Merge branch 'develop' into feature/docker-cluster

.gitignore

@@ -267,6 +267,8 @@ continue_config.json
 .llm.env
 .private/
 
+.claude/
+
 CLAUDE_MONITOR.md
 CLAUDE.md
 

Dockerfile

@@ -1,7 +1,7 @@
 FROM python:3.12-slim-bookworm AS build
 
 # C4ai version
-ARG C4AI_VER=0.7.0-r1
+ARG C4AI_VER=0.7.6
 ENV C4AI_VERSION=$C4AI_VER
 LABEL c4ai.version=$C4AI_VER
 

README.md

@@ -27,11 +27,13 @@
 
 Crawl4AI turns the web into clean, LLM ready Markdown for RAG, agents, and data pipelines. Fast, controllable, battle tested by a 50k+ star community.
 
-[✨ Check out latest update v0.7.4](#-recent-updates)
+[✨ Check out latest update v0.7.6](#-recent-updates)
 
-✨ New in v0.7.4: Revolutionary LLM Table Extraction with intelligent chunking, enhanced concurrency fixes, memory management refactor, and critical stability improvements. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.4.md)
+✨ **New in v0.7.6**: Complete Webhook Infrastructure for Docker Job Queue API! Real-time notifications for both `/crawl/job` and `/llm/job` endpoints with exponential backoff retry, custom headers, and flexible delivery modes. No more polling! [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.6.md)
 
-✨ Recent v0.7.3: Undetected Browser Support, Multi-URL Configurations, Memory Monitoring, Enhanced Table Extraction, GitHub Sponsors. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.3.md)
+✨ Recent v0.7.5: Docker Hooks System with function-based API for pipeline customization, Enhanced LLM Integration with custom providers, HTTPS Preservation, and multiple community-reported bug fixes. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.5.md)
+
+✨ Previous v0.7.4: Revolutionary LLM Table Extraction with intelligent chunking, enhanced concurrency fixes, memory management refactor, and critical stability improvements. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.4.md)
 
 <details>
   <summary>🤓 <strong>My Personal Story</strong></summary>
@@ -177,7 +179,7 @@ No rate-limited APIs. No lock-in. Build and own your data pipeline with direct g
 - 📸 **Screenshots**: Capture page screenshots during crawling for debugging or analysis.
 - 📂 **Raw Data Crawling**: Directly process raw HTML (`raw:`) or local files (`file://`).
 - 🔗 **Comprehensive Link Extraction**: Extracts internal, external links, and embedded iframe content.
-- 🛠️ **Customizable Hooks**: Define hooks at every step to customize crawling behavior.
+- 🛠️ **Customizable Hooks**: Define hooks at every step to customize crawling behavior (supports both string and function-based APIs).
 - 💾 **Caching**: Cache data for improved speed and to avoid redundant fetches.
 - 📄 **Metadata Extraction**: Retrieve structured metadata from web pages.
 - 📡 **IFrame Content Extraction**: Seamless extraction from embedded iframe content.
@@ -544,6 +546,54 @@ async def test_news_crawl():
 
 ## ✨ Recent Updates
 
+<details>
+<summary><strong>Version 0.7.5 Release Highlights - The Docker Hooks & Security Update</strong></summary>
+
+- **🔧 Docker Hooks System**: Complete pipeline customization with user-provided Python functions at 8 key points
+- **✨ Function-Based Hooks API (NEW)**: Write hooks as regular Python functions with full IDE support:
+  ```python
+  from crawl4ai import hooks_to_string
+  from crawl4ai.docker_client import Crawl4aiDockerClient
+
+  # Define hooks as regular Python functions
+  async def on_page_context_created(page, context, **kwargs):
+      """Block images to speed up crawling"""
+      await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+      await page.set_viewport_size({"width": 1920, "height": 1080})
+      return page
+
+  async def before_goto(page, context, url, **kwargs):
+      """Add custom headers"""
+      await page.set_extra_http_headers({'X-Crawl4AI': 'v0.7.5'})
+      return page
+
+  # Option 1: Use hooks_to_string() utility for REST API
+  hooks_code = hooks_to_string({
+      "on_page_context_created": on_page_context_created,
+      "before_goto": before_goto
+  })
+
+  # Option 2: Docker client with automatic conversion (Recommended)
+  client = Crawl4aiDockerClient(base_url="http://localhost:11235")
+  results = await client.crawl(
+      urls=["https://httpbin.org/html"],
+      hooks={
+          "on_page_context_created": on_page_context_created,
+          "before_goto": before_goto
+      }
+  )
+  # ✓ Full IDE support, type checking, and reusability!
+  ```
+
+- **🤖 Enhanced LLM Integration**: Custom providers with temperature control and base_url configuration
+- **🔒 HTTPS Preservation**: Secure internal link handling with `preserve_https_for_internal_links=True`
+- **🐍 Python 3.10+ Support**: Modern language features and enhanced performance
+- **🛠️ Bug Fixes**: Resolved multiple community-reported issues including URL processing, JWT authentication, and proxy configuration
+
+[Full v0.7.5 Release Notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.5.md)
+
+</details>
+
 <details>
 <summary><strong>Version 0.7.4 Release Highlights - The Intelligent Table Extraction & Performance Update</strong></summary>
 
@@ -919,6 +969,36 @@ We envision a future where AI is powered by real human knowledge, ensuring data
 For more details, see our [full mission statement](./MISSION.md).
 </details>
 
+## 🌟 Current Sponsors
+
+### 🏢 Enterprise Sponsors & Partners
+
+Our enterprise sponsors and technology partners help scale Crawl4AI to power production-grade data pipelines.
+
+| Company | About | Sponsorship Tier |
+|------|------|----------------------------|
+| <a href="https://dashboard.capsolver.com/passport/register?inviteCode=ESVSECTX5Q23" target="_blank"><picture><source width="120" media="(prefers-color-scheme: dark)" srcset="https://docs.crawl4ai.com/uploads/sponsors/20251013045338_72a71fa4ee4d2f40.png"><source width="120" media="(prefers-color-scheme: light)" srcset="https://www.capsolver.com/assets/images/logo-text.png"><img alt="Capsolver" src="https://www.capsolver.com/assets/images/logo-text.png"></picture></a> | AI-powered Captcha solving service. Supports all major Captcha types, including reCAPTCHA, Cloudflare, and more | 🥈 Silver |
+| <a href="https://kipo.ai" target="_blank"><img src="https://docs.crawl4ai.com/uploads/sponsors/20251013045751_2d54f57f117c651e.png" alt="DataSync" width="120"/></a> | Helps engineers and buyers find, compare, and source electronic & industrial parts in seconds, with specs, pricing, lead times & alternatives.| 🥇 Gold |
+| <a href="https://www.kidocode.com/" target="_blank"><img src="https://docs.crawl4ai.com/uploads/sponsors/20251013045045_bb8dace3f0440d65.svg" alt="Kidocode" width="120"/><p align="center">KidoCode</p></a> | Kidocode is a hybrid technology and entrepreneurship school for kids aged 5–18, offering both online and on-campus education. | 🥇 Gold |
+| <a href="https://www.alephnull.sg/" target="_blank"><img src="https://docs.crawl4ai.com/uploads/sponsors/20251013050323_a9e8e8c4c3650421.svg" alt="Aleph null" width="120"/></a> | Singapore-based  Aleph Null is Asia’s leading edtech hub, dedicated to student-centric, AI-driven education—empowering learners with the tools to thrive in a fast-changing world. | 🥇 Gold |
+
+### 🧑‍🤝 Individual Sponsors
+
+A heartfelt thanks to our individual supporters! Every contribution helps us keep our opensource mission alive and thriving!
+
+<p align="left">
+  <a href="https://github.com/hafezparast"><img src="https://avatars.githubusercontent.com/u/14273305?s=60&v=4" style="border-radius:50%;" width="64px;"/></a>
+  <a href="https://github.com/ntohidi"><img src="https://avatars.githubusercontent.com/u/17140097?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/Sjoeborg"><img src="https://avatars.githubusercontent.com/u/17451310?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/romek-rozen"><img src="https://avatars.githubusercontent.com/u/30595969?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/Kourosh-Kiyani"><img src="https://avatars.githubusercontent.com/u/34105600?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/Etherdrake"><img src="https://avatars.githubusercontent.com/u/67021215?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/shaman247"><img src="https://avatars.githubusercontent.com/u/211010067?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+  <a href="https://github.com/work-flow-manager"><img src="https://avatars.githubusercontent.com/u/217665461?s=60&v=4" style="border-radius:50%;"width="64px;"/></a>
+</p>
+
+> Want to join them? [Sponsor Crawl4AI →](https://github.com/sponsors/unclecode)
+
 ## Star History
 
 [![Star History Chart](https://api.star-history.com/svg?repos=unclecode/crawl4ai&type=Date)](https://star-history.com/#unclecode/crawl4ai&Date)

crawl4ai/__init__.py

@@ -103,7 +103,8 @@ from .browser_adapter import (
 
 from .utils import (
     start_colab_display_server,
-    setup_colab_environment
+    setup_colab_environment,
+    hooks_to_string
 )
 
 __all__ = [
@@ -183,6 +184,7 @@ __all__ = [
     "ProxyConfig",
     "start_colab_display_server",
     "setup_colab_environment",
+    "hooks_to_string",
     # C4A Script additions
     "c4a_compile",
     "c4a_validate", 

crawl4ai/__version__.py

@@ -1,7 +1,7 @@
 # crawl4ai/__version__.py
 
 # This is the version that will be used for stable releases
-__version__ = "0.7.4"
+__version__ = "0.7.6"
 
 # For nightly builds, this gets set during build process
 __nightly_version__ = None

crawl4ai/docker_client.py

@@ -1,4 +1,4 @@
-from typing import List, Optional, Union, AsyncGenerator, Dict, Any
+from typing import List, Optional, Union, AsyncGenerator, Dict, Any, Callable
 import httpx
 import json
 from urllib.parse import urljoin
@@ -7,6 +7,7 @@ import asyncio
 from .async_configs import BrowserConfig, CrawlerRunConfig
 from .models import CrawlResult
 from .async_logger import AsyncLogger, LogLevel
+from .utils import hooks_to_string
 
 
 class Crawl4aiClientError(Exception):
@@ -70,17 +71,41 @@ class Crawl4aiDockerClient:
             self.logger.error(f"Server unreachable: {str(e)}", tag="ERROR")
             raise ConnectionError(f"Cannot connect to server: {str(e)}")
 
-    def _prepare_request(self, urls: List[str], browser_config: Optional[BrowserConfig] = None, 
+    def _prepare_request(
-                       crawler_config: Optional[CrawlerRunConfig] = None) -> Dict[str, Any]:
+        self,
+        urls: List[str],
+        browser_config: Optional[BrowserConfig] = None,
+        crawler_config: Optional[CrawlerRunConfig] = None,
+        hooks: Optional[Union[Dict[str, Callable], Dict[str, str]]] = None,
+        hooks_timeout: int = 30
+    ) -> Dict[str, Any]:
         """Prepare request data from configs."""
         if self._token:
             self._http_client.headers["Authorization"] = f"Bearer {self._token}"
-        return {
+
+        request_data = {
             "urls": urls,
             "browser_config": browser_config.dump() if browser_config else {},
             "crawler_config": crawler_config.dump() if crawler_config else {}
         }
 
+        # Handle hooks if provided
+        if hooks:
+            # Check if hooks are already strings or need conversion
+            if any(callable(v) for v in hooks.values()):
+                # Convert function objects to strings
+                hooks_code = hooks_to_string(hooks)
+            else:
+                # Already in string format
+                hooks_code = hooks
+
+            request_data["hooks"] = {
+                "code": hooks_code,
+                "timeout": hooks_timeout
+            }
+
+        return request_data
+
     async def _request(self, method: str, endpoint: str, **kwargs) -> httpx.Response:
         """Make an HTTP request with error handling."""
         url = urljoin(self.base_url, endpoint)
@@ -102,16 +127,42 @@ class Crawl4aiDockerClient:
         self,
         urls: List[str],
         browser_config: Optional[BrowserConfig] = None,
-        crawler_config: Optional[CrawlerRunConfig] = None
+        crawler_config: Optional[CrawlerRunConfig] = None,
+        hooks: Optional[Union[Dict[str, Callable], Dict[str, str]]] = None,
+        hooks_timeout: int = 30
     ) -> Union[CrawlResult, List[CrawlResult], AsyncGenerator[CrawlResult, None]]:
-        """Execute a crawl operation."""
+        """
+        Execute a crawl operation.
+
+        Args:
+            urls: List of URLs to crawl
+            browser_config: Browser configuration
+            crawler_config: Crawler configuration
+            hooks: Optional hooks - can be either:
+                   - Dict[str, Callable]: Function objects that will be converted to strings
+                   - Dict[str, str]: Already stringified hook code
+            hooks_timeout: Timeout in seconds for each hook execution (1-120)
+
+        Returns:
+            Single CrawlResult, list of results, or async generator for streaming
+
+        Example with function hooks:
+            >>> async def my_hook(page, context, **kwargs):
+            ...     await page.set_viewport_size({"width": 1920, "height": 1080})
+            ...     return page
+            >>>
+            >>> result = await client.crawl(
+            ...     ["https://example.com"],
+            ...     hooks={"on_page_context_created": my_hook}
+            ... )
+        """
         await self._check_server()
-        
+
-        data = self._prepare_request(urls, browser_config, crawler_config)
+        data = self._prepare_request(urls, browser_config, crawler_config, hooks, hooks_timeout)
         is_streaming = crawler_config and crawler_config.stream
-        
+
         self.logger.info(f"Crawling {len(urls)} URLs {'(streaming)' if is_streaming else ''}", tag="CRAWL")
-        
+
         if is_streaming:
             async def stream_results() -> AsyncGenerator[CrawlResult, None]:
                 async with self._http_client.stream("POST", f"{self.base_url}/crawl/stream", json=data) as response:
@@ -128,12 +179,12 @@ class Crawl4aiDockerClient:
                             else:
                                 yield CrawlResult(**result)
             return stream_results()
-        
+
         response = await self._request("POST", "/crawl", json=data)
         result_data = response.json()
         if not result_data.get("success", False):
             raise RequestError(f"Crawl failed: {result_data.get('msg', 'Unknown error')}")
-        
+
         results = [CrawlResult(**r) for r in result_data.get("results", [])]
         self.logger.success(f"Crawl completed with {len(results)} results", tag="CRAWL")
         return results[0] if len(results) == 1 else results

crawl4ai/utils.py

@@ -47,6 +47,7 @@ from urllib.parse import (
     urljoin, urlparse, urlunparse,
     parse_qsl, urlencode, quote, unquote
 )
+import inspect
 
 
 # Monkey patch to fix wildcard handling in urllib.robotparser
@@ -3529,4 +3530,52 @@ def get_memory_stats() -> Tuple[float, float, float]:
     available_gb = get_true_available_memory_gb()
     used_percent = get_true_memory_usage_percent()
     
-    return used_percent, available_gb, total_gb
+    return used_percent, available_gb, total_gb
+
+
+# Hook utilities for Docker API
+def hooks_to_string(hooks: Dict[str, Callable]) -> Dict[str, str]:
+    """
+    Convert hook function objects to string representations for Docker API.
+
+    This utility simplifies the process of using hooks with the Docker API by converting
+    Python function objects into the string format required by the API.
+
+    Args:
+        hooks: Dictionary mapping hook point names to Python function objects.
+               Functions should be async and follow hook signature requirements.
+
+    Returns:
+        Dictionary mapping hook point names to string representations of the functions.
+
+    Example:
+        >>> async def my_hook(page, context, **kwargs):
+        ...     await page.set_viewport_size({"width": 1920, "height": 1080})
+        ...     return page
+        >>>
+        >>> hooks_dict = {"on_page_context_created": my_hook}
+        >>> api_hooks = hooks_to_string(hooks_dict)
+        >>> # api_hooks is now ready to use with Docker API
+
+    Raises:
+        ValueError: If a hook is not callable or source cannot be extracted
+    """
+    result = {}
+
+    for hook_name, hook_func in hooks.items():
+        if not callable(hook_func):
+            raise ValueError(f"Hook '{hook_name}' must be a callable function, got {type(hook_func)}")
+
+        try:
+            # Get the source code of the function
+            source = inspect.getsource(hook_func)
+            # Remove any leading indentation to get clean source
+            source = textwrap.dedent(source)
+            result[hook_name] = source
+        except (OSError, TypeError) as e:
+            raise ValueError(
+                f"Cannot extract source code for hook '{hook_name}'. "
+                f"Make sure the function is defined in a file (not interactively). Error: {e}"
+            )
+
+    return result

deploy/docker/README.md

@@ -12,6 +12,7 @@
   - [Python SDK](#python-sdk)
   - [Understanding Request Schema](#understanding-request-schema)
   - [REST API Examples](#rest-api-examples)
+  - [Asynchronous Jobs with Webhooks](#asynchronous-jobs-with-webhooks)
 - [Additional API Endpoints](#additional-api-endpoints)
   - [HTML Extraction Endpoint](#html-extraction-endpoint)
   - [Screenshot Endpoint](#screenshot-endpoint)
@@ -58,15 +59,13 @@ Pull and run images directly from Docker Hub without building locally.
 
