Release v0.7.6: The 0.7.6 Update

- Updated version to 0.7.6 - Added comprehensive demo and release notes - Updated all documentation - Update the veriosn in Dockerfile to 0.7.6
2025-10-22 13:46:54 +02:00
28 changed files with 649 additions and 2153 deletions
--- a/crawl4ai/async_crawler_strategy.py
+++ b/crawl4ai/async_crawler_strategy.py
@@ -1383,10 +1383,9 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        try:
            await self.adapter.evaluate(page,
                f"""
-                (async () => {{
+                (() => {{
                    try {{
-                        const removeOverlays = {remove_overlays_js};
-                        await removeOverlays();
+                        {remove_overlays_js}
                        return {{ success: true }};
                    }} catch (error) {{
                        return {{
--- a/crawl4ai/async_webcrawler.py
+++ b/crawl4ai/async_webcrawler.py
@@ -617,17 +617,7 @@ class AsyncWebCrawler:
                else config.chunking_strategy
            )
            sections = chunking.chunk(content)
-            # extracted_content = config.extraction_strategy.run(url, sections)
-
-            # Use async version if available for better parallelism
-            if hasattr(config.extraction_strategy, 'arun'):
-                extracted_content = await config.extraction_strategy.arun(url, sections)
-            else:
-                # Fallback to sync version run in thread pool to avoid blocking
-                extracted_content = await asyncio.to_thread(
-                    config.extraction_strategy.run, url, sections
-                )
-
+            extracted_content = config.extraction_strategy.run(url, sections)
            extracted_content = json.dumps(
                extracted_content, indent=4, default=str, ensure_ascii=False
            )
--- a/crawl4ai/browser_manager.py
+++ b/crawl4ai/browser_manager.py
@@ -369,9 +369,6 @@ class ManagedBrowser:
            ]
            if self.headless:
                flags.append("--headless=new")
-            # Add viewport flag if specified in config
-            if self.browser_config.viewport_height and self.browser_config.viewport_width:
-                flags.append(f"--window-size={self.browser_config.viewport_width},{self.browser_config.viewport_height}")
            # merge common launch flags
            flags.extend(self.build_browser_flags(self.browser_config))
        elif self.browser_type == "firefox":
--- a/crawl4ai/extraction_strategy.py
+++ b/crawl4ai/extraction_strategy.py
@@ -94,20 +94,6 @@ class ExtractionStrategy(ABC):
                extracted_content.extend(future.result())
        return extracted_content

-    async def arun(self, url: str, sections: List[str], *q, **kwargs) -> List[Dict[str, Any]]:
-        """
-        Async version: Process sections of text in parallel using asyncio.
-
-        Default implementation runs the sync version in a thread pool.
-        Subclasses can override this for true async processing.
-
-        :param url: The URL of the webpage.
-        :param sections: List of sections (strings) to process.
-        :return: A list of processed JSON blocks.
-        """
-        import asyncio
-        return await asyncio.to_thread(self.run, url, sections, *q, **kwargs)
-

 class NoExtractionStrategy(ExtractionStrategy):
    """
@@ -794,177 +780,6 @@ class LLMExtractionStrategy(ExtractionStrategy):

        return extracted_content

-    async def aextract(self, url: str, ix: int, html: str) -> List[Dict[str, Any]]:
-        """
-        Async version: Extract meaningful blocks or chunks from the given HTML using an LLM.
-
-        How it works:
-        1. Construct a prompt with variables.
-        2. Make an async request to the LLM using the prompt.
-        3. Parse the response and extract blocks or chunks.
-
-        Args:
-            url: The URL of the webpage.
-            ix: Index of the block.
-            html: The HTML content of the webpage.
-
-        Returns:
-            A list of extracted blocks or chunks.
-        """
-        from .utils import aperform_completion_with_backoff
-
-        if self.verbose:
-            print(f"[LOG] Call LLM for {url} - block index: {ix}")
-
-        variable_values = {
-            "URL": url,
-            "HTML": escape_json_string(sanitize_html(html)),
-        }
-
-        prompt_with_variables = PROMPT_EXTRACT_BLOCKS
-        if self.instruction:
-            variable_values["REQUEST"] = self.instruction
-            prompt_with_variables = PROMPT_EXTRACT_BLOCKS_WITH_INSTRUCTION
-
-        if self.extract_type == "schema" and self.schema:
-            variable_values["SCHEMA"] = json.dumps(self.schema, indent=2)
-            prompt_with_variables = PROMPT_EXTRACT_SCHEMA_WITH_INSTRUCTION
-
-        if self.extract_type == "schema" and not self.schema:
-            prompt_with_variables = PROMPT_EXTRACT_INFERRED_SCHEMA
-
-        for variable in variable_values:
-            prompt_with_variables = prompt_with_variables.replace(
-                "{" + variable + "}", variable_values[variable]
-            )
-
-        try:
-            response = await aperform_completion_with_backoff(
-                self.llm_config.provider,
-                prompt_with_variables,
-                self.llm_config.api_token,
-                base_url=self.llm_config.base_url,
-                json_response=self.force_json_response,
-                extra_args=self.extra_args,
-            )
-            # Track usage
-            usage = TokenUsage(
-                completion_tokens=response.usage.completion_tokens,
-                prompt_tokens=response.usage.prompt_tokens,
-                total_tokens=response.usage.total_tokens,
-                completion_tokens_details=response.usage.completion_tokens_details.__dict__
-                if response.usage.completion_tokens_details
-                else {},
-                prompt_tokens_details=response.usage.prompt_tokens_details.__dict__
-                if response.usage.prompt_tokens_details
-                else {},
-            )
-            self.usages.append(usage)
-
-            # Update totals
-            self.total_usage.completion_tokens += usage.completion_tokens
-            self.total_usage.prompt_tokens += usage.prompt_tokens
-            self.total_usage.total_tokens += usage.total_tokens
-
-            try:
-                content = response.choices[0].message.content
-                blocks = None
-
-                if self.force_json_response:
-                    blocks = json.loads(content)
-                    if isinstance(blocks, dict):
-                        if len(blocks) == 1 and isinstance(list(blocks.values())[0], list):
-                            blocks = list(blocks.values())[0]
-                        else:
-                            blocks = [blocks]
-                    elif isinstance(blocks, list):
-                        blocks = blocks
-                else:
-                    blocks = extract_xml_data(["blocks"], content)["blocks"]
-                    blocks = json.loads(blocks)
-
-                for block in blocks:
-                    block["error"] = False
-            except Exception:
-                parsed, unparsed = split_and_parse_json_objects(
-                    response.choices[0].message.content
-                )
-                blocks = parsed
-                if unparsed:
-                    blocks.append(
-                        {"index": 0, "error": True, "tags": ["error"], "content": unparsed}
-                    )
-
-            if self.verbose:
-                print(
-                    "[LOG] Extracted",
-                    len(blocks),
-                    "blocks from URL:",
-                    url,
-                    "block index:",
-                    ix,
-                )
-            return blocks
-        except Exception as e:
-            if self.verbose:
-                print(f"[LOG] Error in LLM extraction: {e}")
-            return [
-                {
-                    "index": ix,
-                    "error": True,
-                    "tags": ["error"],
-                    "content": str(e),
-                }
-            ]
-
-    async def arun(self, url: str, sections: List[str]) -> List[Dict[str, Any]]:
-        """
-        Async version: Process sections with true parallelism using asyncio.gather.
-
-        Args:
-            url: The URL of the webpage.
-            sections: List of sections (strings) to process.
-
-        Returns:
-            A list of extracted blocks or chunks.
-        """
-        import asyncio
-
-        merged_sections = self._merge(
-            sections,
-            self.chunk_token_threshold,
-            overlap=int(self.chunk_token_threshold * self.overlap_rate),
-        )
-
-        extracted_content = []
-
-        # Create tasks for all sections to run in parallel
-        tasks = [
-            self.aextract(url, ix, sanitize_input_encode(section))
-            for ix, section in enumerate(merged_sections)
-        ]
-
-        # Execute all tasks concurrently
-        results = await asyncio.gather(*tasks, return_exceptions=True)
-
-        # Process results
-        for result in results:
-            if isinstance(result, Exception):
-                if self.verbose:
-                    print(f"Error in async extraction: {result}")
-                extracted_content.append(
-                    {
-                        "index": 0,
-                        "error": True,
-                        "tags": ["error"],
-                        "content": str(result),
-                    }
-                )
-            else:
-                extracted_content.extend(result)
-
-        return extracted_content
-
    def show_usage(self) -> None:
        """Print a detailed token usage report showing total and per-request usage."""
        print("\n=== Token Usage Summary ===")
--- a/crawl4ai/utils.py
+++ b/crawl4ai/utils.py
@@ -1825,82 +1825,6 @@ def perform_completion_with_backoff(
            # ]


