session Management
+```python
+session_id = "my_session"
+result1 = await crawler.arun(url="https://example.com/page1", session_id=session_id)
+result2 = await crawler.arun(url="https://example.com/page2", session_id=session_id)
+await crawler.crawler_strategy.kill_session(session_id)
+```
+
+### 7. Media Handling
+- Screenshot Capture
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    screenshot=True
+)
+base64_screenshot = result.screenshot
+```
+
+- Media Extraction
+```python
+result = await crawler.arun(url="https://example.com")
+print(result.media['images'])  # List of images
+print(result.media['videos'])  # List of videos
+print(result.media['audios'])  # List of audio files
+```
+
+### 8. Structured Data Extraction
+- CSS-based Extraction
+```python
+schema = {
+    "name": "News Articles",
+    "baseSelector": "article",
+    "fields": [
+        {"name": "title", "selector": "h1", "type": "text"},
+        {"name": "date", "selector": ".date", "type": "text"}
+    ]
+}
+extraction_strategy = JsonCssExtractionStrategy(schema)
+result = await crawler.arun(
+    url="https://example.com",
+    extraction_strategy=extraction_strategy
+)
+structured_data = json.loads(result.extracted_content)
+```
+
+- LLM-based Extraction (Multiple Providers)
+```python
+class NewsArticle(BaseModel):
+    title: str
+    summary: str
+
+strategy = LLMExtractionStrategy(
+    provider="ollama/nemotron",  # or "huggingface/...", "ollama/..."
+    api_token="your-token",
+    schema=NewsArticle.schema(),
+    instruction="Extract news article details..."
+)
+result = await crawler.arun(
+    url="https://example.com",
+    extraction_strategy=strategy
+)
+```
+
+### 9. Content Cleaning & Processing
+```python
+result = await crawler.arun(
+    url="https://example.com",
+    remove_overlay_elements=True,  # Remove popups/modals
+    process_iframes=True,  # Process iframe content
+)
+print(result.fit_markdown)  # Get most relevant content
+print(result.fit_html)     # Get cleaned HTML
+```