 #### 1. Pull the Image
 
-Our latest release candidate is `0.7.0-r1`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
+Our latest stable release is `0.7.6`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
-
-> ⚠️ **Important Note**: The `latest` tag currently points to the stable `0.6.0` version. After testing and validation, `0.7.0` (without -r1) will be released and `latest` will be updated. For now, please use `0.7.0-r1` to test the new features.
 
 ```bash
-# Pull the release candidate (for testing new features)
+# Pull the latest stable version (0.7.6)
-docker pull unclecode/crawl4ai:0.7.0-r1
+docker pull unclecode/crawl4ai:0.7.6
 
-# Or pull the current stable version (0.6.0)
+# Or use the latest tag (points to 0.7.6)
 docker pull unclecode/crawl4ai:latest
 ```
 
@@ -101,7 +100,7 @@ EOL
       -p 11235:11235 \
       --name crawl4ai \
       --shm-size=1g \
-      unclecode/crawl4ai:0.7.0-r1
+      unclecode/crawl4ai:0.7.6
     ```
 
 *   **With LLM support:**
@@ -112,7 +111,7 @@ EOL
       --name crawl4ai \
       --env-file .llm.env \
       --shm-size=1g \
-      unclecode/crawl4ai:0.7.0-r1
+      unclecode/crawl4ai:0.7.6
     ```
 
 > The server will be available at `http://localhost:11235`. Visit `/playground` to access the interactive testing interface.
@@ -185,7 +184,7 @@ The `docker-compose.yml` file in the project root provides a simplified approach
     ```bash
     # Pulls and runs the release candidate from Docker Hub
     # Automatically selects the correct architecture
-    IMAGE=unclecode/crawl4ai:0.7.0-r1 docker compose up -d
+    IMAGE=unclecode/crawl4ai:0.7.6 docker compose up -d
     ```
 