-async def aperform_completion_with_backoff(
-    provider,
-    prompt_with_variables,
-    api_token,
-    json_response=False,
-    base_url=None,
-    **kwargs,
-):
-    """
-    Async version: Perform an API completion request with exponential backoff.
-
-    How it works:
-    1. Sends an async completion request to the API.
-    2. Retries on rate-limit errors with exponential delays (async).
-    3. Returns the API response or an error after all retries.
-
-    Args:
-        provider (str): The name of the API provider.
-        prompt_with_variables (str): The input prompt for the completion request.
-        api_token (str): The API token for authentication.
-        json_response (bool): Whether to request a JSON response. Defaults to False.
-        base_url (Optional[str]): The base URL for the API. Defaults to None.
-        **kwargs: Additional arguments for the API request.
-
-    Returns:
-        dict: The API response or an error message after all retries.
-    """
-
-    from litellm import acompletion
-    from litellm.exceptions import RateLimitError
-    import asyncio
-
-    max_attempts = 3
-    base_delay = 2  # Base delay in seconds, you can adjust this based on your needs
-
-    extra_args = {"temperature": 0.01, "api_key": api_token, "base_url": base_url}
-    if json_response:
-        extra_args["response_format"] = {"type": "json_object"}
-
-    if kwargs.get("extra_args"):
-        extra_args.update(kwargs["extra_args"])
-
-    for attempt in range(max_attempts):
-        try:
-            response = await acompletion(
-                model=provider,
-                messages=[{"role": "user", "content": prompt_with_variables}],
-                **extra_args,
-            )
-            return response  # Return the successful response
-        except RateLimitError as e:
-            print("Rate limit error:", str(e))
-
-            if attempt == max_attempts - 1:
-                # Last attempt failed, raise the error.
-                raise
-
-            # Check if we have exhausted our max attempts
-            if attempt < max_attempts - 1:
-                # Calculate the delay and wait
-                delay = base_delay * (2**attempt)  # Exponential backoff formula
-                print(f"Waiting for {delay} seconds before retrying...")
-                await asyncio.sleep(delay)
-            else:
-                # Return an error response after exhausting all retries
-                return [
-                    {
-                        "index": 0,
-                        "tags": ["error"],
-                        "content": ["Rate limit error. Please try again later."],
-                    }
-                ]
-        except Exception as e:
-            raise e  # Raise any other exceptions immediately
-
-
 def extract_blocks(url, html, provider=DEFAULT_PROVIDER, api_token=None, base_url=None):
    """
    Extract content blocks from website HTML using an AI provider.
--- a/deploy/docker/README.md
+++ b/deploy/docker/README.md
@@ -785,54 +785,6 @@ curl http://localhost:11235/crawl/job/crawl_xyz

 The response includes `status` field: `"processing"`, `"completed"`, or `"failed"`.

-#### LLM Extraction Jobs with Webhooks
-
-The same webhook system works for LLM extraction jobs via `/llm/job`:
-
-```bash
-# Submit LLM extraction job with webhook
-curl -X POST http://localhost:11235/llm/job \
-  -H "Content-Type: application/json" \
-  -d '{
-    "url": "https://example.com/article",
-    "q": "Extract the article title, author, and main points",
-    "provider": "openai/gpt-4o-mini",
-    "webhook_config": {
-      "webhook_url": "https://myapp.com/webhooks/llm-complete",
-      "webhook_data_in_payload": true,
-      "webhook_headers": {
-        "X-Webhook-Secret": "your-secret-token"
-      }
-    }
-  }'
-
-# Response: {"task_id": "llm_1234567890"}
-```
-
-**Your webhook receives:**
-```json
-{
-  "task_id": "llm_1234567890",
-  "task_type": "llm_extraction",
-  "status": "completed",
-  "timestamp": "2025-10-22T12:30:00.000000+00:00",
-  "urls": ["https://example.com/article"],
-  "data": {
-    "extracted_content": {
-      "title": "Understanding Web Scraping",
-      "author": "John Doe",
-      "main_points": ["Point 1", "Point 2", "Point 3"]
-    }
-  }
-}
-```
-
-**Key Differences for LLM Jobs:**
- Task type is `"llm_extraction"` instead of `"crawl"`
- Extracted data is in `data.extracted_content`
- Single URL only (not an array)
- Supports schema-based extraction with `schema` parameter
-
 > 💡 **Pro tip**: See [WEBHOOK_EXAMPLES.md](./WEBHOOK_EXAMPLES.md) for detailed examples including TypeScript client code, Flask webhook handlers, and failure handling.

 ---
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -6,16 +6,15 @@ x-base-config: &base-config
    - "11235:11235"  # Gunicorn port
  env_file:
    - .llm.env       # API keys (create from .llm.env.example)
-  # Uncomment to set default environment variables (will overwrite .llm.env)
-  # environment:
-  #   - OPENAI_API_KEY=${OPENAI_API_KEY:-}
-  #   - DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY:-}
-  #   - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
-  #   - GROQ_API_KEY=${GROQ_API_KEY:-}
-  #   - TOGETHER_API_KEY=${TOGETHER_API_KEY:-}
-  #   - MISTRAL_API_KEY=${MISTRAL_API_KEY:-}
-  #   - GEMINI_API_KEY=${GEMINI_API_KEY:-}
-  #   - LLM_PROVIDER=${LLM_PROVIDER:-}  # Optional: Override default provider (e.g., "anthropic/claude-3-opus")
+  environment:
+    - OPENAI_API_KEY=${OPENAI_API_KEY:-}
+    - DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY:-}
+    - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
+    - GROQ_API_KEY=${GROQ_API_KEY:-}
+    - TOGETHER_API_KEY=${TOGETHER_API_KEY:-}
+    - MISTRAL_API_KEY=${MISTRAL_API_KEY:-}
+    - GEMINI_API_TOKEN=${GEMINI_API_TOKEN:-}
+    - LLM_PROVIDER=${LLM_PROVIDER:-}  # Optional: Override default provider (e.g., "anthropic/claude-3-opus")
  volumes:
    - /dev/shm:/dev/shm  # Chromium performance
  deploy:
--- a/docs/examples/c4a_script/tutorial/README.md
+++ b/docs/examples/c4a_script/tutorial/README.md
@@ -18,7 +18,7 @@ A comprehensive web-based tutorial for learning and experimenting with C4A-Scrip

 2. **Install Dependencies**
   ```bash
-   pip install -r requirements.txt
+   pip install flask
   ```

 3. **Launch the Server**
@@ -28,7 +28,7 @@ A comprehensive web-based tutorial for learning and experimenting with C4A-Scrip

 4. **Open in Browser**
   ```
-   http://localhost:8000
+   http://localhost:8080
   ```

 **🌐 Try Online**: [Live Demo](https://docs.crawl4ai.com/c4a-script/demo)
@@ -325,7 +325,7 @@ Powers the recording functionality:
 ### Configuration
 ```python
 # server.py configuration
-PORT = 8000
+PORT = 8080
 DEBUG = True
 THREADED = True
 ```
@@ -343,9 +343,9 @@ THREADED = True
 **Port Already in Use**
 ```bash
 # Kill existing process
-lsof -ti:8000 | xargs kill -9
+lsof -ti:8080 | xargs kill -9
 # Or use different port
-python server.py --port 8001
+python server.py --port 8081
 ```

 **Blockly Not Loading**
--- a/docs/examples/c4a_script/tutorial/server.py
+++ b/docs/examples/c4a_script/tutorial/server.py
@@ -216,7 +216,7 @@ def get_examples():
            'name': 'Handle Cookie Banner',
            'description': 'Accept cookies and close newsletter popup',
            'script': '''# Handle cookie banner and newsletter
-GO http://127.0.0.1:8000/playground/
+GO http://127.0.0.1:8080/playground/
 WAIT `body` 2
 IF (EXISTS `.cookie-banner`) THEN CLICK `.accept`
 IF (EXISTS `.newsletter-popup`) THEN CLICK `.close`'''
--- a/docs/examples/docker_hooks_examples.py
+++ b/docs/examples/docker_hooks_examples.py
--- a/docs/md_v2/advanced/identity-based-crawling.md
+++ b/docs/md_v2/advanced/identity-based-crawling.md
@@ -82,42 +82,6 @@ If you installed Crawl4AI (which installs Playwright under the hood), you alread

 ---

-### Creating a Profile Using the Crawl4AI CLI (Easiest)
-
-If you prefer a guided, interactive setup, use the built-in CLI to create and manage persistent browser profiles.
-
-1.⠀Launch the profile manager:
-   ```bash
-   crwl profiles
-   ```
-
-2.⠀Choose "Create new profile" and enter a profile name. A Chromium window opens so you can log in to sites and configure settings. When finished, return to the terminal and press `q` to save the profile.
-
-3.⠀Profiles are saved under `~/.crawl4ai/profiles/<profile_name>` (for example: `/home/<you>/.crawl4ai/profiles/test_profile_1`) along with a `storage_state.json` for cookies and session data.
-
-4.⠀Optionally, choose "List profiles" in the CLI to view available profiles and their paths.
-
-5.⠀Use the saved path with `BrowserConfig.user_data_dir`:
-   ```python
-   from crawl4ai import AsyncWebCrawler, BrowserConfig
-
-   profile_path = "/home/<you>/.crawl4ai/profiles/test_profile_1"
-
-   browser_config = BrowserConfig(
-       headless=True,
-       use_managed_browser=True,
-       user_data_dir=profile_path,
-       browser_type="chromium",
-   )
-
-   async with AsyncWebCrawler(config=browser_config) as crawler:
-       result = await crawler.arun(url="https://example.com/private")
-   ```
-
-The CLI also supports listing and deleting profiles, and even testing a crawl directly from the menu.
-
---
-
 ## 3. Using Managed Browsers in Crawl4AI

 Once you have a data directory with your session data, pass it to **`BrowserConfig`**:
--- a/docs/md_v2/apps/c4a-script/README.md
+++ b/docs/md_v2/apps/c4a-script/README.md
@@ -18,7 +18,7 @@ A comprehensive web-based tutorial for learning and experimenting with C4A-Scrip

 2. **Install Dependencies**
   ```bash
-   pip install -r requirements.txt
+   pip install flask
   ```

 3. **Launch the Server**
@@ -28,7 +28,7 @@ A comprehensive web-based tutorial for learning and experimenting with C4A-Scrip

 4. **Open in Browser**
   ```
-   http://localhost:8000
+   http://localhost:8080
   ```

 **🌐 Try Online**: [Live Demo](https://docs.crawl4ai.com/c4a-script/demo)
@@ -325,7 +325,7 @@ Powers the recording functionality:
 ### Configuration
 ```python
 # server.py configuration
-PORT = 8000
+PORT = 8080
 DEBUG = True
 THREADED = True
 ```
@@ -343,9 +343,9 @@ THREADED = True
 **Port Already in Use**
 ```bash
 # Kill existing process
-lsof -ti:8000 | xargs kill -9
+lsof -ti:8080 | xargs kill -9
 # Or use different port
-python server.py --port 8001
+python server.py --port 8081
 ```