 *   **Build and Run Locally:**
@@ -648,6 +647,194 @@ async def test_stream_crawl(token: str = None): # Made token optional
 # asyncio.run(test_stream_crawl())
 ```
 
+### Asynchronous Jobs with Webhooks
+
+For long-running crawls or when you want to avoid keeping connections open, use the job queue endpoints. Instead of polling for results, configure a webhook to receive notifications when jobs complete.
+
+#### Why Use Jobs & Webhooks?
+
+- **No Polling Required** - Get notified when crawls complete instead of constantly checking status
+- **Better Resource Usage** - Free up client connections while jobs run in the background
+- **Scalable Architecture** - Ideal for high-volume crawling with TypeScript/Node.js clients or microservices
+- **Reliable Delivery** - Automatic retry with exponential backoff (5 attempts: 1s → 2s → 4s → 8s → 16s)
+
+#### How It Works
+
+1. **Submit Job** → POST to `/crawl/job` with optional `webhook_config`
+2. **Get Task ID** → Receive a `task_id` immediately
+3. **Job Runs** → Crawl executes in the background
+4. **Webhook Fired** → Server POSTs completion notification to your webhook URL
+5. **Fetch Results** → If data wasn't included in webhook, GET `/crawl/job/{task_id}`
+
+#### Quick Example
+
+```bash
+# Submit a crawl job with webhook notification
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": false
+    }
+  }'
+
+# Response: {"task_id": "crawl_a1b2c3d4"}
+```
+
+**Your webhook receives:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4",
+  "task_type": "crawl",
+  "status": "completed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com"]
+}
+```
+
+Then fetch the results:
+```bash
+curl http://localhost:11235/crawl/job/crawl_a1b2c3d4
+```
+
+#### Include Data in Webhook
+
+Set `webhook_data_in_payload: true` to receive the full crawl results directly in the webhook:
+
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": true
+    }
+  }'
+```
+
+**Your webhook receives the complete data:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4",
+  "task_type": "crawl",
+  "status": "completed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "data": {
+    "markdown": "...",
+    "html": "...",
+    "links": {...},
+    "metadata": {...}
+  }
+}
+```
+
+#### Webhook Authentication
+
+Add custom headers for authentication:
+
+```json
+{
+  "urls": ["https://example.com"],
+  "webhook_config": {
+    "webhook_url": "https://myapp.com/webhooks/crawl",
+    "webhook_data_in_payload": false,
+    "webhook_headers": {
+      "X-Webhook-Secret": "your-secret-token",
+      "X-Service-ID": "crawl4ai-prod"
+    }
+  }
+}
+```
+
+#### Global Default Webhook
+
+Configure a default webhook URL in `config.yml` for all jobs:
+
+```yaml
+webhooks:
+  enabled: true
+  default_url: "https://myapp.com/webhooks/default"
+  data_in_payload: false
+  retry:
+    max_attempts: 5
+    initial_delay_ms: 1000
+    max_delay_ms: 32000
+    timeout_ms: 30000
+```
+
+Now jobs without `webhook_config` automatically use the default webhook.
+
+#### Job Status Polling (Without Webhooks)
+
+If you prefer polling instead of webhooks, just omit `webhook_config`:
+
+```bash
+# Submit job
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{"urls": ["https://example.com"]}'
+# Response: {"task_id": "crawl_xyz"}
+
+# Poll for status
+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.
+
 ---
 
 ## Metrics & Monitoring
@@ -826,10 +1013,11 @@ We're here to help you succeed with Crawl4AI! Here's how to get support:
 
 In this guide, we've covered everything you need to get started with Crawl4AI's Docker deployment:
 - Building and running the Docker container
-- Configuring the environment  
+- Configuring the environment
 - Using the interactive playground for testing
 - Making API requests with proper typing
 - Using the Python SDK
+- Asynchronous job queues with webhook notifications
 - Leveraging specialized endpoints for screenshots, PDFs, and JavaScript execution
 - Connecting via the Model Context Protocol (MCP)
 - Monitoring your deployment

deploy/docker/WEBHOOK_EXAMPLES.md

@@ -0,0 +1,378 @@
+# Webhook Feature Examples
+
+This document provides examples of how to use the webhook feature for crawl jobs in Crawl4AI.
+
+## Overview
+
+The webhook feature allows you to receive notifications when crawl jobs complete, eliminating the need for polling. Webhooks are sent with exponential backoff retry logic to ensure reliable delivery.
+
+## Configuration
+
+### Global Configuration (config.yml)
+
+You can configure default webhook settings in `config.yml`:
+
+```yaml
+webhooks:
+  enabled: true
+  default_url: null  # Optional: default webhook URL for all jobs
+  data_in_payload: false  # Optional: default behavior for including data
+  retry:
+    max_attempts: 5
+    initial_delay_ms: 1000  # 1s, 2s, 4s, 8s, 16s exponential backoff
+    max_delay_ms: 32000
+    timeout_ms: 30000  # 30s timeout per webhook call
+  headers:  # Optional: default headers to include
+    User-Agent: "Crawl4AI-Webhook/1.0"
+```
+
+## API Usage Examples
+
+### Example 1: Basic Webhook (Notification Only)
+
+Send a webhook notification without including the crawl data in the payload.
+
+**Request:**
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": false
+    }
+  }'
+```
+
+**Response:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4"
+}
+```
+
+**Webhook Payload Received:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4",
+  "task_type": "crawl",
+  "status": "completed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com"]
+}
+```
+
+Your webhook handler should then fetch the results:
+```bash
+curl http://localhost:11235/crawl/job/crawl_a1b2c3d4
+```
+
+### Example 2: Webhook with Data Included
+
+Include the full crawl results in the webhook payload.
+
+**Request:**
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": true
+    }
+  }'
+```
+
+**Webhook Payload Received:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4",
+  "task_type": "crawl",
+  "status": "completed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "data": {
+    "markdown": "...",
+    "html": "...",
+    "links": {...},
+    "metadata": {...}
+  }
+}
+```
+
+### Example 3: Webhook with Custom Headers
+
+Include custom headers for authentication or identification.
+
+**Request:**
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": false,
+      "webhook_headers": {
+        "X-Webhook-Secret": "my-secret-token",
+        "X-Service-ID": "crawl4ai-production"
+      }
+    }
+  }'
+```
+
+The webhook will be sent with these additional headers plus the default headers from config.
+
+### Example 4: Failure Notification
+
+When a crawl job fails, a webhook is sent with error details.
+
+**Webhook Payload on Failure:**
+```json
+{
+  "task_id": "crawl_a1b2c3d4",
+  "task_type": "crawl",
+  "status": "failed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "error": "Connection timeout after 30s"
+}
+```
+
+### Example 5: Using Global Default Webhook
+
+If you set a `default_url` in config.yml, jobs without webhook_config will use it:
+
+**config.yml:**
+```yaml
+webhooks:
+  enabled: true
+  default_url: "https://myapp.com/webhooks/default"
+  data_in_payload: false
+```
+
+**Request (no webhook_config needed):**
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"]
+  }'
+```
+
+The webhook will be sent to the default URL configured in config.yml.
+
+### Example 6: LLM Extraction Job with Webhook
+
+Use webhooks with the LLM extraction endpoint for asynchronous processing.
+
+**Request:**
+```bash
+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 publication date",
+    "schema": "{\"type\": \"object\", \"properties\": {\"title\": {\"type\": \"string\"}, \"author\": {\"type\": \"string\"}, \"date\": {\"type\": \"string\"}}}",
+    "cache": false,
+    "provider": "openai/gpt-4o-mini",
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/llm-complete",
+      "webhook_data_in_payload": true
+    }
+  }'
+```
+
+**Response:**
+```json
+{
+  "task_id": "llm_1698765432_12345"
+}
+```
+
+**Webhook Payload Received:**
+```json
+{
+  "task_id": "llm_1698765432_12345",
+  "task_type": "llm_extraction",
+  "status": "completed",
+  "timestamp": "2025-10-21T10:30:00.000000+00:00",
+  "urls": ["https://example.com/article"],
+  "data": {
+    "extracted_content": {
+      "title": "Understanding Web Scraping",
+      "author": "John Doe",
+      "date": "2025-10-21"
+    }
+  }
+}
+```
+
+## Webhook Handler Example
+
+Here's a simple Python Flask webhook handler that supports both crawl and LLM extraction jobs:
+
+```python
+from flask import Flask, request, jsonify
+import requests
+
+app = Flask(__name__)
+
+@app.route('/webhooks/crawl-complete', methods=['POST'])
+def handle_crawl_webhook():
+    payload = request.json
+
+    task_id = payload['task_id']
+    task_type = payload['task_type']
+    status = payload['status']
+
+    if status == 'completed':
+        # If data not in payload, fetch it
+        if 'data' not in payload:
+            # Determine endpoint based on task type
+            endpoint = 'crawl' if task_type == 'crawl' else 'llm'
+            response = requests.get(f'http://localhost:11235/{endpoint}/job/{task_id}')
+            data = response.json()
+        else:
+            data = payload['data']
+
+        # Process based on task type
+        if task_type == 'crawl':
+            print(f"Processing crawl results for {task_id}")
+            # Handle crawl results
+            results = data.get('results', [])
+            for result in results:
+                print(f"  - {result.get('url')}: {len(result.get('markdown', ''))} chars")
+
+        elif task_type == 'llm_extraction':
+            print(f"Processing LLM extraction for {task_id}")
+            # Handle LLM extraction
+            # Note: Webhook sends 'extracted_content', API returns 'result'
+            extracted = data.get('extracted_content', data.get('result', {}))
+            print(f"  - Extracted: {extracted}")
+
+        # Your business logic here...
+
+    elif status == 'failed':
+        error = payload.get('error', 'Unknown error')
+        print(f"{task_type} job {task_id} failed: {error}")
+        # Handle failure...
+
+    return jsonify({"status": "received"}), 200
+
+if __name__ == '__main__':
+    app.run(port=8080)
+```
+
+## Retry Logic
+
+The webhook delivery service uses exponential backoff retry logic:
+
+- **Attempts:** Up to 5 attempts by default
+- **Delays:** 1s → 2s → 4s → 8s → 16s
+- **Timeout:** 30 seconds per attempt
+- **Retry Conditions:**
+  - Server errors (5xx status codes)
+  - Network errors
+  - Timeouts
+- **No Retry:**
+  - Client errors (4xx status codes)
+  - Successful delivery (2xx status codes)
+
+## Benefits
+
+1. **No Polling Required** - Eliminates constant API calls to check job status
+2. **Real-time Notifications** - Immediate notification when jobs complete
+3. **Reliable Delivery** - Exponential backoff ensures webhooks are delivered
+4. **Flexible** - Choose between notification-only or full data delivery
+5. **Secure** - Support for custom headers for authentication
+6. **Configurable** - Global defaults or per-job configuration
+7. **Universal Support** - Works with both `/crawl/job` and `/llm/job` endpoints
+
+## TypeScript Client Example
+
+```typescript
+interface WebhookConfig {
+  webhook_url: string;
+  webhook_data_in_payload?: boolean;
+  webhook_headers?: Record<string, string>;
+}
+
+interface CrawlJobRequest {
+  urls: string[];
+  browser_config?: Record<string, any>;
+  crawler_config?: Record<string, any>;
+  webhook_config?: WebhookConfig;
+}
+
+interface LLMJobRequest {
+  url: string;
+  q: string;
+  schema?: string;
+  cache?: boolean;
+  provider?: string;
+  webhook_config?: WebhookConfig;
+}
+
+async function createCrawlJob(request: CrawlJobRequest) {
+  const response = await fetch('http://localhost:11235/crawl/job', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify(request)
+  });
+
+  const { task_id } = await response.json();
+  return task_id;
+}
+
+async function createLLMJob(request: LLMJobRequest) {
+  const response = await fetch('http://localhost:11235/llm/job', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify(request)
+  });
+
+  const { task_id } = await response.json();
+  return task_id;
+}
+
+// Usage - Crawl Job
+const crawlTaskId = await createCrawlJob({
+  urls: ['https://example.com'],
+  webhook_config: {
+    webhook_url: 'https://myapp.com/webhooks/crawl-complete',
+    webhook_data_in_payload: false,
+    webhook_headers: {
+      'X-Webhook-Secret': 'my-secret'
+    }
+  }
+});
+
+// Usage - LLM Extraction Job
+const llmTaskId = await createLLMJob({
+  url: 'https://example.com/article',
+  q: 'Extract the main points from this article',
+  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': 'my-secret'
+    }
+  }
+});
+```
+
+## Monitoring and Debugging
+
+Webhook delivery attempts are logged at INFO level:
+- Successful deliveries
+- Retry attempts with delays
+- Final failures after max attempts
+
+Check the application logs for webhook delivery status:
+```bash
+docker logs crawl4ai-container | grep -i webhook
+```

deploy/docker/api.py

@@ -46,6 +46,7 @@ from utils import (
     get_llm_temperature,
     get_llm_base_url
 )
+from webhook import WebhookDeliveryService
 
 import psutil, time
 
@@ -127,10 +128,14 @@ async def process_llm_extraction(
     schema: Optional[str] = None,
     cache: str = "0",
     provider: Optional[str] = None,
+    webhook_config: Optional[Dict] = None,
     temperature: Optional[float] = None,
     base_url: Optional[str] = None
 ) -> None:
     """Process LLM extraction in background."""
+    # Initialize webhook service
+    webhook_service = WebhookDeliveryService(config)
+
     try:
         # Validate provider
         is_valid, error_msg = validate_llm_provider(config, provider)
@@ -139,6 +144,16 @@ async def process_llm_extraction(
                 "status": TaskStatus.FAILED,
                 "error": error_msg
             })
+
+            # Send webhook notification on failure
+            await webhook_service.notify_job_completion(
+                task_id=task_id,
+                task_type="llm_extraction",
+                status="failed",
+                urls=[url],
+                webhook_config=webhook_config,
+                error=error_msg
+            )
             return
         api_key = get_llm_api_key(config, provider)  # Returns None to let litellm handle it
         llm_strategy = LLMExtractionStrategy(
@@ -169,17 +184,40 @@ async def process_llm_extraction(
                 "status": TaskStatus.FAILED,
                 "error": result.error_message
             })
+
+            # Send webhook notification on failure
+            await webhook_service.notify_job_completion(
+                task_id=task_id,
+                task_type="llm_extraction",
+                status="failed",
+                urls=[url],
+                webhook_config=webhook_config,
+                error=result.error_message
+            )
             return
 
         try:
             content = json.loads(result.extracted_content)
         except json.JSONDecodeError:
             content = result.extracted_content
+
+        result_data = {"extracted_content": content}
+
         await redis.hset(f"task:{task_id}", mapping={
             "status": TaskStatus.COMPLETED,
             "result": json.dumps(content)
         })
 
+        # Send webhook notification on successful completion
+        await webhook_service.notify_job_completion(
+            task_id=task_id,
+            task_type="llm_extraction",
+            status="completed",
+            urls=[url],
+            webhook_config=webhook_config,
+            result=result_data
+        )
+
     except Exception as e:
         logger.error(f"LLM extraction error: {str(e)}", exc_info=True)
         await redis.hset(f"task:{task_id}", mapping={
@@ -187,6 +225,16 @@ async def process_llm_extraction(
             "error": str(e)
         })
 
+        # Send webhook notification on failure
+        await webhook_service.notify_job_completion(
+            task_id=task_id,
+            task_type="llm_extraction",
+            status="failed",
+            urls=[url],
+            webhook_config=webhook_config,
+            error=str(e)
+        )
+
 async def handle_markdown_request(
     url: str,
     filter_type: FilterType,
@@ -275,6 +323,7 @@ async def handle_llm_request(
     cache: str = "0",
     config: Optional[dict] = None,
     provider: Optional[str] = None,
+    webhook_config: Optional[Dict] = None,
     temperature: Optional[float] = None,
     api_base_url: Optional[str] = None
 ) -> JSONResponse:
@@ -308,6 +357,7 @@ async def handle_llm_request(
             base_url,
             config,
             provider,
+            webhook_config,
             temperature,
             api_base_url
         )
@@ -355,6 +405,7 @@ async def create_new_task(
     base_url: str,
     config: dict,
     provider: Optional[str] = None,
+    webhook_config: Optional[Dict] = None,
     temperature: Optional[float] = None,
     api_base_url: Optional[str] = None
 ) -> JSONResponse:
@@ -365,12 +416,18 @@ async def create_new_task(
 