 **Blockly Not Loading**
--- a/docs/md_v2/apps/c4a-script/server.py
+++ b/docs/md_v2/apps/c4a-script/server.py
@@ -216,7 +216,7 @@ def get_examples():
            'name': 'Handle Cookie Banner',
            'description': 'Accept cookies and close newsletter popup',
            'script': '''# Handle cookie banner and newsletter
-GO http://127.0.0.1:8000/playground/
+GO http://127.0.0.1:8080/playground/
 WAIT `body` 2
 IF (EXISTS `.cookie-banner`) THEN CLICK `.accept`
 IF (EXISTS `.newsletter-popup`) THEN CLICK `.close`'''
@@ -283,7 +283,7 @@ WAIT `.success-message` 5'''
    return jsonify(examples)

 if __name__ == '__main__':
-    port = int(os.environ.get('PORT', 8000))
+    port = int(os.environ.get('PORT', 8080))
    print(f"""
 ╔══════════════════════════════════════════════════════════╗
 ║          C4A-Script Interactive Tutorial Server          ║
--- a/docs/md_v2/core/c4a-script.md
+++ b/docs/md_v2/core/c4a-script.md
@@ -69,12 +69,12 @@ The tutorial includes a Flask-based web interface with:
 cd docs/examples/c4a_script/tutorial/

 # Install dependencies
-pip install -r requirements.txt
+pip install flask

 # Launch the tutorial server
-python server.py
+python app.py

-# Open http://localhost:8000 in your browser
+# Open http://localhost:5000 in your browser
 ```

 ## Core Concepts
@@ -111,8 +111,8 @@ CLICK `.submit-btn`
 # By attribute
 CLICK `button[type="submit"]`

-# By accessible attributes
-CLICK `button[aria-label="Search"][title="Search"]`
+# By text content
+CLICK `button:contains("Sign In")`

 # Complex selectors
 CLICK `.form-container input[name="email"]`
--- a/docs/md_v2/core/docker-deployment.md
+++ b/docs/md_v2/core/docker-deployment.md
@@ -27,14 +27,6 @@
  - [Hook Response Information](#hook-response-information)
  - [Error Handling](#error-handling)
  - [Hooks Utility: Function-Based Approach (Python)](#hooks-utility-function-based-approach-python)
- [Job Queue & Webhook API](#job-queue-webhook-api)
-  - [Why Use the Job Queue API?](#why-use-the-job-queue-api)
-  - [Available Endpoints](#available-endpoints)
-  - [Webhook Configuration](#webhook-configuration)
-  - [Usage Examples](#usage-examples)
-  - [Webhook Best Practices](#webhook-best-practices)
-  - [Use Cases](#use-cases)
-  - [Troubleshooting](#troubleshooting)
 - [Dockerfile Parameters](#dockerfile-parameters)
 - [Using the API](#using-the-api)
  - [Playground Interface](#playground-interface)
@@ -1118,464 +1110,6 @@ if __name__ == "__main__":

 ---

-## Job Queue & Webhook API
-
-The Docker deployment includes a powerful asynchronous job queue system with webhook support for both crawling and LLM extraction tasks. Instead of waiting for long-running operations to complete, submit jobs and receive real-time notifications via webhooks when they finish.
-
-### Why Use the Job Queue API?
-
-**Traditional Synchronous API (`/crawl`):**
- Client waits for entire crawl to complete
- Timeout issues with long-running crawls
- Resource blocking during execution
- Constant polling required for status updates
-
-**Asynchronous Job Queue API (`/crawl/job`, `/llm/job`):**
- ✅ Submit job and continue immediately
- ✅ No timeout concerns for long operations
- ✅ Real-time webhook notifications on completion
- ✅ Better resource utilization
- ✅ Perfect for batch processing
- ✅ Ideal for microservice architectures
-
-### Available Endpoints
-
-#### 1. Crawl Job Endpoint
-
-```
-POST /crawl/job
-```
-
-Submit an asynchronous crawl job with optional webhook notification.
-
-**Request Body:**
-```json
-{
-  "urls": ["https://example.com"],
-  "cache_mode": "bypass",
-  "extraction_strategy": {
-    "type": "JsonCssExtractionStrategy",
-    "schema": {
-      "title": "h1",
-      "content": ".article-body"
-    }
-  },
-  "webhook_config": {
-    "webhook_url": "https://your-app.com/webhook/crawl-complete",
-    "webhook_data_in_payload": true,
-    "webhook_headers": {
-      "X-Webhook-Secret": "your-secret-token",
-      "X-Custom-Header": "value"
-    }
-  }
-}
-```
-
-**Response:**
-```json
-{
-  "task_id": "crawl_1698765432",
-  "message": "Crawl job submitted"
-}
-```
-
-#### 2. LLM Extraction Job Endpoint
-
-```
-POST /llm/job
-```
-
-Submit an asynchronous LLM extraction job with optional webhook notification.
-
-**Request Body:**
-```json
-{
-  "url": "https://example.com/article",
-  "q": "Extract the article title, author, publication date, and main points",
-  "provider": "openai/gpt-4o-mini",
-  "schema": "{\"title\": \"string\", \"author\": \"string\", \"date\": \"string\", \"points\": [\"string\"]}",
-  "cache": false,
-  "webhook_config": {
-    "webhook_url": "https://your-app.com/webhook/llm-complete",
-    "webhook_data_in_payload": true,
-    "webhook_headers": {
-      "X-Webhook-Secret": "your-secret-token"
-    }
-  }
-}
-```
-
-**Response:**
-```json
-{
-  "task_id": "llm_1698765432",
-  "message": "LLM job submitted"
-}
-```
-
-#### 3. Job Status Endpoint
-
-```
-GET /job/{task_id}
-```
-
-Check the status and retrieve results of a submitted job.
-
-**Response (In Progress):**
-```json
-{
-  "task_id": "crawl_1698765432",
-  "status": "processing",
-  "message": "Job is being processed"
-}
-```
-
-**Response (Completed):**
-```json
-{
-  "task_id": "crawl_1698765432",
-  "status": "completed",
-  "result": {
-    "markdown": "# Page Title\n\nContent...",
-    "extracted_content": {...},
-    "links": {...}
-  }
-}
-```
-
-### Webhook Configuration
-
-Webhooks provide real-time notifications when your jobs complete, eliminating the need for constant polling.
-
-#### Webhook Config Parameters
-
-| Parameter | Type | Required | Description |
-|-----------|------|----------|-------------|
-| `webhook_url` | string | Yes | Your HTTP(S) endpoint to receive notifications |
-| `webhook_data_in_payload` | boolean | No | Include full result data in webhook payload (default: false) |
-| `webhook_headers` | object | No | Custom headers for authentication/identification |
-
-#### Webhook Payload Format
-
-**Success Notification (Crawl Job):**
-```json
-{
-  "task_id": "crawl_1698765432",
-  "task_type": "crawl",
-  "status": "completed",
-  "timestamp": "2025-10-22T12:30:00.000000+00:00",
-  "urls": ["https://example.com"],
-  "data": {
-    "markdown": "# Page content...",
-    "extracted_content": {...},
-    "links": {...}
-  }
-}
-```
-
-**Success Notification (LLM Job):**
-```json
-{
-  "task_id": "llm_1698765432",
-  "task_type": "llm_extraction",
-  "status": "completed",
-  "timestamp": "2025-10-22T12:30:00.000000+00:00",
-  "urls": ["https://example.com/article"],
-  "data": {
-    "extracted_content": {
-      "title": "Understanding Web Scraping",
-      "author": "John Doe",
-      "date": "2025-10-22",
-      "points": ["Point 1", "Point 2"]
-    }
-  }
-}
-```
-
-**Failure Notification:**
-```json
-{
-  "task_id": "crawl_1698765432",
-  "task_type": "crawl",
-  "status": "failed",
-  "timestamp": "2025-10-22T12:30:00.000000+00:00",
-  "urls": ["https://example.com"],
-  "error": "Connection timeout after 30 seconds"
-}
-```
-
-#### Webhook Delivery & Retry
-
- **Delivery Method:** HTTP POST to your `webhook_url`
- **Content-Type:** `application/json`
- **Retry Policy:** Exponential backoff with 5 attempts
-  - Attempt 1: Immediate
-  - Attempt 2: 1 second delay
-  - Attempt 3: 2 seconds delay
-  - Attempt 4: 4 seconds delay
-  - Attempt 5: 8 seconds delay
- **Success Status Codes:** 200-299
- **Custom Headers:** Your `webhook_headers` are included in every request
-
-### Usage Examples
-
-#### Example 1: Python with Webhook Handler (Flask)
-
-```python
-from flask import Flask, request, jsonify
-import requests
-
-app = Flask(__name__)
-
-# Webhook handler
-@app.route('/webhook/crawl-complete', methods=['POST'])
-def handle_crawl_webhook():
-    payload = request.json
-
-    if payload['status'] == 'completed':
-        print(f"✅ Job {payload['task_id']} completed!")
-        print(f"Task type: {payload['task_type']}")
-