     from datetime import datetime
     task_id = f"llm_{int(datetime.now().timestamp())}_{id(background_tasks)}"
-    
+
-    await redis.hset(f"task:{task_id}", mapping={
+    task_data = {
         "status": TaskStatus.PROCESSING,
         "created_at": datetime.now().isoformat(),
         "url": decoded_url
-    })
+    }
+
+    # Store webhook config if provided
+    if webhook_config:
+        task_data["webhook_config"] = json.dumps(webhook_config)
+
+    await redis.hset(f"task:{task_id}", mapping=task_data)
 
     background_tasks.add_task(
         process_llm_extraction,
@@ -382,6 +439,7 @@ async def create_new_task(
         schema,
         cache,
         provider,
+        webhook_config,
         temperature,
         api_base_url
     )
@@ -723,6 +781,7 @@ async def handle_crawl_job(
     browser_config: Dict,
     crawler_config: Dict,
     config: Dict,
+    webhook_config: Optional[Dict] = None,
 ) -> Dict:
     """
     Fire-and-forget version of handle_crawl_request.
@@ -730,13 +789,24 @@ async def handle_crawl_job(
     lets /crawl/job/{task_id} polling fetch the result.
     """
     task_id = f"crawl_{uuid4().hex[:8]}"
-    await redis.hset(f"task:{task_id}", mapping={
+
+    # Store task data in Redis
+    task_data = {
         "status": TaskStatus.PROCESSING,         # <-- keep enum values consistent
         "created_at": datetime.now(timezone.utc).replace(tzinfo=None).isoformat(),
         "url": json.dumps(urls),                 # store list as JSON string
         "result": "",
         "error": "",
-    })
+    }
+
+    # Store webhook config if provided
+    if webhook_config:
+        task_data["webhook_config"] = json.dumps(webhook_config)
+
+    await redis.hset(f"task:{task_id}", mapping=task_data)
+
+    # Initialize webhook service
+    webhook_service = WebhookDeliveryService(config)
 
     async def _runner():
         try:
@@ -750,6 +820,17 @@ async def handle_crawl_job(
                 "status": TaskStatus.COMPLETED,
                 "result": json.dumps(result),
             })
+
+            # Send webhook notification on successful completion
+            await webhook_service.notify_job_completion(
+                task_id=task_id,
+                task_type="crawl",
+                status="completed",
+                urls=urls,
+                webhook_config=webhook_config,
+                result=result
+            )
+
             await asyncio.sleep(5)  # Give Redis time to process the update
         except Exception as exc:
             await redis.hset(f"task:{task_id}", mapping={
@@ -757,5 +838,15 @@ async def handle_crawl_job(
                 "error": str(exc),
             })
 
+            # Send webhook notification on failure
+            await webhook_service.notify_job_completion(
+                task_id=task_id,
+                task_type="crawl",
+                status="failed",
+                urls=urls,
+                webhook_config=webhook_config,
+                error=str(exc)
+            )
+
     background_tasks.add_task(_runner)
     return {"task_id": task_id}

deploy/docker/config.yml

@@ -87,4 +87,17 @@ observability:
     enabled: True
     endpoint: "/metrics"
   health_check:
-    endpoint: "/health"
+    endpoint: "/health"
+
+# Webhook Configuration
+webhooks:
+  enabled: true
+  default_url: null  # Optional: default webhook URL for all jobs
+  data_in_payload: false  # Optional: default behavior for including data
+  retry:
+    max_attempts: 5
+    initial_delay_ms: 1000  # 1s, 2s, 4s, 8s, 16s exponential backoff
+    max_delay_ms: 32000
+    timeout_ms: 30000  # 30s timeout per webhook call
+  headers:  # Optional: default headers to include
+    User-Agent: "Crawl4AI-Webhook/1.0"

deploy/docker/job.py

@@ -12,6 +12,7 @@ from api import (
     handle_crawl_job,
     handle_task_status,
 )
+from schemas import WebhookConfig
 
 # ------------- dependency placeholders -------------
 _redis = None        # will be injected from server.py
@@ -37,6 +38,7 @@ class LlmJobPayload(BaseModel):
     schema: Optional[str] = None
     cache:  bool = False
     provider: Optional[str] = None
+    webhook_config: Optional[WebhookConfig] = None
     temperature: Optional[float] = None
     base_url: Optional[str] = None
 
@@ -45,6 +47,7 @@ class CrawlJobPayload(BaseModel):
     urls:           list[HttpUrl]
     browser_config: Dict = {}
     crawler_config: Dict = {}
+    webhook_config: Optional[WebhookConfig] = None
 
 
 # ---------- LL​M job ---------------------------------------------------------
@@ -55,6 +58,10 @@ async def llm_job_enqueue(
         request: Request,
         _td: Dict = Depends(lambda: _token_dep()),   # late-bound dep
 ):
+    webhook_config = None
+    if payload.webhook_config:
+        webhook_config = payload.webhook_config.model_dump(mode='json')
+
     return await handle_llm_request(
         _redis,
         background_tasks,
@@ -65,6 +72,7 @@ async def llm_job_enqueue(
         cache=payload.cache,
         config=_config,
         provider=payload.provider,
+        webhook_config=webhook_config,
         temperature=payload.temperature,
         api_base_url=payload.base_url,
     )
@@ -86,6 +94,10 @@ async def crawl_job_enqueue(
         background_tasks: BackgroundTasks,
         _td: Dict = Depends(lambda: _token_dep()),
 ):
+    webhook_config = None
+    if payload.webhook_config:
+        webhook_config = payload.webhook_config.model_dump(mode='json')
+
     return await handle_crawl_job(
         _redis,
         background_tasks,
@@ -93,6 +105,7 @@ async def crawl_job_enqueue(
         payload.browser_config,
         payload.crawler_config,
         config=_config,
+        webhook_config=webhook_config,
     )
 
 

deploy/docker/requirements.txt

@@ -12,6 +12,6 @@ pydantic>=2.11
 rank-bm25==0.2.2
 anyio==4.9.0
 PyJWT==2.10.1
-mcp>=1.6.0
+mcp>=1.18.0
 websockets>=15.0.1
 httpx[http2]>=0.27.2

deploy/docker/schemas.py

@@ -1,6 +1,6 @@
 from typing import List, Optional, Dict
 from enum import Enum
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, HttpUrl
 from utils import FilterType
 
 
@@ -85,4 +85,22 @@ class JSEndpointRequest(BaseModel):
     scripts: List[str] = Field(
         ...,
         description="List of separated JavaScript snippets to execute"
-    )
+    )
+
+
+class WebhookConfig(BaseModel):
+    """Configuration for webhook notifications."""
+    webhook_url: HttpUrl
+    webhook_data_in_payload: bool = False
+    webhook_headers: Optional[Dict[str, str]] = None
+
+
+class WebhookPayload(BaseModel):
+    """Payload sent to webhook endpoints."""
+    task_id: str
+    task_type: str  # "crawl", "llm_extraction", etc.
+    status: str  # "completed" or "failed"
+    timestamp: str  # ISO 8601 format
+    urls: List[str]
+    error: Optional[str] = None
+    data: Optional[Dict] = None  # Included only if webhook_data_in_payload=True

deploy/docker/webhook.py

@@ -0,0 +1,159 @@
+"""
+Webhook delivery service for Crawl4AI.
+
+This module provides webhook notification functionality with exponential backoff retry logic.
+"""
+import asyncio
+import httpx
+import logging
+from typing import Dict, Optional
+from datetime import datetime, timezone
+
+logger = logging.getLogger(__name__)
+
+
+class WebhookDeliveryService:
+    """Handles webhook delivery with exponential backoff retry logic."""
+
+    def __init__(self, config: Dict):
+        """
+        Initialize the webhook delivery service.
+
+        Args:
+            config: Application configuration dictionary containing webhook settings
+        """
+        self.config = config.get("webhooks", {})
+        self.max_attempts = self.config.get("retry", {}).get("max_attempts", 5)
+        self.initial_delay = self.config.get("retry", {}).get("initial_delay_ms", 1000) / 1000
+        self.max_delay = self.config.get("retry", {}).get("max_delay_ms", 32000) / 1000
+        self.timeout = self.config.get("retry", {}).get("timeout_ms", 30000) / 1000
+
+    async def send_webhook(
+        self,
+        webhook_url: str,
+        payload: Dict,
+        headers: Optional[Dict[str, str]] = None
+    ) -> bool:
+        """
+        Send webhook with exponential backoff retry logic.
+
+        Args:
+            webhook_url: The URL to send the webhook to
+            payload: The JSON payload to send
+            headers: Optional custom headers
+
+        Returns:
+            bool: True if delivered successfully, False otherwise
+        """
+        default_headers = self.config.get("headers", {})
+        merged_headers = {**default_headers, **(headers or {})}
+        merged_headers["Content-Type"] = "application/json"
+
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            for attempt in range(self.max_attempts):
+                try:
+                    logger.info(
+                        f"Sending webhook (attempt {attempt + 1}/{self.max_attempts}) to {webhook_url}"
+                    )
+
+                    response = await client.post(
+                        webhook_url,
+                        json=payload,
+                        headers=merged_headers
+                    )
+
+                    # Success or client error (don't retry client errors)
+                    if response.status_code < 500:
+                        if 200 <= response.status_code < 300:
+                            logger.info(f"Webhook delivered successfully to {webhook_url}")
+                            return True
+                        else:
+                            logger.warning(
+                                f"Webhook rejected with status {response.status_code}: {response.text[:200]}"
+                            )
+                            return False  # Client error - don't retry
+
+                    # Server error - retry with backoff
+                    logger.warning(
+                        f"Webhook failed with status {response.status_code}, will retry"
+                    )
+
+                except httpx.TimeoutException as exc:
+                    logger.error(f"Webhook timeout (attempt {attempt + 1}): {exc}")
+                except httpx.RequestError as exc:
+                    logger.error(f"Webhook request error (attempt {attempt + 1}): {exc}")
+                except Exception as exc:
+                    logger.error(f"Webhook delivery error (attempt {attempt + 1}): {exc}")
+
+                # Calculate exponential backoff delay
+                if attempt < self.max_attempts - 1:
+                    delay = min(self.initial_delay * (2 ** attempt), self.max_delay)
+                    logger.info(f"Retrying in {delay}s...")
+                    await asyncio.sleep(delay)
+
+        logger.error(
+            f"Webhook delivery failed after {self.max_attempts} attempts to {webhook_url}"
+        )
+        return False
+
+    async def notify_job_completion(
+        self,
+        task_id: str,
+        task_type: str,
+        status: str,
+        urls: list,
+        webhook_config: Optional[Dict],
+        result: Optional[Dict] = None,
+        error: Optional[str] = None
+    ):
+        """
+        Notify webhook of job completion.
+
+        Args:
+            task_id: The task identifier
+            task_type: Type of task (e.g., "crawl", "llm_extraction")
+            status: Task status ("completed" or "failed")
+            urls: List of URLs that were crawled
+            webhook_config: Webhook configuration from the job request
+            result: Optional crawl result data
+            error: Optional error message if failed
+        """
+        # Determine webhook URL
+        webhook_url = None
+        data_in_payload = self.config.get("data_in_payload", False)
+        custom_headers = None
+
+        if webhook_config:
+            webhook_url = webhook_config.get("webhook_url")
+            data_in_payload = webhook_config.get("webhook_data_in_payload", data_in_payload)
+            custom_headers = webhook_config.get("webhook_headers")
+
+        if not webhook_url:
+            webhook_url = self.config.get("default_url")
+
+        if not webhook_url:
+            logger.debug("No webhook URL configured, skipping notification")
+            return
+
+        # Check if webhooks are enabled
+        if not self.config.get("enabled", True):
+            logger.debug("Webhooks are disabled, skipping notification")
+            return
+
+        # Build payload
+        payload = {
+            "task_id": task_id,
+            "task_type": task_type,
+            "status": status,
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "urls": urls
+        }
+
+        if error:
+            payload["error"] = error
+
+        if data_in_payload and result:
+            payload["data"] = result
+
+        # Send webhook (fire and forget - don't block on completion)
+        await self.send_webhook(webhook_url, payload, custom_headers)

docs/blog/release-v0.7.4.md

@@ -10,7 +10,6 @@ Today I'm releasing Crawl4AI v0.7.4—the Intelligent Table Extraction & Perform
 
 - **🚀 LLMTableExtraction**: Revolutionary table extraction with intelligent chunking for massive tables
 - **⚡ Enhanced Concurrency**: True concurrency improvements for fast-completing tasks in batch operations
-- **🧹 Memory Management Refactor**: Streamlined memory utilities and better resource management
 - **🔧 Browser Manager Fixes**: Resolved race conditions in concurrent page creation
 - **⌨️ Cross-Platform Browser Profiler**: Improved keyboard handling and quit mechanisms
 - **🔗 Advanced URL Processing**: Better handling of raw URLs and base tag link resolution
@@ -158,40 +157,6 @@ async with AsyncWebCrawler() as crawler:
 - **Monitoring Systems**: Faster health checks and status page monitoring
 - **Data Aggregation**: Improved performance for real-time data collection
 
-## 🧹 Memory Management Refactor: Cleaner Architecture
-
-**The Problem:** Memory utilities were scattered and difficult to maintain, with potential import conflicts and unclear organization.
-
-**My Solution:** I consolidated all memory-related utilities into the main `utils.py` module, creating a cleaner, more maintainable architecture.
-
-### Improved Memory Handling
-
-```python
-# All memory utilities now consolidated
-from crawl4ai.utils import get_true_memory_usage_percent, MemoryMonitor
-
-# Enhanced memory monitoring
-monitor = MemoryMonitor()
-monitor.start_monitoring()
-
-async with AsyncWebCrawler() as crawler:
-    # Memory-efficient batch processing
-    results = await crawler.arun_many(large_url_list)
-    
-    # Get accurate memory metrics
-    memory_usage = get_true_memory_usage_percent()
-    memory_report = monitor.get_report()
-    
-    print(f"Memory efficiency: {memory_report['efficiency']:.1f}%")
-    print(f"Peak usage: {memory_report['peak_mb']:.1f} MB")
-```
-
-**Expected Real-World Impact:**
-- **Production Stability**: More reliable memory tracking and management
-- **Code Maintainability**: Cleaner architecture for easier debugging
-- **Import Clarity**: Resolved potential conflicts and import issues
-- **Developer Experience**: Simpler API for memory monitoring
-
 ## 🔧 Critical Stability Fixes
 
 ### Browser Manager Race Condition Resolution

docs/blog/release-v0.7.5.md

@@ -0,0 +1,318 @@
+# 🚀 Crawl4AI v0.7.5: The Docker Hooks & Security Update
+
+*September 29, 2025 • 8 min read*
+
+---
+
+Today I'm releasing Crawl4AI v0.7.5—focused on extensibility and security. This update introduces the Docker Hooks System for pipeline customization, enhanced LLM integration, and important security improvements.
+
+## 🎯 What's New at a Glance
+
+- **Docker Hooks System**: Custom Python functions at key pipeline points with function-based API
+- **Function-Based Hooks**: New `hooks_to_string()` utility with Docker client auto-conversion
+- **Enhanced LLM Integration**: Custom providers with temperature control
+- **HTTPS Preservation**: Secure internal link handling
+- **Bug Fixes**: Resolved multiple community-reported issues
+- **Improved Docker Error Handling**: Better debugging and reliability
+
+## 🔧 Docker Hooks System: Pipeline Customization
+
+Every scraping project needs custom logic—authentication, performance optimization, content processing. Traditional solutions require forking or complex workarounds. Docker Hooks let you inject custom Python functions at 8 key points in the crawling pipeline.
+
+### Real Example: Authentication & Performance
+
+```python
+import requests
+
+# Real working hooks for httpbin.org
+hooks_config = {
+    "on_page_context_created": """
+async def hook(page, context, **kwargs):
+    print("Hook: Setting up page context")
+    # Block images to speed up crawling
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    print("Hook: Images blocked")
+    return page
+""",
+
+    "before_retrieve_html": """
+async def hook(page, context, **kwargs):
+    print("Hook: Before retrieving HTML")
+    # Scroll to bottom to load lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    print("Hook: Scrolled to bottom")
+    return page
+""",
+
+    "before_goto": """
+async def hook(page, context, url, **kwargs):
+    print(f"Hook: About to navigate to {url}")
+    # Add custom headers
+    await page.set_extra_http_headers({
+        'X-Test-Header': 'crawl4ai-hooks-test'
+    })
+    return page
+"""
+}
+
+# Test with Docker API
+payload = {
+    "urls": ["https://httpbin.org/html"],
+    "hooks": {
+        "code": hooks_config,
+        "timeout": 30
+    }
+}
+
+response = requests.post("http://localhost:11235/crawl", json=payload)
+result = response.json()
+
+if result.get('success'):
+    print("✅ Hooks executed successfully!")
+    print(f"Content length: {len(result.get('markdown', ''))} characters")
+```
+
+**Available Hook Points:**
+- `on_browser_created`: Browser setup
+- `on_page_context_created`: Page context configuration
+- `before_goto`: Pre-navigation setup
+- `after_goto`: Post-navigation processing
+- `on_user_agent_updated`: User agent changes
+- `on_execution_started`: Crawl initialization
+- `before_retrieve_html`: Pre-extraction processing
+- `before_return_html`: Final HTML processing
+
+### Function-Based Hooks API
+
+Writing hooks as strings works, but lacks IDE support and type checking. v0.7.5 introduces a function-based approach with automatic conversion!
+
+**Option 1: Using the `hooks_to_string()` Utility**
+
+```python
+from crawl4ai import hooks_to_string
+import requests
+
+# Define hooks as regular Python functions (with full IDE support!)
+async def on_page_context_created(page, context, **kwargs):
+    """Block images to speed up crawling"""
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+
+async def before_goto(page, context, url, **kwargs):
+    """Add custom headers"""
+    await page.set_extra_http_headers({
+        'X-Crawl4AI': 'v0.7.5',
+        'X-Custom-Header': 'my-value'
+    })
+    return page
+
+# Convert functions to strings
+hooks_code = hooks_to_string({
+    "on_page_context_created": on_page_context_created,
+    "before_goto": before_goto
+})
+
+# Use with REST API
+payload = {
+    "urls": ["https://httpbin.org/html"],
+    "hooks": {"code": hooks_code, "timeout": 30}
+}
+response = requests.post("http://localhost:11235/crawl", json=payload)
+```
+
+**Option 2: Docker Client with Automatic Conversion (Recommended!)**
+
+```python
+from crawl4ai.docker_client import Crawl4aiDockerClient
+
+# Define hooks as functions (same as above)
+async def on_page_context_created(page, context, **kwargs):
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    return page
+
+async def before_retrieve_html(page, context, **kwargs):
+    # Scroll to load lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    return page
+
+# Use Docker client - conversion happens automatically!
+client = Crawl4aiDockerClient(base_url="http://localhost:11235")
+
+results = await client.crawl(
+    urls=["https://httpbin.org/html"],
+    hooks={
+        "on_page_context_created": on_page_context_created,
+        "before_retrieve_html": before_retrieve_html
+    },
+    hooks_timeout=30
+)
+
+if results and results.success:
+    print(f"✅ Hooks executed! HTML length: {len(results.html)}")
+```
+
+**Benefits of Function-Based Hooks:**
+- ✅ Full IDE support (autocomplete, syntax highlighting)
+- ✅ Type checking and linting
+- ✅ Easier to test and debug
+- ✅ Reusable across projects
+- ✅ Automatic conversion in Docker client
+- ✅ No breaking changes - string hooks still work!
+
+## 🤖 Enhanced LLM Integration
+
+Enhanced LLM integration with custom providers, temperature control, and base URL configuration.
+
+### Multi-Provider Support
+
+```python
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
+from crawl4ai.extraction_strategy import LLMExtractionStrategy
+
+# Test with different providers
+async def test_llm_providers():
+    # OpenAI with custom temperature
+    openai_strategy = LLMExtractionStrategy(
+        provider="gemini/gemini-2.5-flash-lite",
+        api_token="your-api-token",
+        temperature=0.7,  # New in v0.7.5
+        instruction="Summarize this page in one sentence"
+    )
+
+    async with AsyncWebCrawler() as crawler:
+        result = await crawler.arun(
+            "https://example.com",
+            config=CrawlerRunConfig(extraction_strategy=openai_strategy)
+        )
+
+        if result.success:
+            print("✅ LLM extraction completed")
+            print(result.extracted_content)
+
+# Docker API with enhanced LLM config
+llm_payload = {
+    "url": "https://example.com",
+    "f": "llm",
+    "q": "Summarize this page in one sentence.",
+    "provider": "gemini/gemini-2.5-flash-lite",
+    "temperature": 0.7
+}
+
+response = requests.post("http://localhost:11235/md", json=llm_payload)
+```
+
+**New Features:**
+- Custom `temperature` parameter for creativity control
+- `base_url` for custom API endpoints
+- Multi-provider environment variable support
+- Docker API integration
+
+## 🔒 HTTPS Preservation
+
+**The Problem:** Modern web apps require HTTPS everywhere. When crawlers downgrade internal links from HTTPS to HTTP, authentication breaks and security warnings appear.
+
+**Solution:** HTTPS preservation maintains secure protocols throughout crawling.
+
+```python
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, FilterChain, URLPatternFilter, BFSDeepCrawlStrategy
+
+async def test_https_preservation():
+    # Enable HTTPS preservation
+    url_filter = URLPatternFilter(
+        patterns=["^(https:\/\/)?quotes\.toscrape\.com(\/.*)?$"]
+    )
+
+    config = CrawlerRunConfig(
+        exclude_external_links=True,
+        preserve_https_for_internal_links=True,  # New in v0.7.5
+        deep_crawl_strategy=BFSDeepCrawlStrategy(
+            max_depth=2,
+            max_pages=5,
+            filter_chain=FilterChain([url_filter])
+        )
+    )
+
+    async with AsyncWebCrawler() as crawler:
+        async for result in await crawler.arun(
+            url="https://quotes.toscrape.com",
+            config=config
+        ):
+            # All internal links maintain HTTPS
+            internal_links = [link['href'] for link in result.links['internal']]
+            https_links = [link for link in internal_links if link.startswith('https://')]
+
+            print(f"HTTPS links preserved: {len(https_links)}/{len(internal_links)}")
+            for link in https_links[:3]:
+                print(f"  → {link}")
+```
+
+## 🛠️ Bug Fixes and Improvements
+
+### Major Fixes
+- **URL Processing**: Fixed '+' sign preservation in query parameters (#1332)
+- **Proxy Configuration**: Enhanced proxy string parsing (old `proxy` parameter deprecated)
+- **Docker Error Handling**: Comprehensive error messages with status codes
+- **Memory Management**: Fixed leaks in long-running sessions
+- **JWT Authentication**: Fixed Docker JWT validation issues (#1442)
+- **Playwright Stealth**: Fixed stealth features for Playwright integration (#1481)
+- **API Configuration**: Fixed config handling to prevent overriding user-provided settings (#1505)
+- **Docker Filter Serialization**: Resolved JSON encoding errors in deep crawl strategy (#1419)
+- **LLM Provider Support**: Fixed custom LLM provider integration for adaptive crawler (#1291)
+- **Performance Issues**: Resolved backoff strategy failures and timeout handling (#989)
+
+### Community-Reported Issues Fixed
+This release addresses multiple issues reported by the community through GitHub issues and Discord discussions:
+- Fixed browser configuration reference errors
+- Resolved dependency conflicts with cssselect
+- Improved error messaging for failed authentications
+- Enhanced compatibility with various proxy configurations
+- Fixed edge cases in URL normalization
+
+### Configuration Updates
+```python
+# Old proxy config (deprecated)
+# browser_config = BrowserConfig(proxy="http://proxy:8080")
+
+# New enhanced proxy config
+browser_config = BrowserConfig(
+    proxy_config={
+        "server": "http://proxy:8080",
+        "username": "optional-user",
+        "password": "optional-pass"
+    }
+)
+```
+
+## 🔄 Breaking Changes
+
+1. **Python 3.10+ Required**: Upgrade from Python 3.9
+2. **Proxy Parameter Deprecated**: Use new `proxy_config` structure
+3. **New Dependency**: Added `cssselect` for better CSS handling
+
+## 🚀 Get Started
+
+```bash
+# Install latest version
+pip install crawl4ai==0.7.5
+
+# Docker deployment
+docker pull unclecode/crawl4ai:latest
+docker run -p 11235:11235 unclecode/crawl4ai:latest
+```
+
+**Try the Demo:**
+```bash
+# Run working examples
+python docs/releases_review/demo_v0.7.5.py
+```
+
+**Resources:**
+- 📖 Documentation: [docs.crawl4ai.com](https://docs.crawl4ai.com)
+- 🐙 GitHub: [github.com/unclecode/crawl4ai](https://github.com/unclecode/crawl4ai)
+- 💬 Discord: [discord.gg/crawl4ai](https://discord.gg/jP8KfhDhyN)
+- 🐦 Twitter: [@unclecode](https://x.com/unclecode)
+
+Happy crawling! 🕷️

docs/blog/release-v0.7.6.md

@@ -0,0 +1,314 @@
+# Crawl4AI v0.7.6 Release Notes
+
+*Release Date: October 22, 2025*
+
+I'm excited to announce Crawl4AI v0.7.6, featuring a complete webhook infrastructure for the Docker job queue API! This release eliminates polling and brings real-time notifications to both crawling and LLM extraction workflows.
+
+## 🎯 What's New
+
+### Webhook Support for Docker Job Queue API
+
+The headline feature of v0.7.6 is comprehensive webhook support for asynchronous job processing. No more constant polling to check if your jobs are done - get instant notifications when they complete!
+
+**Key Capabilities:**
+
+- ✅ **Universal Webhook Support**: Both `/crawl/job` and `/llm/job` endpoints now support webhooks
+- ✅ **Flexible Delivery Modes**: Choose notification-only or include full data in the webhook payload
+- ✅ **Reliable Delivery**: Exponential backoff retry mechanism (5 attempts: 1s → 2s → 4s → 8s → 16s)
+- ✅ **Custom Authentication**: Add custom headers for webhook authentication
+- ✅ **Global Configuration**: Set default webhook URL in `config.yml` for all jobs
+- ✅ **Task Type Identification**: Distinguish between `crawl` and `llm_extraction` tasks
+
+### How It Works
+
+Instead of constantly checking job status:
+
+**OLD WAY (Polling):**
+```python
+# Submit job
+response = requests.post("http://localhost:11235/crawl/job", json=payload)
+task_id = response.json()['task_id']
+
+# Poll until complete
+while True:
+    status = requests.get(f"http://localhost:11235/crawl/job/{task_id}")
+    if status.json()['status'] == 'completed':
+        break
+    time.sleep(5)  # Wait and try again
+```
+
+**NEW WAY (Webhooks):**
+```python
+# Submit job with webhook
+payload = {
+    "urls": ["https://example.com"],
+    "webhook_config": {
+        "webhook_url": "https://myapp.com/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+response = requests.post("http://localhost:11235/crawl/job", json=payload)
+
+# Done! Webhook will notify you when complete
+# Your webhook handler receives the results automatically
+```
+
+### Crawl Job Webhooks
+
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "browser_config": {"headless": true},
+    "crawler_config": {"cache_mode": "bypass"},
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": false,
+      "webhook_headers": {
+        "X-Webhook-Secret": "your-secret-token"
+      }
+    }
+  }'
+```
+
+### LLM Extraction Job Webhooks (NEW!)
+
+```bash
+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 publication date",
+    "schema": "{\"type\":\"object\",\"properties\":{\"title\":{\"type\":\"string\"}}}",
+    "provider": "openai/gpt-4o-mini",
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/llm-complete",
+      "webhook_data_in_payload": true
+    }
+  }'
+```
+
+### Webhook Payload Structure
+
+**Success (with data):**
+```json
+{
+  "task_id": "llm_1698765432",
+  "task_type": "llm_extraction",
+  "status": "completed",
+  "timestamp": "2025-10-22T10:30:00.000000+00:00",
+  "urls": ["https://example.com/article"],
+  "data": {
+    "extracted_content": {
+      "title": "Understanding Web Scraping",
+      "author": "John Doe",
+      "date": "2025-10-22"
+    }
+  }
+}
+```
+
+**Failure:**
+```json
+{
+  "task_id": "crawl_abc123",
+  "task_type": "crawl",
+  "status": "failed",
+  "timestamp": "2025-10-22T10:30:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "error": "Connection timeout after 30s"
+}
+```
+
+### Simple Webhook Handler Example
+
+```python
+from flask import Flask, request, jsonify
+
+app = Flask(__name__)
+
+@app.route('/webhook', methods=['POST'])
+def handle_webhook():
+    payload = request.json
+
+    task_id = payload['task_id']
+    task_type = payload['task_type']
+    status = payload['status']
+
+    if status == 'completed':
+        if 'data' in payload:
+            # Process data directly
+            data = payload['data']
+        else:
+            # Fetch from API
+            endpoint = 'crawl' if task_type == 'crawl' else 'llm'
+            response = requests.get(f'http://localhost:11235/{endpoint}/job/{task_id}')
+            data = response.json()
+
+        # Your business logic here
+        print(f"Job {task_id} completed!")
+
+    elif status == 'failed':
+        error = payload.get('error', 'Unknown error')
+        print(f"Job {task_id} failed: {error}")
+
+    return jsonify({"status": "received"}), 200
+
+app.run(port=8080)
+```
+
+## 📊 Performance Improvements
+
+- **Reduced Server Load**: Eliminates constant polling requests
+- **Lower Latency**: Instant notification vs. polling interval delay
+- **Better Resource Usage**: Frees up client connections while jobs run in background
+- **Scalable Architecture**: Handles high-volume crawling workflows efficiently
+
+## 🐛 Bug Fixes
+
+- Fixed webhook configuration serialization for Pydantic HttpUrl fields
+- Improved error handling in webhook delivery service
+- Enhanced Redis task storage for webhook config persistence
+
+## 🌍 Expected Real-World Impact
+
+### For Web Scraping Workflows
+- **Reduced Costs**: Less API calls = lower bandwidth and server costs
+- **Better UX**: Instant notifications improve user experience
+- **Scalability**: Handle 100s of concurrent jobs without polling overhead
+
+### For LLM Extraction Pipelines
+- **Async Processing**: Submit LLM extraction jobs and move on
+- **Batch Processing**: Queue multiple extractions, get notified as they complete
+- **Integration**: Easy integration with workflow automation tools (Zapier, n8n, etc.)
+
+### For Microservices
+- **Event-Driven**: Perfect for event-driven microservice architectures
+- **Decoupling**: Decouple job submission from result processing
+- **Reliability**: Automatic retries ensure webhooks are delivered
+
+## 🔄 Breaking Changes
+
+**None!** This release is fully backward compatible.
+
+- Webhook configuration is optional
+- Existing code continues to work without modification
+- Polling is still supported for jobs without webhook config
+
+## 📚 Documentation
+
+### New Documentation
+- **[WEBHOOK_EXAMPLES.md](../deploy/docker/WEBHOOK_EXAMPLES.md)** - Comprehensive webhook usage guide
+- **[docker_webhook_example.py](../docs/examples/docker_webhook_example.py)** - Working code examples
+
+### Updated Documentation
+- **[Docker README](../deploy/docker/README.md)** - Added webhook sections
+- API documentation with webhook examples
+
+## 🛠️ Migration Guide
+
+No migration needed! Webhooks are opt-in:
+
+1. **To use webhooks**: Add `webhook_config` to your job payload
+2. **To keep polling**: Continue using your existing code
+
+### Quick Start
+
+```python
+# Just add webhook_config to your existing payload
+payload = {
+    # Your existing configuration
+    "urls": ["https://example.com"],
+    "browser_config": {...},
+    "crawler_config": {...},
+
+    # NEW: Add webhook configuration
+    "webhook_config": {
+        "webhook_url": "https://myapp.com/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+```
+
+## 🔧 Configuration
+
+### Global Webhook Configuration (config.yml)
+
+```yaml
+webhooks:
+  enabled: true
+  default_url: "https://myapp.com/webhooks/default"  # Optional
+  data_in_payload: false
+  retry:
+    max_attempts: 5
+    initial_delay_ms: 1000
+    max_delay_ms: 32000
+    timeout_ms: 30000
+  headers:
+    User-Agent: "Crawl4AI-Webhook/1.0"
+```
+
+## 🚀 Upgrade Instructions
+
+### Docker
+
+```bash
+# Pull the latest image
+docker pull unclecode/crawl4ai:0.7.6
+
+# Or use latest tag
+docker pull unclecode/crawl4ai:latest
+
+# Run with webhook support
+docker run -d \
+  -p 11235:11235 \
+  --env-file .llm.env \
+  --name crawl4ai \
+  unclecode/crawl4ai:0.7.6
+```
+
+### Python Package
+
+```bash
+pip install --upgrade crawl4ai
+```
+
+## 💡 Pro Tips
+
+1. **Use notification-only mode** for large results - fetch data separately to avoid large webhook payloads
+2. **Set custom headers** for webhook authentication and request tracking
+3. **Configure global default webhook** for consistent handling across all jobs
+4. **Implement idempotent webhook handlers** - same webhook may be delivered multiple times on retry
+5. **Use structured schemas** with LLM extraction for predictable webhook data
+
+## 🎬 Demo
+
+Try the release demo:
+
+```bash
+python docs/releases_review/demo_v0.7.6.py
+```
+
+This comprehensive demo showcases:
+- Crawl job webhooks (notification-only and with data)
+- LLM extraction webhooks (with JSON schema support)
+- Custom headers for authentication
+- Webhook retry mechanism
+- Real-time webhook receiver
+
+## 🙏 Acknowledgments