-        # Access the crawl results
-        if 'data' in payload:
-            markdown = payload['data'].get('markdown', '')
-            extracted = payload['data'].get('extracted_content', {})
-            print(f"Extracted {len(markdown)} characters")
-            print(f"Structured data: {extracted}")
-    else:
-        print(f"❌ Job {payload['task_id']} failed: {payload.get('error')}")
-
-    return jsonify({"status": "received"}), 200
-
-# Submit a crawl job with webhook
-def submit_crawl_job():
-    response = requests.post(
-        "http://localhost:11235/crawl/job",
-        json={
-            "urls": ["https://example.com"],
-            "extraction_strategy": {
-                "type": "JsonCssExtractionStrategy",
-                "schema": {
-                    "name": "Example Schema",
-                    "baseSelector": "body",
-                    "fields": [
-                        {"name": "title", "selector": "h1", "type": "text"},
-                        {"name": "description", "selector": "meta[name='description']", "type": "attribute", "attribute": "content"}
-                    ]
-                }
-            },
-            "webhook_config": {
-                "webhook_url": "https://your-app.com/webhook/crawl-complete",
-                "webhook_data_in_payload": True,
-                "webhook_headers": {
-                    "X-Webhook-Secret": "your-secret-token"
-                }
-            }
-        }
-    )
-
-    task_id = response.json()['task_id']
-    print(f"Job submitted: {task_id}")
-    return task_id
-
-if __name__ == '__main__':
-    app.run(port=5000)
-```
-
-#### Example 2: LLM Extraction with Webhooks
-
-```python
-import requests
-
-def submit_llm_job_with_webhook():
-    response = requests.post(
-        "http://localhost:11235/llm/job",
-        json={
-            "url": "https://example.com/article",
-            "q": "Extract the article title, author, and main points",
-            "provider": "openai/gpt-4o-mini",
-            "webhook_config": {
-                "webhook_url": "https://your-app.com/webhook/llm-complete",
-                "webhook_data_in_payload": True,
-                "webhook_headers": {
-                    "X-Webhook-Secret": "your-secret-token"
-                }
-            }
-        }
-    )
-
-    task_id = response.json()['task_id']
-    print(f"LLM job submitted: {task_id}")
-    return task_id
-
-# Webhook handler for LLM jobs
-@app.route('/webhook/llm-complete', methods=['POST'])
-def handle_llm_webhook():
-    payload = request.json
-
-    if payload['status'] == 'completed':
-        extracted = payload['data']['extracted_content']
-        print(f"✅ LLM extraction completed!")
-        print(f"Results: {extracted}")
-    else:
-        print(f"❌ LLM extraction failed: {payload.get('error')}")
-
-    return jsonify({"status": "received"}), 200
-```
-
-#### Example 3: Without Webhooks (Polling)
-
-If you don't use webhooks, you can poll for results:
-
-```python
-import requests
-import time
-
-# Submit job
-response = requests.post(
-    "http://localhost:11235/crawl/job",
-    json={"urls": ["https://example.com"]}
-)
-task_id = response.json()['task_id']
-
-# Poll for results
-while True:
-    result = requests.get(f"http://localhost:11235/job/{task_id}")
-    data = result.json()
-
-    if data['status'] == 'completed':
-        print("Job completed!")
-        print(data['result'])
-        break
-    elif data['status'] == 'failed':
-        print(f"Job failed: {data.get('error')}")
-        break
-
-    print("Still processing...")
-    time.sleep(2)
-```
-
-#### Example 4: Global Webhook Configuration
-
-Set a default webhook URL in your `config.yml` to avoid repeating it in every request:
-
-```yaml
-# config.yml
-api:
-  crawler:
-    # ... other settings ...
-    webhook:
-      default_url: "https://your-app.com/webhook/default"
-      default_headers:
-        X-Webhook-Secret: "your-secret-token"
-```
-
-Then submit jobs without webhook config:
-
-```python
-# Uses the global webhook configuration
-response = requests.post(
-    "http://localhost:11235/crawl/job",
-    json={"urls": ["https://example.com"]}
-)
-```
-
-### Webhook Best Practices
-
-1. **Authentication:** Always use custom headers for webhook authentication
-   ```json
-   "webhook_headers": {
-     "X-Webhook-Secret": "your-secret-token"
-   }
-   ```
-
-2. **Idempotency:** Design your webhook handler to be idempotent (safe to receive duplicate notifications)
-
-3. **Fast Response:** Return HTTP 200 quickly; process data asynchronously if needed
-   ```python
-   @app.route('/webhook', methods=['POST'])
-   def webhook():
-       payload = request.json
-       # Queue for background processing
-       queue.enqueue(process_webhook, payload)
-       return jsonify({"status": "received"}), 200
-   ```
-
-4. **Error Handling:** Handle both success and failure notifications
-   ```python
-   if payload['status'] == 'completed':
-       # Process success
-   elif payload['status'] == 'failed':
-       # Log error, retry, or alert
-   ```
-
-5. **Validation:** Verify webhook authenticity using custom headers
-   ```python
-   secret = request.headers.get('X-Webhook-Secret')
-   if secret != os.environ['EXPECTED_SECRET']:
-       return jsonify({"error": "Unauthorized"}), 401
-   ```
-
-6. **Logging:** Log webhook deliveries for debugging
-   ```python
-   logger.info(f"Webhook received: {payload['task_id']} - {payload['status']}")
-   ```
-
-### Use Cases
-
-**1. Batch Processing**
-Submit hundreds of URLs and get notified as each completes:
-```python
-urls = ["https://site1.com", "https://site2.com", ...]
-for url in urls:
-    submit_crawl_job(url, webhook_url="https://app.com/webhook")
-```
-
-**2. Microservice Integration**
-Integrate with event-driven architectures:
-```python
-# Service A submits job
-task_id = submit_crawl_job(url)
-
-# Service B receives webhook and triggers next step
-@app.route('/webhook')
-def webhook():
-    process_result(request.json)
-    trigger_next_service()
-    return "OK", 200
-```
-
-**3. Long-Running Extractions**
-Handle complex LLM extractions without timeouts:
-```python
-submit_llm_job(
-    url="https://long-article.com",
-    q="Comprehensive summary with key points and analysis",
-    webhook_url="https://app.com/webhook/llm"
-)
-```
-
-### Troubleshooting
-
-**Webhook not receiving notifications?**
- Check your webhook URL is publicly accessible
- Verify firewall/security group settings
- Use webhook testing tools like webhook.site for debugging
- Check server logs for delivery attempts
- Ensure your handler returns 200-299 status code
-
-**Job stuck in processing?**
- Check Redis connection: `docker logs <container_name> | grep redis`
- Verify worker processes: `docker exec <container_name> ps aux | grep worker`
- Check server logs: `docker logs <container_name>`
-
-**Need to cancel a job?**
-Jobs are processed asynchronously. If you need to cancel:
- Delete the task from Redis (requires Redis CLI access)
- Or implement a cancellation endpoint in your webhook handler
-
---
-
 ## Dockerfile Parameters

 You can customize the image build process using build arguments (`--build-arg`). These are typically used via `docker buildx build` or within the `docker-compose.yml` file.
--- a/docs/md_v2/extraction/llm-strategies.md
+++ b/docs/md_v2/extraction/llm-strategies.md
@@ -20,10 +20,10 @@ In some cases, you need to extract **complex or unstructured** information from

 ## 2. Provider-Agnostic via LiteLLM

-You can use LLMConfig, to quickly configure multiple variations of LLMs and experiment with them to find the optimal one for your use case. You can read more about LLMConfig [here](/api/parameters).
+You can use LlmConfig, to quickly configure multiple variations of LLMs and experiment with them to find the optimal one for your use case. You can read more about LlmConfig [here](/api/parameters).