+
+Thank you to the community for the feedback that shaped this feature! Special thanks to everyone who requested webhook support for asynchronous job processing.
+
+## 📞 Support
+
+- **Documentation**: https://docs.crawl4ai.com
+- **GitHub Issues**: https://github.com/unclecode/crawl4ai/issues
+- **Discord**: https://discord.gg/crawl4ai
+
+---
+
+**Happy crawling with webhooks!** 🕷️🪝
+
+*- unclecode*

docs/examples/docker_client_hooks_example.py

@@ -0,0 +1,522 @@
+#!/usr/bin/env python3
+"""
+Comprehensive hooks examples using Docker Client with function objects.
+
+This approach is recommended because:
+- Write hooks as regular Python functions
+- Full IDE support (autocomplete, type checking)
+- Automatic conversion to API format
+- Reusable and testable code
+- Clean, readable syntax
+"""
+
+import asyncio
+from crawl4ai import Crawl4aiDockerClient
+
+# API_BASE_URL = "http://localhost:11235"
+API_BASE_URL = "http://localhost:11234"
+
+
+# ============================================================================
+# Hook Function Definitions
+# ============================================================================
+
+# --- All Hooks Demo ---
+async def browser_created_hook(browser, **kwargs):
+    """Called after browser is created"""
+    print("[HOOK] Browser created and ready")
+    return browser
+
+
+async def page_context_hook(page, context, **kwargs):
+    """Setup page environment"""
+    print("[HOOK] Setting up page environment")
+
+    # Set viewport
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+
+    # Add cookies
+    await context.add_cookies([{
+        "name": "test_session",
+        "value": "abc123xyz",
+        "domain": ".httpbin.org",
+        "path": "/"
+    }])
+
+    # Block resources
+    await context.route("**/*.{png,jpg,jpeg,gif}", lambda route: route.abort())
+    await context.route("**/analytics/*", lambda route: route.abort())
+
+    print("[HOOK] Environment configured")
+    return page
+
+
+async def user_agent_hook(page, context, user_agent, **kwargs):
+    """Called when user agent is updated"""
+    print(f"[HOOK] User agent: {user_agent[:50]}...")
+    return page
+
+
+async def before_goto_hook(page, context, url, **kwargs):
+    """Called before navigating to URL"""
+    print(f"[HOOK] Navigating to: {url}")
+
+    await page.set_extra_http_headers({
+        "X-Custom-Header": "crawl4ai-test",
+        "Accept-Language": "en-US"
+    })
+
+    return page
+
+
+async def after_goto_hook(page, context, url, response, **kwargs):
+    """Called after page loads"""
+    print(f"[HOOK] Page loaded: {url}")
+
+    await page.wait_for_timeout(1000)
+
+    try:
+        await page.wait_for_selector("body", timeout=2000)
+        print("[HOOK] Body element ready")
+    except:
+        print("[HOOK] Timeout, continuing")
+
+    return page
+
+
+async def execution_started_hook(page, context, **kwargs):
+    """Called when custom JS execution starts"""
+    print("[HOOK] JS execution started")
+    await page.evaluate("console.log('[HOOK] Custom JS');")
+    return page
+
+
+async def before_retrieve_hook(page, context, **kwargs):
+    """Called before retrieving HTML"""
+    print("[HOOK] Preparing HTML retrieval")
+
+    # Scroll for lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight);")
+    await page.wait_for_timeout(500)
+    await page.evaluate("window.scrollTo(0, 0);")
+
+    print("[HOOK] Scrolling complete")
+    return page
+
+
+async def before_return_hook(page, context, html, **kwargs):
+    """Called before returning HTML"""
+    print(f"[HOOK] HTML ready: {len(html)} chars")
+
+    metrics = await page.evaluate('''() => ({
+        images: document.images.length,
+        links: document.links.length,
+        scripts: document.scripts.length
+    })''')
+
+    print(f"[HOOK] Metrics - Images: {metrics['images']}, Links: {metrics['links']}")
+    return page
+
+
+# --- Authentication Hooks ---
+async def auth_context_hook(page, context, **kwargs):
+    """Setup authentication context"""
+    print("[HOOK] Setting up authentication")
+
+    # Add auth cookies
+    await context.add_cookies([{
+        "name": "auth_token",
+        "value": "fake_jwt_token",
+        "domain": ".httpbin.org",
+        "path": "/",
+        "httpOnly": True
+    }])
+
+    # Set localStorage
+    await page.evaluate('''
+        localStorage.setItem('user_id', '12345');
+        localStorage.setItem('auth_time', new Date().toISOString());
+    ''')
+
+    print("[HOOK] Auth context ready")
+    return page
+
+
+async def auth_headers_hook(page, context, url, **kwargs):
+    """Add authentication headers"""
+    print(f"[HOOK] Adding auth headers for {url}")
+
+    import base64
+    credentials = base64.b64encode(b"user:passwd").decode('ascii')
+
+    await page.set_extra_http_headers({
+        'Authorization': f'Basic {credentials}',
+        'X-API-Key': 'test-key-123'
+    })
+
+    return page
+
+
+# --- Performance Optimization Hooks ---
+async def performance_hook(page, context, **kwargs):
+    """Optimize page for performance"""
+    print("[HOOK] Optimizing for performance")
+
+    # Block resource-heavy content
+    await context.route("**/*.{png,jpg,jpeg,gif,webp,svg}", lambda r: r.abort())
+    await context.route("**/*.{woff,woff2,ttf}", lambda r: r.abort())
+    await context.route("**/*.{mp4,webm,ogg}", lambda r: r.abort())
+    await context.route("**/googletagmanager.com/*", lambda r: r.abort())
+    await context.route("**/google-analytics.com/*", lambda r: r.abort())
+    await context.route("**/facebook.com/*", lambda r: r.abort())
+
+    # Disable animations
+    await page.add_style_tag(content='''
+        *, *::before, *::after {
+            animation-duration: 0s !important;
+            transition-duration: 0s !important;
+        }
+    ''')
+
+    print("[HOOK] Optimizations applied")
+    return page
+
+
+async def cleanup_hook(page, context, **kwargs):
+    """Clean page before extraction"""
+    print("[HOOK] Cleaning page")
+
+    await page.evaluate('''() => {
+        const selectors = [
+            '.ad', '.ads', '.advertisement',
+            '.popup', '.modal', '.overlay',
+            '.cookie-banner', '.newsletter'
+        ];
+
+        selectors.forEach(sel => {
+            document.querySelectorAll(sel).forEach(el => el.remove());
+        });
+
+        document.querySelectorAll('script, style').forEach(el => el.remove());
+    }''')
+
+    print("[HOOK] Page cleaned")
+    return page
+
+
+# --- Content Extraction Hooks ---
+async def wait_dynamic_content_hook(page, context, url, response, **kwargs):
+    """Wait for dynamic content to load"""
+    print(f"[HOOK] Waiting for dynamic content on {url}")
+
+    await page.wait_for_timeout(2000)
+
+    # Click "Load More" if exists
+    try:
+        load_more = await page.query_selector('[class*="load-more"], button:has-text("Load More")')
+        if load_more:
+            await load_more.click()
+            await page.wait_for_timeout(1000)
+            print("[HOOK] Clicked 'Load More'")
+    except:
+        pass
+
+    return page
+
+
+async def extract_metadata_hook(page, context, **kwargs):
+    """Extract page metadata"""
+    print("[HOOK] Extracting metadata")
+
+    metadata = await page.evaluate('''() => {
+        const getMeta = (name) => {
+            const el = document.querySelector(`meta[name="${name}"], meta[property="${name}"]`);
+            return el ? el.getAttribute('content') : null;
+        };
+
+        return {
+            title: document.title,
+            description: getMeta('description'),
+            author: getMeta('author'),
+            keywords: getMeta('keywords'),
+        };
+    }''')
+
+    print(f"[HOOK] Metadata: {metadata}")
+
+    # Infinite scroll
+    for i in range(3):
+        await page.evaluate("window.scrollTo(0, document.body.scrollHeight);")
+        await page.wait_for_timeout(1000)
+        print(f"[HOOK] Scroll {i+1}/3")
+
+    return page
+
+
+# --- Multi-URL Hooks ---
+async def url_specific_hook(page, context, url, **kwargs):
+    """Apply URL-specific logic"""
+    print(f"[HOOK] Processing URL: {url}")
+
+    # URL-specific headers
+    if 'html' in url:
+        await page.set_extra_http_headers({"X-Type": "HTML"})
+    elif 'json' in url:
+        await page.set_extra_http_headers({"X-Type": "JSON"})
+
+    return page
+
+
+async def track_progress_hook(page, context, url, response, **kwargs):
+    """Track crawl progress"""
+    status = response.status if response else 'unknown'
+    print(f"[HOOK] Loaded {url} - Status: {status}")
+    return page
+
+
+# ============================================================================
+# Test Functions
+# ============================================================================
+
+async def test_all_hooks_comprehensive():
+    """Test all 8 hook types"""
+    print("=" * 70)
+    print("Test 1: All Hooks Comprehensive Demo (Docker Client)")
+    print("=" * 70)
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nCrawling with all 8 hooks...")
+
+        # Define hooks with function objects
+        hooks = {
+            "on_browser_created": browser_created_hook,
+            "on_page_context_created": page_context_hook,
+            "on_user_agent_updated": user_agent_hook,
+            "before_goto": before_goto_hook,
+            "after_goto": after_goto_hook,
+            "on_execution_started": execution_started_hook,
+            "before_retrieve_html": before_retrieve_hook,
+            "before_return_html": before_return_hook
+        }
+
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            hooks=hooks,
+            hooks_timeout=30
+        )
+
+        print("\n✅ Success!")
+        print(f"   URL: {result.url}")
+        print(f"   Success: {result.success}")
+        print(f"   HTML: {len(result.html)} chars")
+
+
+async def test_authentication_workflow():
+    """Test authentication with hooks"""
+    print("\n" + "=" * 70)
+    print("Test 2: Authentication Workflow (Docker Client)")
+    print("=" * 70)
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nTesting authentication...")
+
+        hooks = {
+            "on_page_context_created": auth_context_hook,
+            "before_goto": auth_headers_hook
+        }
+
+        result = await client.crawl(
+            ["https://httpbin.org/basic-auth/user/passwd"],
+            hooks=hooks,
+            hooks_timeout=15
+        )
+
+        print("\n✅ Authentication completed")
+
+        if result.success:
+            if '"authenticated"' in result.html and 'true' in result.html:
+                print("   ✅ Basic auth successful!")
+            else:
+                print("   ⚠️ Auth status unclear")
+        else:
+            print(f"   ❌ Failed: {result.error_message}")
+
+
+async def test_performance_optimization():
+    """Test performance optimization"""
+    print("\n" + "=" * 70)
+    print("Test 3: Performance Optimization (Docker Client)")
+    print("=" * 70)
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nTesting performance hooks...")
+
+        hooks = {
+            "on_page_context_created": performance_hook,
+            "before_retrieve_html": cleanup_hook
+        }
+
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            hooks=hooks,
+            hooks_timeout=10
+        )
+
+        print("\n✅ Optimization completed")
+        print(f"   HTML size: {len(result.html):,} chars")
+        print("   Resources blocked, ads removed")
+
+
+async def test_content_extraction():
+    """Test content extraction"""
+    print("\n" + "=" * 70)
+    print("Test 4: Content Extraction (Docker Client)")
+    print("=" * 70)
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nTesting extraction hooks...")
+
+        hooks = {
+            "after_goto": wait_dynamic_content_hook,
+            "before_retrieve_html": extract_metadata_hook
+        }
+
+        result = await client.crawl(
+            ["https://www.kidocode.com/"],
+            hooks=hooks,
+            hooks_timeout=20
+        )
+
+        print("\n✅ Extraction completed")
+        print(f"   URL: {result.url}")
+        print(f"   Success: {result.success}")
+        print(f"   Metadata: {result.metadata}")
+
+
+async def test_multi_url_crawl():
+    """Test hooks with multiple URLs"""
+    print("\n" + "=" * 70)
+    print("Test 5: Multi-URL Crawl (Docker Client)")
+    print("=" * 70)
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nCrawling multiple URLs...")
+
+        hooks = {
+            "before_goto": url_specific_hook,
+            "after_goto": track_progress_hook
+        }
+
+        results = await client.crawl(
+            [
+                "https://httpbin.org/html",
+                "https://httpbin.org/json",
+                "https://httpbin.org/xml"
+            ],
+            hooks=hooks,
+            hooks_timeout=15
+        )
+
+        print("\n✅ Multi-URL crawl completed")
+        print(f"\n   Crawled {len(results)} URLs:")
+        for i, result in enumerate(results, 1):
+            status = "✅" if result.success else "❌"
+            print(f"   {status} {i}. {result.url}")
+
+
+async def test_reusable_hook_library():
+    """Test using reusable hook library"""
+    print("\n" + "=" * 70)
+    print("Test 6: Reusable Hook Library (Docker Client)")
+    print("=" * 70)
+
+    # Create a library of reusable hooks
+    class HookLibrary:
+        @staticmethod
+        async def block_images(page, context, **kwargs):
+            """Block all images"""
+            await context.route("**/*.{png,jpg,jpeg,gif}", lambda r: r.abort())
+            print("[LIBRARY] Images blocked")
+            return page
+
+        @staticmethod
+        async def block_analytics(page, context, **kwargs):
+            """Block analytics"""
+            await context.route("**/analytics/*", lambda r: r.abort())
+            await context.route("**/google-analytics.com/*", lambda r: r.abort())
+            print("[LIBRARY] Analytics blocked")
+            return page
+
+        @staticmethod
+        async def scroll_infinite(page, context, **kwargs):
+            """Handle infinite scroll"""
+            for i in range(5):
+                prev = await page.evaluate("document.body.scrollHeight")
+                await page.evaluate("window.scrollTo(0, document.body.scrollHeight);")
+                await page.wait_for_timeout(1000)
+                curr = await page.evaluate("document.body.scrollHeight")
+                if curr == prev:
+                    break
+            print("[LIBRARY] Infinite scroll complete")
+            return page
+
+    async with Crawl4aiDockerClient(base_url=API_BASE_URL, verbose=False) as client:
+        print("\nUsing hook library...")
+
+        hooks = {
+            "on_page_context_created": HookLibrary.block_images,
+            "before_retrieve_html": HookLibrary.scroll_infinite
+        }
+
+        result = await client.crawl(
+            ["https://www.kidocode.com/"],
+            hooks=hooks,
+            hooks_timeout=20
+        )
+
+        print("\n✅ Library hooks completed")
+        print(f"   Success: {result.success}")
+
+
+# ============================================================================
+# Main
+# ============================================================================
+
+async def main():
+    """Run all Docker client hook examples"""
+    print("🔧 Crawl4AI Docker Client - Hooks Examples (Function-Based)")
+    print("Using Python function objects with automatic conversion")
+    print("=" * 70)
+
+    tests = [
+        ("All Hooks Demo", test_all_hooks_comprehensive),
+        ("Authentication", test_authentication_workflow),
+        ("Performance", test_performance_optimization),
+        ("Extraction", test_content_extraction),
+        ("Multi-URL", test_multi_url_crawl),
+        ("Hook Library", test_reusable_hook_library)
+    ]
+
+    for i, (name, test_func) in enumerate(tests, 1):
+        try:
+            await test_func()
+            print(f"\n✅ Test {i}/{len(tests)}: {name} completed\n")
+        except Exception as e:
+            print(f"\n❌ Test {i}/{len(tests)}: {name} failed: {e}\n")
+            import traceback
+            traceback.print_exc()
+
+    print("=" * 70)
+    print("🎉 All Docker client hook examples completed!")
+    print("\n💡 Key Benefits of Function-Based Hooks:")
+    print("   • Write as regular Python functions")
+    print("   • Full IDE support (autocomplete, types)")
+    print("   • Automatic conversion to API format")
+    print("   • Reusable across projects")
+    print("   • Clean, readable code")
+    print("   • Easy to test and debug")
+    print("=" * 70)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

docs/examples/docker_webhook_example.py

@@ -0,0 +1,461 @@
+"""
+Docker Webhook Example for Crawl4AI
+
+This example demonstrates how to use webhooks with the Crawl4AI job queue API.
+Instead of polling for results, webhooks notify your application when jobs complete.
+
+Supports both:
+- /crawl/job - Raw crawling with markdown extraction
+- /llm/job - LLM-powered content extraction
+
+Prerequisites:
+1. Crawl4AI Docker container running on localhost:11235
+2. Flask installed: pip install flask requests
+3. LLM API key configured in .llm.env (for LLM extraction examples)
+
+Usage:
+1. Run this script: python docker_webhook_example.py
+2. The webhook server will start on http://localhost:8080
+3. Jobs will be submitted and webhooks will be received automatically
+"""
+
+import requests
+import json
+import time
+from flask import Flask, request, jsonify
+from threading import Thread
+
+# Configuration
+CRAWL4AI_BASE_URL = "http://localhost:11235"
+WEBHOOK_BASE_URL = "http://localhost:8080"  # Your webhook receiver URL
+
+# Initialize Flask app for webhook receiver
+app = Flask(__name__)
+
+# Store received webhook data for demonstration
+received_webhooks = []
+
+
+@app.route('/webhooks/crawl-complete', methods=['POST'])
+def handle_crawl_webhook():
+    """
+    Webhook handler that receives notifications when crawl jobs complete.
+
+    Payload structure:
+    {
+        "task_id": "crawl_abc123",
+        "task_type": "crawl",
+        "status": "completed" or "failed",
+        "timestamp": "2025-10-21T10:30:00.000000+00:00",
+        "urls": ["https://example.com"],
+        "error": "error message" (only if failed),
+        "data": {...} (only if webhook_data_in_payload=True)
+    }
+    """
+    payload = request.json
+    print(f"\n{'='*60}")
+    print(f"📬 Webhook received for task: {payload['task_id']}")
+    print(f"   Status: {payload['status']}")
+    print(f"   Timestamp: {payload['timestamp']}")
+    print(f"   URLs: {payload['urls']}")
+
+    if payload['status'] == 'completed':
+        # If data is in payload, process it directly
+        if 'data' in payload:
+            print(f"   ✅ Data included in webhook")
+            data = payload['data']
+            # Process the crawl results here
+            for result in data.get('results', []):
+                print(f"      - Crawled: {result.get('url')}")
+                print(f"      - Markdown length: {len(result.get('markdown', ''))}")
+        else:
+            # Fetch results from API if not included
+            print(f"   📥 Fetching results from API...")
+            task_id = payload['task_id']
+            result_response = requests.get(f"{CRAWL4AI_BASE_URL}/crawl/job/{task_id}")
+            if result_response.ok:
+                data = result_response.json()
+                print(f"   ✅ Results fetched successfully")
+                # Process the crawl results here
+                for result in data['result'].get('results', []):
+                    print(f"      - Crawled: {result.get('url')}")
+                    print(f"      - Markdown length: {len(result.get('markdown', ''))}")
+
+    elif payload['status'] == 'failed':
+        print(f"   ❌ Job failed: {payload.get('error', 'Unknown error')}")
+
+    print(f"{'='*60}\n")
+
+    # Store webhook for demonstration
+    received_webhooks.append(payload)
+
+    # Return 200 OK to acknowledge receipt
+    return jsonify({"status": "received"}), 200
+
+
+@app.route('/webhooks/llm-complete', methods=['POST'])
+def handle_llm_webhook():
+    """
+    Webhook handler that receives notifications when LLM extraction jobs complete.
+
+    Payload structure:
+    {
+        "task_id": "llm_1698765432_12345",
+        "task_type": "llm_extraction",
+        "status": "completed" or "failed",
+        "timestamp": "2025-10-21T10:30:00.000000+00:00",
+        "urls": ["https://example.com/article"],
+        "error": "error message" (only if failed),
+        "data": {"extracted_content": {...}} (only if webhook_data_in_payload=True)
+    }
+    """
+    payload = request.json
+    print(f"\n{'='*60}")
+    print(f"🤖 LLM Webhook received for task: {payload['task_id']}")
+    print(f"   Task Type: {payload['task_type']}")
+    print(f"   Status: {payload['status']}")
+    print(f"   Timestamp: {payload['timestamp']}")
+    print(f"   URL: {payload['urls'][0]}")
+
+    if payload['status'] == 'completed':
+        # If data is in payload, process it directly
+        if 'data' in payload:
+            print(f"   ✅ Data included in webhook")
+            data = payload['data']
+            # Webhook wraps extracted content in 'extracted_content' field
+            extracted = data.get('extracted_content', {})
+            print(f"      - Extracted content:")
+            print(f"        {json.dumps(extracted, indent=8)}")
+        else:
+            # Fetch results from API if not included
+            print(f"   📥 Fetching results from API...")
+            task_id = payload['task_id']
+            result_response = requests.get(f"{CRAWL4AI_BASE_URL}/llm/job/{task_id}")
+            if result_response.ok:
+                data = result_response.json()
+                print(f"   ✅ Results fetched successfully")
+                # API returns unwrapped content in 'result' field
+                extracted = data['result']
+                print(f"      - Extracted content:")
+                print(f"        {json.dumps(extracted, indent=8)}")
+
+    elif payload['status'] == 'failed':
+        print(f"   ❌ Job failed: {payload.get('error', 'Unknown error')}")
+
+    print(f"{'='*60}\n")
+
+    # Store webhook for demonstration
+    received_webhooks.append(payload)
+
+    # Return 200 OK to acknowledge receipt
+    return jsonify({"status": "received"}), 200
+
+
+def start_webhook_server():
+    """Start the Flask webhook server in a separate thread"""
+    app.run(host='0.0.0.0', port=8080, debug=False, use_reloader=False)
+
+
+def submit_crawl_job_with_webhook(urls, webhook_url, include_data=False):
+    """
+    Submit a crawl job with webhook notification.
+
+    Args:
+        urls: List of URLs to crawl
+        webhook_url: URL to receive webhook notifications
+        include_data: Whether to include full results in webhook payload
+
+    Returns:
+        task_id: The job's task identifier
+    """
+    payload = {
+        "urls": urls,
+        "browser_config": {"headless": True},
+        "crawler_config": {"cache_mode": "bypass"},
+        "webhook_config": {
+            "webhook_url": webhook_url,
+            "webhook_data_in_payload": include_data,
+            # Optional: Add custom headers for authentication
+            # "webhook_headers": {
+            #     "X-Webhook-Secret": "your-secret-token"
+            # }
+        }
+    }
+
+    print(f"\n🚀 Submitting crawl job...")
+    print(f"   URLs: {urls}")
+    print(f"   Webhook: {webhook_url}")
+    print(f"   Include data: {include_data}")
+
+    response = requests.post(
+        f"{CRAWL4AI_BASE_URL}/crawl/job",
+        json=payload,
+        headers={"Content-Type": "application/json"}
+    )
+
+    if response.ok:
+        data = response.json()
+        task_id = data['task_id']
+        print(f"   ✅ Job submitted successfully")
+        print(f"   Task ID: {task_id}")
+        return task_id
+    else:
+        print(f"   ❌ Failed to submit job: {response.text}")
+        return None
+
+
+def submit_llm_job_with_webhook(url, query, webhook_url, include_data=False, schema=None, provider=None):
+    """
+    Submit an LLM extraction job with webhook notification.
+
+    Args:
+        url: URL to extract content from
+        query: Instruction for the LLM (e.g., "Extract article title and author")
+        webhook_url: URL to receive webhook notifications
+        include_data: Whether to include full results in webhook payload
+        schema: Optional JSON schema for structured extraction
+        provider: Optional LLM provider (e.g., "openai/gpt-4o-mini")
+
+    Returns:
+        task_id: The job's task identifier
+    """
+    payload = {
+        "url": url,
+        "q": query,
+        "cache": False,
+        "webhook_config": {
+            "webhook_url": webhook_url,
+            "webhook_data_in_payload": include_data,
+            # Optional: Add custom headers for authentication
+            # "webhook_headers": {
+            #     "X-Webhook-Secret": "your-secret-token"
+            # }
+        }
+    }
+
+    if schema:
+        payload["schema"] = schema
+
+    if provider:
+        payload["provider"] = provider
+
+    print(f"\n🤖 Submitting LLM extraction job...")
+    print(f"   URL: {url}")
+    print(f"   Query: {query}")
+    print(f"   Webhook: {webhook_url}")
+    print(f"   Include data: {include_data}")
+    if provider:
+        print(f"   Provider: {provider}")
+
+    response = requests.post(
+        f"{CRAWL4AI_BASE_URL}/llm/job",
+        json=payload,
+        headers={"Content-Type": "application/json"}
+    )
+
+    if response.ok:
+        data = response.json()
+        task_id = data['task_id']
+        print(f"   ✅ Job submitted successfully")
+        print(f"   Task ID: {task_id}")
+        return task_id
+    else:
+        print(f"   ❌ Failed to submit job: {response.text}")
+        return None
+
+
+def submit_job_without_webhook(urls):
+    """
+    Submit a job without webhook (traditional polling approach).
+
+    Args:
+        urls: List of URLs to crawl
+
+    Returns:
+        task_id: The job's task identifier
+    """
+    payload = {
+        "urls": urls,
+        "browser_config": {"headless": True},
+        "crawler_config": {"cache_mode": "bypass"}
+    }
+
+    print(f"\n🚀 Submitting crawl job (without webhook)...")
+    print(f"   URLs: {urls}")
+
+    response = requests.post(
+        f"{CRAWL4AI_BASE_URL}/crawl/job",
+        json=payload
+    )
+
+    if response.ok:
+        data = response.json()
+        task_id = data['task_id']
+        print(f"   ✅ Job submitted successfully")
+        print(f"   Task ID: {task_id}")
+        return task_id
+    else:
+        print(f"   ❌ Failed to submit job: {response.text}")
+        return None
+
+
+def poll_job_status(task_id, timeout=60):
+    """
+    Poll for job status (used when webhook is not configured).
+
+    Args:
+        task_id: The job's task identifier
+        timeout: Maximum time to wait in seconds
+    """
+    print(f"\n⏳ Polling for job status...")
+    start_time = time.time()
+
+    while time.time() - start_time < timeout:
+        response = requests.get(f"{CRAWL4AI_BASE_URL}/crawl/job/{task_id}")
+
+        if response.ok:
+            data = response.json()
+            status = data.get('status', 'unknown')
+
+            if status == 'completed':
+                print(f"   ✅ Job completed!")
+                return data
+            elif status == 'failed':
+                print(f"   ❌ Job failed: {data.get('error', 'Unknown error')}")
+                return data
+            else:
+                print(f"   ⏳ Status: {status}, waiting...")
+                time.sleep(2)
+        else:
+            print(f"   ❌ Failed to get status: {response.text}")
+            return None
+
+    print(f"   ⏰ Timeout reached")
+    return None
+
+
+def main():
+    """Run the webhook demonstration"""
+
+    # Check if Crawl4AI is running
+    try:
+        health = requests.get(f"{CRAWL4AI_BASE_URL}/health", timeout=5)
+        print(f"✅ Crawl4AI is running: {health.json()}")
+    except:
+        print(f"❌ Cannot connect to Crawl4AI at {CRAWL4AI_BASE_URL}")
+        print("   Please make sure Docker container is running:")
+        print("   docker run -d -p 11235:11235 --name crawl4ai unclecode/crawl4ai:latest")
+        return
+
+    # Start webhook server in background thread
+    print(f"\n🌐 Starting webhook server at {WEBHOOK_BASE_URL}...")
+    webhook_thread = Thread(target=start_webhook_server, daemon=True)
+    webhook_thread.start()
+    time.sleep(2)  # Give server time to start
+
+    # Example 1: Job with webhook (notification only, fetch data separately)
+    print(f"\n{'='*60}")
+    print("Example 1: Webhook Notification Only")
+    print(f"{'='*60}")
+    task_id_1 = submit_crawl_job_with_webhook(
+        urls=["https://example.com"],
+        webhook_url=f"{WEBHOOK_BASE_URL}/webhooks/crawl-complete",
+        include_data=False
+    )
+
+    # Example 2: Job with webhook (data included in payload)
+    time.sleep(5)  # Wait a bit between requests
+    print(f"\n{'='*60}")
+    print("Example 2: Webhook with Full Data")
+    print(f"{'='*60}")
+    task_id_2 = submit_crawl_job_with_webhook(
+        urls=["https://www.python.org"],
+        webhook_url=f"{WEBHOOK_BASE_URL}/webhooks/crawl-complete",
+        include_data=True
+    )
+
+    # Example 3: LLM extraction with webhook (notification only)
+    time.sleep(5)  # Wait a bit between requests
+    print(f"\n{'='*60}")
+    print("Example 3: LLM Extraction with Webhook (Notification Only)")
+    print(f"{'='*60}")
+    task_id_3 = submit_llm_job_with_webhook(
+        url="https://www.example.com",
+        query="Extract the main heading and description from this page.",
+        webhook_url=f"{WEBHOOK_BASE_URL}/webhooks/llm-complete",
+        include_data=False,
+        provider="openai/gpt-4o-mini"
+    )
+
+    # Example 4: LLM extraction with webhook (data included + schema)
+    time.sleep(5)  # Wait a bit between requests
+    print(f"\n{'='*60}")
+    print("Example 4: LLM Extraction with Schema and Full Data")
+    print(f"{'='*60}")
+
+    # Define a schema for structured extraction
+    schema = json.dumps({
+        "type": "object",
+        "properties": {
+            "title": {"type": "string", "description": "Page title"},
+            "description": {"type": "string", "description": "Page description"}
+        },
+        "required": ["title"]
+    })
+
+    task_id_4 = submit_llm_job_with_webhook(
+        url="https://www.python.org",
+        query="Extract the title and description of this website",
+        webhook_url=f"{WEBHOOK_BASE_URL}/webhooks/llm-complete",
+        include_data=True,
+        schema=schema,
+        provider="openai/gpt-4o-mini"
+    )
+
+    # Example 5: Traditional polling (no webhook)
+    time.sleep(5)  # Wait a bit between requests
+    print(f"\n{'='*60}")
+    print("Example 5: Traditional Polling (No Webhook)")
+    print(f"{'='*60}")
+    task_id_5 = submit_job_without_webhook(
+        urls=["https://github.com"]
+    )
+    if task_id_5:
+        result = poll_job_status(task_id_5)
+        if result and result.get('status') == 'completed':
+            print(f"   ✅ Results retrieved via polling")
+
+    # Wait for webhooks to arrive
+    print(f"\n⏳ Waiting for webhooks to be received...")
+    time.sleep(30)  # Give jobs time to complete and webhooks to arrive (longer for LLM)
+
+    # Summary
+    print(f"\n{'='*60}")
+    print("Summary")
+    print(f"{'='*60}")
+    print(f"Total webhooks received: {len(received_webhooks)}")
+
+    crawl_webhooks = [w for w in received_webhooks if w['task_type'] == 'crawl']
+    llm_webhooks = [w for w in received_webhooks if w['task_type'] == 'llm_extraction']
+
+    print(f"\n📊 Breakdown:")
+    print(f"   - Crawl webhooks: {len(crawl_webhooks)}")
+    print(f"   - LLM extraction webhooks: {len(llm_webhooks)}")
+
+    print(f"\n📋 Details:")
+    for i, webhook in enumerate(received_webhooks, 1):
+        task_type = webhook['task_type']
+        icon = "🕷️" if task_type == "crawl" else "🤖"
+        print(f"{i}. {icon} Task {webhook['task_id']}: {webhook['status']} ({task_type})")
+
+    print(f"\n✅ Demo completed!")
+    print(f"\n💡 Pro tips:")
+    print(f"   - In production, your webhook URL should be publicly accessible")
+    print(f"     (e.g., https://myapp.com/webhooks) or use ngrok for testing")
+    print(f"   - Both /crawl/job and /llm/job support the same webhook configuration")
+    print(f"   - Use webhook_data_in_payload=true to get results directly in the webhook")
+    print(f"   - LLM jobs may take longer, adjust timeouts accordingly")
+
+
+if __name__ == "__main__":
+    main()

docs/md_v2/blog/index.md

@@ -20,17 +20,43 @@ Ever wondered why your AI coding assistant struggles with your library despite c
 
 ## Latest Release
 
+### [Crawl4AI v0.7.6 – The Webhook Infrastructure Update](../blog/release-v0.7.6.md)
+*October 22, 2025*
+
+Crawl4AI v0.7.6 introduces comprehensive webhook support for the Docker job queue API, bringing real-time notifications to both crawling and LLM extraction workflows. No more polling!
+
+Key highlights:
+- **🪝 Complete Webhook Support**: Real-time notifications for both `/crawl/job` and `/llm/job` endpoints
+- **🔄 Reliable Delivery**: Exponential backoff retry mechanism (5 attempts: 1s → 2s → 4s → 8s → 16s)
+- **🔐 Custom Authentication**: Add custom headers for webhook authentication
+- **📊 Flexible Delivery**: Choose notification-only or include full data in payload
+- **⚙️ Global Configuration**: Set default webhook URL in config.yml for all jobs
+- **🎯 Zero Breaking Changes**: Fully backward compatible, webhooks are opt-in
+
+[Read full release notes →](../blog/release-v0.7.6.md)
+
+## Recent Releases
+
+### [Crawl4AI v0.7.5 – The Docker Hooks & Security Update](../blog/release-v0.7.5.md)
+*September 29, 2025*
+
+Crawl4AI v0.7.5 introduces the powerful Docker Hooks System for complete pipeline customization, enhanced LLM integration with custom providers, HTTPS preservation for modern web security, and resolves multiple community-reported issues.
+
+Key highlights:
+- **🔧 Docker Hooks System**: Custom Python functions at 8 key pipeline points for unprecedented customization