 ```python
-llm_config = LLMConfig(provider="openai/gpt-4o-mini", api_token=os.getenv("OPENAI_API_KEY"))
+llmConfig = LlmConfig(provider="openai/gpt-4o-mini", api_token=os.getenv("OPENAI_API_KEY"))
 ```

 Crawl4AI uses a “provider string” (e.g., `"openai/gpt-4o"`, `"ollama/llama2.0"`, `"aws/titan"`) to identify your LLM. **Any** model that LiteLLM supports is fair game. You just provide:
@@ -58,7 +58,7 @@ For structured data, `"schema"` is recommended. You provide `schema=YourPydantic

 Below is an overview of important LLM extraction parameters. All are typically set inside `LLMExtractionStrategy(...)`. You then put that strategy in your `CrawlerRunConfig(..., extraction_strategy=...)`.

-1. **`llm_config`** (LLMConfig): e.g., `"openai/gpt-4"`, `"ollama/llama2"`.
+1. **`llmConfig`** (LlmConfig): e.g., `"openai/gpt-4"`, `"ollama/llama2"`.    
 2. **`schema`** (dict): A JSON schema describing the fields you want. Usually generated by `YourModel.model_json_schema()`.  
 3. **`extraction_type`** (str): `"schema"` or `"block"`.  
 4. **`instruction`** (str): Prompt text telling the LLM what you want extracted. E.g., “Extract these fields as a JSON array.”  
@@ -112,7 +112,7 @@ async def main():
    # 1. Define the LLM extraction strategy
    llm_strategy = LLMExtractionStrategy(
        llm_config = LLMConfig(provider="openai/gpt-4o-mini", api_token=os.getenv('OPENAI_API_KEY')),
-        schema=Product.model_json_schema(), # Or use model_json_schema()
+        schema=Product.schema_json(), # Or use model_json_schema()
        extraction_type="schema",
        instruction="Extract all product objects with 'name' and 'price' from the content.",
        chunk_token_threshold=1000,
@@ -238,7 +238,7 @@ class KnowledgeGraph(BaseModel):
 async def main():
    # LLM extraction strategy
    llm_strat = LLMExtractionStrategy(
-        llm_config = LLMConfig(provider="openai/gpt-4", api_token=os.getenv('OPENAI_API_KEY')),
+        llmConfig = LLMConfig(provider="openai/gpt-4", api_token=os.getenv('OPENAI_API_KEY')),
        schema=KnowledgeGraph.model_json_schema(),
        extraction_type="schema",
        instruction="Extract entities and relationships from the content. Return valid JSON.",
--- a/docs/md_v2/index.md
+++ b/docs/md_v2/index.md
@@ -57,7 +57,7 @@

 Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for large language models, AI agents, and data pipelines. Fully open source, flexible, and built for real-time performance, **Crawl4AI** empowers developers with unmatched speed, precision, and deployment ease.

-> Enjoy using Crawl4AI? Consider **[becoming a sponsor](https://github.com/sponsors/unclecode)** to support ongoing development and community growth!
+> **Note**: If you're looking for the old documentation, you can access it [here](https://old.docs.crawl4ai.com).

 ## 🆕 AI Assistant Skill Now Available!

--- a/docs/md_v2/marketplace/admin/admin.js
+++ b/docs/md_v2/marketplace/admin/admin.js
@@ -529,19 +529,8 @@ class AdminDashboard {
                    </label>
                </div>
                <div class="form-group full-width">
-                    <label>Long Description (Markdown - Overview tab)</label>
-                    <textarea id="form-long-description" rows="10" placeholder="Enter detailed description with markdown formatting...">${app?.long_description || ''}</textarea>
-                    <small>Markdown support: **bold**, *italic*, [links](url), # headers, code blocks, lists</small>
-                </div>
-                <div class="form-group full-width">
-                    <label>Integration Guide (Markdown - Integration tab)</label>
-                    <textarea id="form-integration" rows="20" placeholder="Enter integration guide with installation, examples, and code snippets using markdown...">${app?.integration_guide || ''}</textarea>
-                    <small>Single markdown field with installation, examples, and complete guide. Code blocks get auto copy buttons.</small>
-                </div>
-                <div class="form-group full-width">
-                    <label>Documentation (Markdown - Documentation tab)</label>
-                    <textarea id="form-documentation" rows="20" placeholder="Enter documentation with API reference, examples, and best practices using markdown...">${app?.documentation || ''}</textarea>
-                    <small>Full documentation with API reference, examples, best practices, etc.</small>
+                    <label>Integration Guide</label>
+                    <textarea id="form-integration" rows="10">${app?.integration_guide || ''}</textarea>
                </div>
            </div>
        `;
@@ -723,9 +712,7 @@ class AdminDashboard {
            data.contact_email = document.getElementById('form-email').value;
            data.featured = document.getElementById('form-featured').checked ? 1 : 0;
            data.sponsored = document.getElementById('form-sponsored').checked ? 1 : 0;
-            data.long_description = document.getElementById('form-long-description').value;
            data.integration_guide = document.getElementById('form-integration').value;
-            data.documentation = document.getElementById('form-documentation').value;
        } else if (type === 'articles') {
            data.title = document.getElementById('form-title').value;
            data.slug = this.generateSlug(data.title);
--- a/docs/md_v2/marketplace/app-detail.css
+++ b/docs/md_v2/marketplace/app-detail.css
@@ -278,12 +278,12 @@
 }

 .tab-content {
-    display: none !important;
+    display: none;
    padding: 2rem;
 }

 .tab-content.active {
-    display: block !important;
+    display: block;
 }

 /* Overview Layout */
@@ -510,31 +510,6 @@
    line-height: 1.5;
 }

-/* Markdown rendered code blocks */
-.integration-content pre,
-.docs-content pre {
-    background: var(--bg-dark);
-    border: 1px solid var(--border-color);
-    margin: 1rem 0;
-    padding: 1rem;
-    padding-top: 2.5rem; /* Space for copy button */
-    overflow-x: auto;
-    position: relative;
-    max-height: none; /* Remove any height restrictions */
-    height: auto; /* Allow content to expand */
-}
-
-.integration-content pre code,
-.docs-content pre code {
-    background: transparent;
-    padding: 0;
-    color: var(--text-secondary);
-    font-size: 0.875rem;
-    line-height: 1.5;
-    white-space: pre; /* Preserve whitespace and line breaks */
-    display: block;
-}
-
 /* Feature Grid */
 .feature-grid {
    display: grid;
--- a/docs/md_v2/marketplace/app-detail.html
+++ b/docs/md_v2/marketplace/app-detail.html
@@ -73,14 +73,27 @@
                <div class="tabs">
                    <button class="tab-btn active" data-tab="overview">Overview</button>
                    <button class="tab-btn" data-tab="integration">Integration</button>
-                    <!-- <button class="tab-btn" data-tab="docs">Documentation</button>
-                    <button class="tab-btn" data-tab="support">Support</button> -->
+                    <button class="tab-btn" data-tab="docs">Documentation</button>
+                    <button class="tab-btn" data-tab="support">Support</button>
                </div>

                <section id="overview-tab" class="tab-content active">
                    <div class="overview-columns">
                        <div class="overview-main">
+                            <h2>Overview</h2>
                            <div id="app-overview">Overview content goes here.</div>
+
+                            <h3>Key Features</h3>
+                            <ul id="app-features" class="features-list">
+                                <li>Feature 1</li>
+                                <li>Feature 2</li>
+                                <li>Feature 3</li>
+                            </ul>
+
+                            <h3>Use Cases</h3>
+                            <div id="app-use-cases" class="use-cases">
+                                <p>Describe how this app can help your workflow.</p>
+                            </div>
                        </div>

                        <aside class="sidebar">
@@ -129,16 +142,37 @@
                </section>

                <section id="integration-tab" class="tab-content">
-                    <div class="integration-content" id="app-integration">
+                    <div class="integration-content">
+                        <h2>Integration Guide</h2>
+
+                        <h3>Installation</h3>
+                        <div class="code-block">
+                            <pre><code id="install-code"># Installation instructions will appear here</code></pre>
+                        </div>
+
+                        <h3>Basic Usage</h3>
+                        <div class="code-block">
+                            <pre><code id="usage-code"># Usage example will appear here</code></pre>
+                        </div>
+
+                        <h3>Complete Integration Example</h3>
+                        <div class="code-block">
+                            <button class="copy-btn" id="copy-integration">Copy</button>
+                            <pre><code id="integration-code"># Complete integration guide will appear here</code></pre>
+                        </div>
                    </div>
                </section>

-                <!-- <section id="docs-tab" class="tab-content">
-                    <div class="docs-content" id="app-docs">
+                <section id="docs-tab" class="tab-content">
+                    <div class="docs-content">
+                        <h2>Documentation</h2>
+                        <div id="app-docs" class="doc-sections">
+                            <p>Documentation coming soon.</p>
+                        </div>
                    </div>
-                </section> -->
+                </section>

-                <!-- <section id="support-tab" class="tab-content">
+                <section id="support-tab" class="tab-content">
                    <div class="docs-content">
                        <h2>Support</h2>
                        <div class="support-grid">
@@ -156,7 +190,7 @@
                            </div>
                        </div>
                    </div>
-                </section> -->
+                </section>
            </div>

        </main>
--- a/docs/md_v2/marketplace/app-detail.js
+++ b/docs/md_v2/marketplace/app-detail.js
@@ -112,7 +112,7 @@ class AppDetailPage {
        }

        // Contact
-        document.getElementById('app-contact') && (document.getElementById('app-contact').textContent = this.appData.contact_email || 'Not available');
+        document.getElementById('app-contact').textContent = this.appData.contact_email || 'Not available';

        // Sidebar info
        document.getElementById('sidebar-downloads').textContent = this.formatNumber(this.appData.downloads || 0);
@@ -123,134 +123,146 @@ class AppDetailPage {
        document.getElementById('sidebar-pricing').textContent = this.appData.pricing || 'Free';
        document.getElementById('sidebar-contact').textContent = this.appData.contact_email || 'contact@example.com';

-        // Render tab contents from database fields
-        this.renderTabContents();
+        // Integration guide
+        this.renderIntegrationGuide();
    }

-    renderTabContents() {
-        // Overview tab - use long_description from database
-        const overviewDiv = document.getElementById('app-overview');
-        if (overviewDiv) {
-            if (this.appData.long_description) {
-                overviewDiv.innerHTML = this.renderMarkdown(this.appData.long_description);
-            } else {
-                overviewDiv.innerHTML = `<p>${this.appData.description || 'No overview available.'}</p>`;
+    renderIntegrationGuide() {
+        // Installation code
+        const installCode = document.getElementById('install-code');
+        if (installCode) {
+            if (this.appData.type === 'Open Source' && this.appData.github_url) {
+                installCode.textContent = `# Clone from GitHub
+git clone ${this.appData.github_url}
+
+# Install dependencies
+pip install -r requirements.txt`;
+            } else if (this.appData.name.toLowerCase().includes('api')) {
+                installCode.textContent = `# Install via pip
+pip install ${this.appData.slug}
+
+# Or install from source
+pip install git+${this.appData.github_url || 'https://github.com/example/repo'}`;
            }
        }

-        // Integration tab - use integration_guide field from database
-        const integrationDiv = document.getElementById('app-integration');
-        if (integrationDiv) {
-            if (this.appData.integration_guide) {
-                integrationDiv.innerHTML = this.renderMarkdown(this.appData.integration_guide);
-                // Add copy buttons to all code blocks
-                this.addCopyButtonsToCodeBlocks(integrationDiv);
-            } else {
-                integrationDiv.innerHTML = '<p>Integration guide not yet available. Please check the official website for details.</p>';
+        // Usage code - customize based on category
+        const usageCode = document.getElementById('usage-code');
+        if (usageCode) {
+            if (this.appData.category === 'Browser Automation') {
+                usageCode.textContent = `from crawl4ai import AsyncWebCrawler
+from ${this.appData.slug.replace(/-/g, '_')} import ${this.appData.name.replace(/\s+/g, '')}
+
+async def main():
+    # Initialize ${this.appData.name}
+    automation = ${this.appData.name.replace(/\s+/g, '')}()
+
+    async with AsyncWebCrawler() as crawler:
+        result = await crawler.arun(
+            url="https://example.com",
+            browser_config=automation.config,
+            wait_for="css:body"
+        )
+        print(result.markdown)`;
+        } else if (this.appData.category === 'Proxy Services') {
+            usageCode.textContent = `from crawl4ai import AsyncWebCrawler
+import ${this.appData.slug.replace(/-/g, '_')}
+
+# Configure proxy
+proxy_config = {
+    "server": "${this.appData.website_url || 'https://proxy.example.com'}",
+    "username": "your_username",
+    "password": "your_password"
+}
+
+async with AsyncWebCrawler(proxy=proxy_config) as crawler:
+    result = await crawler.arun(
+        url="https://example.com",
+        bypass_cache=True
+    )
+    print(result.status_code)`;
+        } else if (this.appData.category === 'LLM Integration') {
+            usageCode.textContent = `from crawl4ai import AsyncWebCrawler
+from crawl4ai.extraction_strategy import LLMExtractionStrategy
+
+# Configure LLM extraction
+strategy = LLMExtractionStrategy(
+    provider="${this.appData.name.toLowerCase().includes('gpt') ? 'openai' : 'anthropic'}",
+    api_key="your-api-key",
+    model="${this.appData.name.toLowerCase().includes('gpt') ? 'gpt-4' : 'claude-3'}",
+    instruction="Extract structured data"
+)
+
+async with AsyncWebCrawler() as crawler:
+    result = await crawler.arun(
+        url="https://example.com",
+        extraction_strategy=strategy
+    )
+    print(result.extracted_content)`;
            }
        }

-        // Documentation tab - use documentation field from database
-        const docsDiv = document.getElementById('app-docs');
-        if (docsDiv) {
-            if (this.appData.documentation) {
-                docsDiv.innerHTML = this.renderMarkdown(this.appData.documentation);
-                // Add copy buttons to all code blocks
-                this.addCopyButtonsToCodeBlocks(docsDiv);
-            } else {
-                docsDiv.innerHTML = '<p>Documentation coming soon.</p>';
-            }
+        // Integration example
+        const integrationCode = document.getElementById('integration-code');
+        if (integrationCode) {
+            integrationCode.textContent = this.appData.integration_guide ||
+`# Complete ${this.appData.name} Integration Example
+
+from crawl4ai import AsyncWebCrawler
+from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
+import json
+
+async def crawl_with_${this.appData.slug.replace(/-/g, '_')}():
+    """
+    Complete example showing how to use ${this.appData.name}
+    with Crawl4AI for production web scraping
+    """
+
+    # Define extraction schema
+    schema = {
+        "name": "ProductList",
+        "baseSelector": "div.product",
+        "fields": [
+            {"name": "title", "selector": "h2", "type": "text"},
+            {"name": "price", "selector": ".price", "type": "text"},
+            {"name": "image", "selector": "img", "type": "attribute", "attribute": "src"},
+            {"name": "link", "selector": "a", "type": "attribute", "attribute": "href"}
+        ]
+    }
+
+    # Initialize crawler with ${this.appData.name}
+    async with AsyncWebCrawler(
+        browser_type="chromium",
+        headless=True,
+        verbose=True
+    ) as crawler:
+
+        # Crawl with extraction
+        result = await crawler.arun(
+            url="https://example.com/products",
+            extraction_strategy=JsonCssExtractionStrategy(schema),
+            cache_mode="bypass",
+            wait_for="css:.product",
+            screenshot=True
+        )
+
+        # Process results
+        if result.success:
+            products = json.loads(result.extracted_content)
+            print(f"Found {len(products)} products")
+
+            for product in products[:5]:
+                print(f"- {product['title']}: {product['price']}")
+
+        return products
+
+# Run the crawler
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(crawl_with_${this.appData.slug.replace(/-/g, '_')}())`;
        }
    }

-    addCopyButtonsToCodeBlocks(container) {
-        // Find all code blocks and add copy buttons
-        const codeBlocks = container.querySelectorAll('pre code');
-        codeBlocks.forEach(codeBlock => {
-            const pre = codeBlock.parentElement;
-
-            // Skip if already has a copy button
-            if (pre.querySelector('.copy-btn')) return;
-
-            // Create copy button
-            const copyBtn = document.createElement('button');
-            copyBtn.className = 'copy-btn';
-            copyBtn.textContent = 'Copy';
-            copyBtn.onclick = () => {
-                navigator.clipboard.writeText(codeBlock.textContent).then(() => {
-                    copyBtn.textContent = '✓ Copied!';
-                    setTimeout(() => {
-                        copyBtn.textContent = 'Copy';
-                    }, 2000);
-                });
-            };
-
-            // Add button to pre element
-            pre.style.position = 'relative';
-            pre.insertBefore(copyBtn, codeBlock);
-        });
-    }
-
-    renderMarkdown(text) {
-        if (!text) return '';
-
-        // Store code blocks temporarily to protect them from processing
-        const codeBlocks = [];
-        let processed = text.replace(/```(\w+)?\n([\s\S]*?)```/g, (match, lang, code) => {
-            const placeholder = `___CODE_BLOCK_${codeBlocks.length}___`;
-            codeBlocks.push(`<pre><code class="language-${lang || ''}">${this.escapeHtml(code)}</code></pre>`);
-            return placeholder;
-        });
-
-        // Store inline code temporarily
-        const inlineCodes = [];
-        processed = processed.replace(/`([^`]+)`/g, (match, code) => {
-            const placeholder = `___INLINE_CODE_${inlineCodes.length}___`;
-            inlineCodes.push(`<code>${this.escapeHtml(code)}</code>`);
-            return placeholder;
-        });
-
-        // Now process the rest of the markdown
-        processed = processed
-            // Headers
-            .replace(/^### (.*$)/gim, '<h3>$1</h3>')
-            .replace(/^## (.*$)/gim, '<h2>$1</h2>')
-            .replace(/^# (.*$)/gim, '<h1>$1</h1>')
-            // Bold
-            .replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>')
-            // Italic
-            .replace(/\*(.*?)\*/g, '<em>$1</em>')
-            // Links
-            .replace(/\[([^\]]+)\]\(([^)]+)\)/g, '<a href="$2" target="_blank">$1</a>')
-            // Line breaks
-            .replace(/\n\n/g, '</p><p>')
-            .replace(/\n/g, '<br>')
-            // Lists
-            .replace(/^\* (.*)$/gim, '<li>$1</li>')
-            .replace(/^- (.*)$/gim, '<li>$1</li>')
-            // Wrap in paragraphs
-            .replace(/^(?!<[h|p|pre|ul|ol|li])/gim, '<p>')
-            .replace(/(?<![>])$/gim, '</p>');
-
-        // Restore inline code
-        inlineCodes.forEach((code, i) => {
-            processed = processed.replace(`___INLINE_CODE_${i}___`, code);
-        });
-
-        // Restore code blocks
-        codeBlocks.forEach((block, i) => {
-            processed = processed.replace(`___CODE_BLOCK_${i}___`, block);
-        });
-
-        return processed;
-    }
-
-    escapeHtml(text) {
-        const div = document.createElement('div');
-        div.textContent = text;
-        return div.innerHTML;
-    }
-
    formatNumber(num) {
        if (num >= 1000000) {
            return (num / 1000000).toFixed(1) + 'M';
@@ -263,27 +275,45 @@ class AppDetailPage {
    setupEventListeners() {
        // Tab switching
        const tabs = document.querySelectorAll('.tab-btn');
-
        tabs.forEach(tab => {
            tab.addEventListener('click', () => {
-                // Update active tab button
+                // Update active tab
                tabs.forEach(t => t.classList.remove('active'));
                tab.classList.add('active');

                // Show corresponding content
                const tabName = tab.dataset.tab;
-
-                // Hide all tab contents
-                const allTabContents = document.querySelectorAll('.tab-content');
-                allTabContents.forEach(content => {
+                document.querySelectorAll('.tab-content').forEach(content => {
                    content.classList.remove('active');
                });
+                document.getElementById(`${tabName}-tab`).classList.add('active');
+            });
+        });

-                // Show the selected tab content
-                const targetTab = document.getElementById(`${tabName}-tab`);
-                if (targetTab) {
-                    targetTab.classList.add('active');
-                }
+        // Copy integration code
+        document.getElementById('copy-integration').addEventListener('click', () => {
+            const code = document.getElementById('integration-code').textContent;
+            navigator.clipboard.writeText(code).then(() => {
+                const btn = document.getElementById('copy-integration');
+                const originalText = btn.innerHTML;
+                btn.innerHTML = '<span>✓</span> Copied!';
+                setTimeout(() => {
+                    btn.innerHTML = originalText;
+                }, 2000);
+            });
+        });
+
+        // Copy code buttons
+        document.querySelectorAll('.copy-btn').forEach(btn => {
+            btn.addEventListener('click', (e) => {
+                const codeBlock = e.target.closest('.code-block');
+                const code = codeBlock.querySelector('code').textContent;
+                navigator.clipboard.writeText(code).then(() => {
+                    btn.textContent = 'Copied!';
+                    setTimeout(() => {
+                        btn.textContent = 'Copy';
+                    }, 2000);
+                });
            });
        });
    }
--- a/docs/md_v2/marketplace/backend/server.py
+++ b/docs/md_v2/marketplace/backend/server.py
@@ -471,17 +471,13 @@ async def delete_sponsor(sponsor_id: int):

 app.include_router(router)

-# Version info
-VERSION = "1.1.0"
-BUILD_DATE = "2025-10-26"

@app.get("/")
 async def root():
    """API info"""
    return {
        "name": "Crawl4AI Marketplace API",
-        "version": VERSION,
-        "build_date": BUILD_DATE,
+        "version": "1.0.0",
        "endpoints": [
            "/marketplace/api/apps",
            "/marketplace/api/articles",
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -31,7 +31,7 @@ dependencies = [
    "rank-bm25~=0.2",
    "snowballstemmer~=2.2",
    "pydantic>=2.10",
-    "pyOpenSSL>=25.3.0",
+    "pyOpenSSL>=24.3.0",
    "psutil>=6.1.1",
    "PyYAML>=6.0",
    "nltk>=3.9.1",
--- a/requirements.txt
+++ b/requirements.txt
@@ -19,7 +19,7 @@ rank-bm25~=0.2
 colorama~=0.4
 snowballstemmer~=2.2
 pydantic>=2.10
-pyOpenSSL>=25.3.0
+pyOpenSSL>=24.3.0
 psutil>=6.1.1
 PyYAML>=6.0
 nltk>=3.9.1
--- a/tests/general/test_async_crawler_strategy.py
+++ b/tests/general/test_async_crawler_strategy.py
@@ -364,19 +364,5 @@ async def test_network_error_handling():
        async with AsyncPlaywrightCrawlerStrategy() as strategy:
            await strategy.crawl("https://invalid.example.com", config)

-@pytest.mark.asyncio
-async def test_remove_overlay_elements(crawler_strategy):
-    config = CrawlerRunConfig(
-        remove_overlay_elements=True,
-        delay_before_return_html=5,
-    )
-    
-    response = await crawler_strategy.crawl(
-        "https://www2.hm.com/en_us/index.html",
-        config
-    )
-    assert response.status_code == 200
-    assert "Accept all cookies" not in response.html
-
 if __name__ == "__main__":
    pytest.main([__file__, "-v"])
--- a/tests/test_llm_extraction_parallel_issue_1055.py
+++ b/tests/test_llm_extraction_parallel_issue_1055.py
@@ -1,220 +0,0 @@
-"""
-Final verification test for Issue #1055 fix
-
-This test demonstrates that LLM extraction now runs in parallel
-when using arun_many with multiple URLs.
-"""
-
-import os
-import sys
-import time
-import asyncio
-
-grandparent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-sys.path.append(grandparent_dir)
-
-from crawl4ai import (
-    AsyncWebCrawler,
-    BrowserConfig,
-    CrawlerRunConfig,
-    CacheMode,
-    LLMExtractionStrategy,
-    LLMConfig,
-)
-
-from pydantic import BaseModel
-
-
-class SimpleData(BaseModel):
-    title: str
-    summary: str
-
-
-def print_section(title):
-    print("\n" + "=" * 80)
-    print(title)
-    print("=" * 80 + "\n")
-
-
-async def test_without_llm():
-    """Baseline: Test crawling without LLM extraction"""
-    print_section("TEST 1: Crawling WITHOUT LLM Extraction")
-
-    config = CrawlerRunConfig(
-        cache_mode=CacheMode.BYPASS,
-    )
-
-    browser_config = BrowserConfig(headless=True, verbose=False)
-
-    urls = [
-        "https://www.example.com",
-        "https://www.iana.org",
-        "https://www.wikipedia.org",
-    ]
-
-    print(f"Crawling {len(urls)} URLs without LLM extraction...")
-    print("Expected: Fast and parallel\n")
-
-    start_time = time.time()
-
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        results = await crawler.arun_many(urls=urls, config=config)
-
-    duration = time.time() - start_time
-
-    print(f"\n✅ Completed in {duration:.2f}s")
-    print(f"   Successful: {sum(1 for r in results if r.success)}/{len(urls)}")
-    print(f"   Average: {duration/len(urls):.2f}s per URL")
-
-    return duration
-
-
-async def test_with_llm_before_fix():
-    """Demonstrate the problem: Sequential execution with LLM"""
-    print_section("TEST 2: What Issue #1055 Reported (LLM Sequential Behavior)")
-
-    print("The issue reported that with LLM extraction, URLs would crawl")
-    print("one after another instead of in parallel.")
-    print("\nWithout our fix, this would show:")
-    print("  - URL 1 fetches → extracts → completes")
-    print("  - URL 2 fetches → extracts → completes")
-    print("  - URL 3 fetches → extracts → completes")
-    print("\nTotal time would be approximately sum of all individual times.")
-
-
-async def test_with_llm_after_fix():
-    """Demonstrate the fix: Parallel execution with LLM"""
-    print_section("TEST 3: After Fix - LLM Extraction in Parallel")
-
-    config = CrawlerRunConfig(
-        cache_mode=CacheMode.BYPASS,
-        extraction_strategy=LLMExtractionStrategy(
-            llm_config=LLMConfig(provider="openai/gpt-4o-mini"),
-            schema=SimpleData.model_json_schema(),
-            extraction_type="schema",
-            instruction="Extract title and summary",
-        )
-    )
-
-    browser_config = BrowserConfig(headless=True, verbose=False)
-
-    urls = [
-        "https://www.example.com",
-        "https://www.iana.org",
-        "https://www.wikipedia.org",
-    ]
-
-    print(f"Crawling {len(urls)} URLs WITH LLM extraction...")
-    print("Expected: Parallel execution with our fix\n")
-
-    completion_times = {}
-    start_time = time.time()
-
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        results = await crawler.arun_many(urls=urls, config=config)
-        for result in results:
-            elapsed = time.time() - start_time
-            completion_times[result.url] = elapsed
-            print(f"  [{elapsed:5.2f}s] ✓ {result.url[:50]}")
-
-    duration = time.time() - start_time
-
-    print(f"\n✅ Total time: {duration:.2f}s")
-    print(f"   Successful: {sum(1 for url in urls if url in completion_times)}/{len(urls)}")
-
-    # Analyze parallelism
-    times = list(completion_times.values())
-    if len(times) >= 2:
-        # If parallel, completion times should be staggered, not evenly spaced
-        time_diffs = [times[i+1] - times[i] for i in range(len(times)-1)]
-        avg_diff = sum(time_diffs) / len(time_diffs)
-
-        print(f"\nParallelism Analysis:")
-        print(f"   Completion time differences: {[f'{d:.2f}s' for d in time_diffs]}")
-        print(f"   Average difference: {avg_diff:.2f}s")
-
-        # In parallel mode, some tasks complete close together
-        # In sequential mode, they're evenly spaced (avg ~2-3s apart)
-        if avg_diff < duration / len(urls):
-            print(f"   ✅ PARALLEL: Tasks completed with overlapping execution")
-        else:
-            print(f"   ⚠️  SEQUENTIAL: Tasks completed one after another")
-
-    return duration
-
-
-async def test_multiple_arun_calls():
-    """Test multiple individual arun() calls in parallel"""
-    print_section("TEST 4: Multiple arun() Calls with asyncio.gather")
-
-    config = CrawlerRunConfig(
-        cache_mode=CacheMode.BYPASS,
-        extraction_strategy=LLMExtractionStrategy(
-            llm_config=LLMConfig(provider="openai/gpt-4o-mini"),
-            schema=SimpleData.model_json_schema(),
-            extraction_type="schema",
-            instruction="Extract title and summary",
-        )
-    )
-
-    browser_config = BrowserConfig(headless=True, verbose=False)
-
-    urls = [
-        "https://www.example.com",
-        "https://www.iana.org",
-        "https://www.wikipedia.org",
-    ]
-
-    print(f"Running {len(urls)} arun() calls with asyncio.gather()...")
-    print("Expected: True parallel execution\n")
-
-    start_time = time.time()
-
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        tasks = [crawler.arun(url, config=config) for url in urls]
-        results = await asyncio.gather(*tasks)
-
-    duration = time.time() - start_time
-
-    print(f"\n✅ Completed in {duration:.2f}s")
-    print(f"   Successful: {sum(1 for r in results if r.success)}/{len(urls)}")
-    print(f"   This proves the async LLM extraction works correctly")
-
-    return duration
-
-
-async def main():
-    print("\n" + "🚀" * 40)
-    print("ISSUE #1055 FIX VERIFICATION")
-    print("Testing: Sequential → Parallel LLM Extraction")
-    print("🚀" * 40)
-
-    # Run tests
-    await test_without_llm()
-
-    await test_with_llm_before_fix()
-
-    time_with_llm = await test_with_llm_after_fix()
-
-    time_gather = await test_multiple_arun_calls()
-
-    # Final summary
-    print_section("FINAL VERDICT")
-
-    print("✅ Fix Verified!")
-    print("\nWhat changed:")
-    print("  • Created aperform_completion_with_backoff() using litellm.acompletion")
-    print("  • Added arun() method to ExtractionStrategy base class")
-    print("  • Implemented parallel arun() in LLMExtractionStrategy")
-    print("  • Updated AsyncWebCrawler to use arun() when available")
-    print("\nResult:")
-    print("  • LLM extraction now runs in parallel across multiple URLs")
-    print("  • Backward compatible - existing strategies still work")
-    print("  • No breaking changes to the API")
-    print("\n✨ Issue #1055 is RESOLVED!")
-
-    print("\n" + "=" * 80 + "\n")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/tests/test_pyopenssl_security_fix.py
+++ b/tests/test_pyopenssl_security_fix.py
@@ -1,168 +0,0 @@
-"""
-Lightweight test to verify pyOpenSSL security fix (Issue #1545).
-
-This test verifies the security requirements are met:
-1. pyOpenSSL >= 25.3.0 is installed
-2. cryptography >= 45.0.7 is installed (above vulnerable range)
-3. SSL/TLS functionality works correctly
-
-This test can run without full crawl4ai dependencies installed.
-"""
-
-import sys
-from packaging import version
-
-
-def test_package_versions():
-    """Test that package versions meet security requirements."""
-    print("=" * 70)
-    print("TEST: Package Version Security Requirements (Issue #1545)")
-    print("=" * 70)
-
-    all_passed = True
-
-    # Test pyOpenSSL version
-    try:
-        import OpenSSL
-        pyopenssl_version = OpenSSL.__version__
-        print(f"\n✓ pyOpenSSL is installed: {pyopenssl_version}")
-
-        if version.parse(pyopenssl_version) >= version.parse("25.3.0"):
-            print(f"  ✓ PASS: pyOpenSSL {pyopenssl_version} >= 25.3.0 (required)")
-        else:
-            print(f"  ✗ FAIL: pyOpenSSL {pyopenssl_version} < 25.3.0 (required)")
-            all_passed = False
-
-    except ImportError as e:
-        print(f"\n✗ FAIL: pyOpenSSL not installed - {e}")
-        all_passed = False
-
-    # Test cryptography version
-    try:
-        import cryptography
-        crypto_version = cryptography.__version__
-        print(f"\n✓ cryptography is installed: {crypto_version}")
-
-        # The vulnerable range is >=37.0.0 & <43.0.1
-        # We need >= 45.0.7 to be safe
-        if version.parse(crypto_version) >= version.parse("45.0.7"):
-            print(f"  ✓ PASS: cryptography {crypto_version} >= 45.0.7 (secure)")
-            print(f"  ✓ NOT in vulnerable range (37.0.0 to 43.0.0)")
-        elif version.parse(crypto_version) >= version.parse("37.0.0") and version.parse(crypto_version) < version.parse("43.0.1"):
-            print(f"  ✗ FAIL: cryptography {crypto_version} is VULNERABLE")
-            print(f"  ✗ Version is in vulnerable range (>=37.0.0 & <43.0.1)")
-            all_passed = False
-        else:
-            print(f"  ⚠ WARNING: cryptography {crypto_version} < 45.0.7")
-            print(f"  ⚠ May not meet security requirements")
-
-    except ImportError as e:
-        print(f"\n✗ FAIL: cryptography not installed - {e}")
-        all_passed = False
-
-    return all_passed
-
-
-def test_ssl_basic_functionality():
-    """Test that SSL/TLS basic functionality works."""
-    print("\n" + "=" * 70)
-    print("TEST: SSL/TLS Basic Functionality")
-    print("=" * 70)
-
-    try:
-        import OpenSSL.SSL
-
-        # Create a basic SSL context to verify functionality
-        context = OpenSSL.SSL.Context(OpenSSL.SSL.TLSv1_2_METHOD)
-        print("\n✓ SSL Context created successfully")
-        print("  ✓ PASS: SSL/TLS functionality is working")
-        return True
-
-    except Exception as e:
-        print(f"\n✗ FAIL: SSL functionality test failed - {e}")
-        return False
-
-
-def test_pyopenssl_crypto_integration():
-    """Test that pyOpenSSL and cryptography integration works."""
-    print("\n" + "=" * 70)
-    print("TEST: pyOpenSSL <-> cryptography Integration")
-    print("=" * 70)
-
-    try:
-        from OpenSSL import crypto
-
-        # Generate a simple key pair to test integration
-        key = crypto.PKey()
-        key.generate_key(crypto.TYPE_RSA, 2048)
-
-        print("\n✓ Generated RSA key pair successfully")
-        print("  ✓ PASS: pyOpenSSL and cryptography are properly integrated")
-        return True
-
-    except Exception as e:
-        print(f"\n✗ FAIL: Integration test failed - {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def main():
-    """Run all security tests."""
-    print("\n")
-    print("╔" + "=" * 68 + "╗")
-    print("║  pyOpenSSL Security Fix Verification - Issue #1545               ║")
-    print("╚" + "=" * 68 + "╝")
-    print("\nVerifying that the pyOpenSSL update resolves the security vulnerability")
-    print("in the cryptography package (CVE: versions >=37.0.0 & <43.0.1)\n")
-
-    results = []
-
-    # Test 1: Package versions
-    results.append(("Package Versions", test_package_versions()))
-
-    # Test 2: SSL functionality
-    results.append(("SSL Functionality", test_ssl_basic_functionality()))
-
-    # Test 3: Integration
-    results.append(("pyOpenSSL-crypto Integration", test_pyopenssl_crypto_integration()))
-
-    # Summary
-    print("\n" + "=" * 70)
-    print("TEST SUMMARY")
-    print("=" * 70)
-
-    all_passed = True
-    for test_name, passed in results:
-        status = "✓ PASS" if passed else "✗ FAIL"
-        print(f"{status}: {test_name}")
-        all_passed = all_passed and passed
-
-    print("=" * 70)
-
-    if all_passed:
-        print("\n✓✓✓ ALL TESTS PASSED ✓✓✓")
-        print("✓ Security vulnerability is resolved")
-        print("✓ pyOpenSSL >= 25.3.0 is working correctly")
-        print("✓ cryptography >= 45.0.7 (not vulnerable)")
-        print("\nThe dependency update is safe to merge.\n")
-        return True
-    else:
-        print("\n✗✗✗ SOME TESTS FAILED ✗✗✗")
-        print("✗ Security requirements not met")
-        print("\nDo NOT merge until all tests pass.\n")
-        return False
-
-
-if __name__ == "__main__":
-    try:
-        success = main()
-        sys.exit(0 if success else 1)
-    except KeyboardInterrupt:
-        print("\n\nTest interrupted by user")
-        sys.exit(1)
-    except Exception as e:
-        print(f"\n✗ Unexpected error: {e}")
-        import traceback
-        traceback.print_exc()
-        sys.exit(1)
--- a/tests/test_pyopenssl_update.py
+++ b/tests/test_pyopenssl_update.py
@@ -1,184 +0,0 @@
-"""
-Test script to verify pyOpenSSL update doesn't break crawl4ai functionality.
-
-This test verifies:
-1. pyOpenSSL and cryptography versions are correct and secure
-2. Basic crawling functionality still works
-3. HTTPS/SSL connections work properly
-4. Stealth mode integration works (uses playwright-stealth internally)
-
-Issue: #1545 - Security vulnerability in cryptography package
-Fix: Updated pyOpenSSL from >=24.3.0 to >=25.3.0
-Expected: cryptography package should be >=45.0.7 (above vulnerable range)
-"""
-
-import asyncio
-import sys
-from packaging import version
-
-
-def check_versions():
-    """Verify pyOpenSSL and cryptography versions meet security requirements."""
-    print("=" * 60)
-    print("STEP 1: Checking Package Versions")
-    print("=" * 60)
-
-    try:
-        import OpenSSL
-        pyopenssl_version = OpenSSL.__version__
-        print(f"✓ pyOpenSSL version: {pyopenssl_version}")
-
-        # Check pyOpenSSL >= 25.3.0
-        if version.parse(pyopenssl_version) >= version.parse("25.3.0"):
-            print(f"  ✓ Version check passed: {pyopenssl_version} >= 25.3.0")
-        else:
-            print(f"  ✗ Version check FAILED: {pyopenssl_version} < 25.3.0")
-            return False
-
-    except ImportError as e:
-        print(f"✗ Failed to import pyOpenSSL: {e}")
-        return False
-
-    try:
-        import cryptography
-        crypto_version = cryptography.__version__
-        print(f"✓ cryptography version: {crypto_version}")
-
-        # Check cryptography >= 45.0.7 (above vulnerable range)
-        if version.parse(crypto_version) >= version.parse("45.0.7"):
-            print(f"  ✓ Security check passed: {crypto_version} >= 45.0.7 (not vulnerable)")
-        else:
-            print(f"  ✗ Security check FAILED: {crypto_version} < 45.0.7 (potentially vulnerable)")
-            return False
-
-    except ImportError as e:
-        print(f"✗ Failed to import cryptography: {e}")
-        return False
-
-    print("\n✓ All version checks passed!\n")
-    return True
-
-
-async def test_basic_crawl():
-    """Test basic crawling functionality with HTTPS site."""
-    print("=" * 60)
-    print("STEP 2: Testing Basic HTTPS Crawling")
-    print("=" * 60)
-
-    try:
-        from crawl4ai import AsyncWebCrawler
-
-        async with AsyncWebCrawler(verbose=True) as crawler:
-            # Test with a simple HTTPS site (requires SSL/TLS)
-            print("Crawling example.com (HTTPS)...")
-            result = await crawler.arun(
-                url="https://www.example.com",
-                bypass_cache=True
-            )
-
-            if result.success:
-                print(f"✓ Crawl successful!")
-                print(f"  - Status code: {result.status_code}")
-                print(f"  - Content length: {len(result.html)} bytes")
-                print(f"  - SSL/TLS connection: ✓ Working")
-                return True
-            else:
-                print(f"✗ Crawl failed: {result.error_message}")
-                return False
-
-    except Exception as e:
-        print(f"✗ Test failed with error: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-async def test_stealth_mode():
-    """Test stealth mode functionality (depends on playwright-stealth)."""
-    print("\n" + "=" * 60)
-    print("STEP 3: Testing Stealth Mode Integration")
-    print("=" * 60)
-
-    try:
-        from crawl4ai import AsyncWebCrawler, BrowserConfig
-
-        # Create browser config with stealth mode
-        browser_config = BrowserConfig(
-            headless=True,
-            verbose=False
-        )
-
-        async with AsyncWebCrawler(config=browser_config, verbose=True) as crawler:
-            print("Crawling with stealth mode enabled...")
-            result = await crawler.arun(
-                url="https://www.example.com",
-                bypass_cache=True
-            )
-
-            if result.success:
-                print(f"✓ Stealth crawl successful!")
-                print(f"  - Stealth mode: ✓ Working")
-                return True
-            else:
-                print(f"✗ Stealth crawl failed: {result.error_message}")
-                return False
-
-    except Exception as e:
-        print(f"✗ Stealth test failed with error: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-async def main():
-    """Run all tests."""
-    print("\n")
-    print("╔" + "=" * 58 + "╗")
-    print("║  pyOpenSSL Security Update Verification Test (Issue #1545) ║")
-    print("╚" + "=" * 58 + "╝")
-    print("\n")
-
-    # Step 1: Check versions
-    versions_ok = check_versions()
-    if not versions_ok:
-        print("\n✗ FAILED: Version requirements not met")
-        return False
-
-    # Step 2: Test basic crawling
-    crawl_ok = await test_basic_crawl()
-    if not crawl_ok:
-        print("\n✗ FAILED: Basic crawling test failed")
-        return False
-
-    # Step 3: Test stealth mode
-    stealth_ok = await test_stealth_mode()
-    if not stealth_ok:
-        print("\n✗ FAILED: Stealth mode test failed")
-        return False
-
-    # All tests passed
-    print("\n" + "=" * 60)
-    print("FINAL RESULT")
-    print("=" * 60)
-    print("✓ All tests passed successfully!")
-    print("✓ pyOpenSSL update is working correctly")
-    print("✓ No breaking changes detected")
-    print("✓ Security vulnerability resolved")
-    print("=" * 60)
-    print("\n")
-
-    return True
-
-
-if __name__ == "__main__":
-    try:
-        success = asyncio.run(main())
-        sys.exit(0 if success else 1)
-    except KeyboardInterrupt:
-        print("\n\nTest interrupted by user")
-        sys.exit(1)
-    except Exception as e:
-        print(f"\n✗ Unexpected error: {e}")
-        import traceback
-        traceback.print_exc()
-        sys.exit(1)