+- **🤖 Enhanced LLM Integration**: Custom providers with temperature control and base_url configuration
+- **🔒 HTTPS Preservation**: Secure internal link handling for modern web applications
+- **🐍 Python 3.10+ Support**: Modern language features and enhanced performance
+- **🛠️ Bug Fixes**: Resolved multiple community-reported issues including URL processing, JWT authentication, and proxy configuration
+
+[Read full release notes →](../blog/release-v0.7.5.md)
+
+## Recent Releases
+
 ### [Crawl4AI v0.7.4 – The Intelligent Table Extraction & Performance Update](../blog/release-v0.7.4.md)
 *August 17, 2025*
 
-Crawl4AI v0.7.4 introduces revolutionary LLM-powered table extraction with intelligent chunking, performance improvements for concurrent crawling, enhanced browser management, and critical stability fixes that make Crawl4AI more robust for production workloads.
+Revolutionary LLM-powered table extraction with intelligent chunking, performance improvements for concurrent crawling, enhanced browser management, and critical stability fixes.
-
-Key highlights:
-- **🚀 LLMTableExtraction**: Revolutionary table extraction with intelligent chunking for massive tables
-- **⚡ Dispatcher Bug Fix**: Fixed sequential processing issue in arun_many for fast-completing tasks
-- **🧹 Memory Management Refactor**: Streamlined memory utilities and better resource management
-- **🔧 Browser Manager Fixes**: Resolved race conditions in concurrent page creation
-- **🔗 Advanced URL Processing**: Better handling of raw URLs and base tag link resolution
 
 [Read full release notes →](../blog/release-v0.7.4.md)
 

docs/md_v2/blog/releases/0.7.6.md

@@ -0,0 +1,314 @@
+# Crawl4AI v0.7.6 Release Notes
+
+*Release Date: October 22, 2025*
+
+I'm excited to announce Crawl4AI v0.7.6, featuring a complete webhook infrastructure for the Docker job queue API! This release eliminates polling and brings real-time notifications to both crawling and LLM extraction workflows.
+
+## 🎯 What's New
+
+### Webhook Support for Docker Job Queue API
+
+The headline feature of v0.7.6 is comprehensive webhook support for asynchronous job processing. No more constant polling to check if your jobs are done - get instant notifications when they complete!
+
+**Key Capabilities:**
+
+- ✅ **Universal Webhook Support**: Both `/crawl/job` and `/llm/job` endpoints now support webhooks
+- ✅ **Flexible Delivery Modes**: Choose notification-only or include full data in the webhook payload
+- ✅ **Reliable Delivery**: Exponential backoff retry mechanism (5 attempts: 1s → 2s → 4s → 8s → 16s)
+- ✅ **Custom Authentication**: Add custom headers for webhook authentication
+- ✅ **Global Configuration**: Set default webhook URL in `config.yml` for all jobs
+- ✅ **Task Type Identification**: Distinguish between `crawl` and `llm_extraction` tasks
+
+### How It Works
+
+Instead of constantly checking job status:
+
+**OLD WAY (Polling):**
+```python
+# Submit job
+response = requests.post("http://localhost:11235/crawl/job", json=payload)
+task_id = response.json()['task_id']
+
+# Poll until complete
+while True:
+    status = requests.get(f"http://localhost:11235/crawl/job/{task_id}")
+    if status.json()['status'] == 'completed':
+        break
+    time.sleep(5)  # Wait and try again
+```
+
+**NEW WAY (Webhooks):**
+```python
+# Submit job with webhook
+payload = {
+    "urls": ["https://example.com"],
+    "webhook_config": {
+        "webhook_url": "https://myapp.com/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+response = requests.post("http://localhost:11235/crawl/job", json=payload)
+
+# Done! Webhook will notify you when complete
+# Your webhook handler receives the results automatically
+```
+
+### Crawl Job Webhooks
+
+```bash
+curl -X POST http://localhost:11235/crawl/job \
+  -H "Content-Type: application/json" \
+  -d '{
+    "urls": ["https://example.com"],
+    "browser_config": {"headless": true},
+    "crawler_config": {"cache_mode": "bypass"},
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/crawl-complete",
+      "webhook_data_in_payload": false,
+      "webhook_headers": {
+        "X-Webhook-Secret": "your-secret-token"
+      }
+    }
+  }'
+```
+
+### LLM Extraction Job Webhooks (NEW!)
+
+```bash
+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 publication date",
+    "schema": "{\"type\":\"object\",\"properties\":{\"title\":{\"type\":\"string\"}}}",
+    "provider": "openai/gpt-4o-mini",
+    "webhook_config": {
+      "webhook_url": "https://myapp.com/webhooks/llm-complete",
+      "webhook_data_in_payload": true
+    }
+  }'
+```
+
+### Webhook Payload Structure
+
+**Success (with data):**
+```json
+{
+  "task_id": "llm_1698765432",
+  "task_type": "llm_extraction",
+  "status": "completed",
+  "timestamp": "2025-10-22T10:30:00.000000+00:00",
+  "urls": ["https://example.com/article"],
+  "data": {
+    "extracted_content": {
+      "title": "Understanding Web Scraping",
+      "author": "John Doe",
+      "date": "2025-10-22"
+    }
+  }
+}
+```
+
+**Failure:**
+```json
+{
+  "task_id": "crawl_abc123",
+  "task_type": "crawl",
+  "status": "failed",
+  "timestamp": "2025-10-22T10:30:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "error": "Connection timeout after 30s"
+}
+```
+
+### Simple Webhook Handler Example
+
+```python
+from flask import Flask, request, jsonify
+
+app = Flask(__name__)
+
+@app.route('/webhook', methods=['POST'])
+def handle_webhook():
+    payload = request.json
+
+    task_id = payload['task_id']
+    task_type = payload['task_type']
+    status = payload['status']
+
+    if status == 'completed':
+        if 'data' in payload:
+            # Process data directly
+            data = payload['data']
+        else:
+            # Fetch from API
+            endpoint = 'crawl' if task_type == 'crawl' else 'llm'
+            response = requests.get(f'http://localhost:11235/{endpoint}/job/{task_id}')
+            data = response.json()
+
+        # Your business logic here
+        print(f"Job {task_id} completed!")
+
+    elif status == 'failed':
+        error = payload.get('error', 'Unknown error')
+        print(f"Job {task_id} failed: {error}")
+
+    return jsonify({"status": "received"}), 200
+
+app.run(port=8080)
+```
+
+## 📊 Performance Improvements
+
+- **Reduced Server Load**: Eliminates constant polling requests
+- **Lower Latency**: Instant notification vs. polling interval delay
+- **Better Resource Usage**: Frees up client connections while jobs run in background
+- **Scalable Architecture**: Handles high-volume crawling workflows efficiently
+
+## 🐛 Bug Fixes
+
+- Fixed webhook configuration serialization for Pydantic HttpUrl fields
+- Improved error handling in webhook delivery service
+- Enhanced Redis task storage for webhook config persistence
+
+## 🌍 Expected Real-World Impact
+
+### For Web Scraping Workflows
+- **Reduced Costs**: Less API calls = lower bandwidth and server costs
+- **Better UX**: Instant notifications improve user experience
+- **Scalability**: Handle 100s of concurrent jobs without polling overhead
+
+### For LLM Extraction Pipelines
+- **Async Processing**: Submit LLM extraction jobs and move on
+- **Batch Processing**: Queue multiple extractions, get notified as they complete
+- **Integration**: Easy integration with workflow automation tools (Zapier, n8n, etc.)
+
+### For Microservices
+- **Event-Driven**: Perfect for event-driven microservice architectures
+- **Decoupling**: Decouple job submission from result processing
+- **Reliability**: Automatic retries ensure webhooks are delivered
+
+## 🔄 Breaking Changes
+
+**None!** This release is fully backward compatible.
+
+- Webhook configuration is optional
+- Existing code continues to work without modification
+- Polling is still supported for jobs without webhook config
+
+## 📚 Documentation
+
+### New Documentation
+- **[WEBHOOK_EXAMPLES.md](../deploy/docker/WEBHOOK_EXAMPLES.md)** - Comprehensive webhook usage guide
+- **[docker_webhook_example.py](../docs/examples/docker_webhook_example.py)** - Working code examples
+
+### Updated Documentation
+- **[Docker README](../deploy/docker/README.md)** - Added webhook sections
+- API documentation with webhook examples
+
+## 🛠️ Migration Guide
+
+No migration needed! Webhooks are opt-in:
+
+1. **To use webhooks**: Add `webhook_config` to your job payload
+2. **To keep polling**: Continue using your existing code
+
+### Quick Start
+
+```python
+# Just add webhook_config to your existing payload
+payload = {
+    # Your existing configuration
+    "urls": ["https://example.com"],
+    "browser_config": {...},
+    "crawler_config": {...},
+
+    # NEW: Add webhook configuration
+    "webhook_config": {
+        "webhook_url": "https://myapp.com/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+```
+
+## 🔧 Configuration
+
+### Global Webhook Configuration (config.yml)
+
+```yaml
+webhooks:
+  enabled: true
+  default_url: "https://myapp.com/webhooks/default"  # Optional
+  data_in_payload: false
+  retry:
+    max_attempts: 5
+    initial_delay_ms: 1000
+    max_delay_ms: 32000
+    timeout_ms: 30000
+  headers:
+    User-Agent: "Crawl4AI-Webhook/1.0"
+```
+
+## 🚀 Upgrade Instructions
+
+### Docker
+
+```bash
+# Pull the latest image
+docker pull unclecode/crawl4ai:0.7.6
+
+# Or use latest tag
+docker pull unclecode/crawl4ai:latest
+
+# Run with webhook support
+docker run -d \
+  -p 11235:11235 \
+  --env-file .llm.env \
+  --name crawl4ai \
+  unclecode/crawl4ai:0.7.6
+```
+
+### Python Package
+
+```bash
+pip install --upgrade crawl4ai
+```
+
+## 💡 Pro Tips
+
+1. **Use notification-only mode** for large results - fetch data separately to avoid large webhook payloads
+2. **Set custom headers** for webhook authentication and request tracking
+3. **Configure global default webhook** for consistent handling across all jobs
+4. **Implement idempotent webhook handlers** - same webhook may be delivered multiple times on retry
+5. **Use structured schemas** with LLM extraction for predictable webhook data
+
+## 🎬 Demo
+
+Try the release demo:
+
+```bash
+python docs/releases_review/demo_v0.7.6.py
+```
+
+This comprehensive demo showcases:
+- Crawl job webhooks (notification-only and with data)
+- LLM extraction webhooks (with JSON schema support)
+- Custom headers for authentication
+- Webhook retry mechanism
+- Real-time webhook receiver
+
+## 🙏 Acknowledgments
+
+Thank you to the community for the feedback that shaped this feature! Special thanks to everyone who requested webhook support for asynchronous job processing.
+
+## 📞 Support
+
+- **Documentation**: https://docs.crawl4ai.com
+- **GitHub Issues**: https://github.com/unclecode/crawl4ai/issues
+- **Discord**: https://discord.gg/crawl4ai
+
+---
+
+**Happy crawling with webhooks!** 🕷️🪝
+
+*- unclecode*

docs/md_v2/blog/releases/v0.7.5.md

@@ -0,0 +1,318 @@
+# 🚀 Crawl4AI v0.7.5: The Docker Hooks & Security Update
+
+*September 29, 2025 • 8 min read*
+
+---
+
+Today I'm releasing Crawl4AI v0.7.5—focused on extensibility and security. This update introduces the Docker Hooks System for pipeline customization, enhanced LLM integration, and important security improvements.
+
+## 🎯 What's New at a Glance
+
+- **Docker Hooks System**: Custom Python functions at key pipeline points with function-based API
+- **Function-Based Hooks**: New `hooks_to_string()` utility with Docker client auto-conversion
+- **Enhanced LLM Integration**: Custom providers with temperature control
+- **HTTPS Preservation**: Secure internal link handling
+- **Bug Fixes**: Resolved multiple community-reported issues
+- **Improved Docker Error Handling**: Better debugging and reliability
+
+## 🔧 Docker Hooks System: Pipeline Customization
+
+Every scraping project needs custom logic—authentication, performance optimization, content processing. Traditional solutions require forking or complex workarounds. Docker Hooks let you inject custom Python functions at 8 key points in the crawling pipeline.
+
+### Real Example: Authentication & Performance
+
+```python
+import requests
+
+# Real working hooks for httpbin.org
+hooks_config = {
+    "on_page_context_created": """
+async def hook(page, context, **kwargs):
+    print("Hook: Setting up page context")
+    # Block images to speed up crawling
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    print("Hook: Images blocked")
+    return page
+""",
+
+    "before_retrieve_html": """
+async def hook(page, context, **kwargs):
+    print("Hook: Before retrieving HTML")
+    # Scroll to bottom to load lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    print("Hook: Scrolled to bottom")
+    return page
+""",
+
+    "before_goto": """
+async def hook(page, context, url, **kwargs):
+    print(f"Hook: About to navigate to {url}")
+    # Add custom headers
+    await page.set_extra_http_headers({
+        'X-Test-Header': 'crawl4ai-hooks-test'
+    })
+    return page
+"""
+}
+
+# Test with Docker API
+payload = {
+    "urls": ["https://httpbin.org/html"],
+    "hooks": {
+        "code": hooks_config,
+        "timeout": 30
+    }
+}
+
+response = requests.post("http://localhost:11235/crawl", json=payload)
+result = response.json()
+
+if result.get('success'):
+    print("✅ Hooks executed successfully!")
+    print(f"Content length: {len(result.get('markdown', ''))} characters")
+```
+
+**Available Hook Points:**
+- `on_browser_created`: Browser setup
+- `on_page_context_created`: Page context configuration
+- `before_goto`: Pre-navigation setup
+- `after_goto`: Post-navigation processing
+- `on_user_agent_updated`: User agent changes
+- `on_execution_started`: Crawl initialization
+- `before_retrieve_html`: Pre-extraction processing
+- `before_return_html`: Final HTML processing
+
+### Function-Based Hooks API
+
+Writing hooks as strings works, but lacks IDE support and type checking. v0.7.5 introduces a function-based approach with automatic conversion!
+
+**Option 1: Using the `hooks_to_string()` Utility**
+
+```python
+from crawl4ai import hooks_to_string
+import requests
+
+# Define hooks as regular Python functions (with full IDE support!)
+async def on_page_context_created(page, context, **kwargs):
+    """Block images to speed up crawling"""
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+
+async def before_goto(page, context, url, **kwargs):
+    """Add custom headers"""
+    await page.set_extra_http_headers({
+        'X-Crawl4AI': 'v0.7.5',
+        'X-Custom-Header': 'my-value'
+    })
+    return page
+
+# Convert functions to strings
+hooks_code = hooks_to_string({
+    "on_page_context_created": on_page_context_created,
+    "before_goto": before_goto
+})
+
+# Use with REST API
+payload = {
+    "urls": ["https://httpbin.org/html"],
+    "hooks": {"code": hooks_code, "timeout": 30}
+}
+response = requests.post("http://localhost:11235/crawl", json=payload)
+```
+
+**Option 2: Docker Client with Automatic Conversion (Recommended!)**
+
+```python
+from crawl4ai.docker_client import Crawl4aiDockerClient
+
+# Define hooks as functions (same as above)
+async def on_page_context_created(page, context, **kwargs):
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    return page
+
+async def before_retrieve_html(page, context, **kwargs):
+    # Scroll to load lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    return page
+
+# Use Docker client - conversion happens automatically!
+client = Crawl4aiDockerClient(base_url="http://localhost:11235")
+
+results = await client.crawl(
+    urls=["https://httpbin.org/html"],
+    hooks={
+        "on_page_context_created": on_page_context_created,
+        "before_retrieve_html": before_retrieve_html
+    },
+    hooks_timeout=30
+)
+
+if results and results.success:
+    print(f"✅ Hooks executed! HTML length: {len(results.html)}")
+```
+
+**Benefits of Function-Based Hooks:**
+- ✅ Full IDE support (autocomplete, syntax highlighting)
+- ✅ Type checking and linting
+- ✅ Easier to test and debug
+- ✅ Reusable across projects
+- ✅ Automatic conversion in Docker client
+- ✅ No breaking changes - string hooks still work!
+
+## 🤖 Enhanced LLM Integration
+
+Enhanced LLM integration with custom providers, temperature control, and base URL configuration.
+
+### Multi-Provider Support
+
+```python
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
+from crawl4ai.extraction_strategy import LLMExtractionStrategy
+
+# Test with different providers
+async def test_llm_providers():
+    # OpenAI with custom temperature
+    openai_strategy = LLMExtractionStrategy(
+        provider="gemini/gemini-2.5-flash-lite",
+        api_token="your-api-token",
+        temperature=0.7,  # New in v0.7.5
+        instruction="Summarize this page in one sentence"
+    )
+
+    async with AsyncWebCrawler() as crawler:
+        result = await crawler.arun(
+            "https://example.com",
+            config=CrawlerRunConfig(extraction_strategy=openai_strategy)
+        )
+
+        if result.success:
+            print("✅ LLM extraction completed")
+            print(result.extracted_content)
+
+# Docker API with enhanced LLM config
+llm_payload = {
+    "url": "https://example.com",
+    "f": "llm",
+    "q": "Summarize this page in one sentence.",
+    "provider": "gemini/gemini-2.5-flash-lite",
+    "temperature": 0.7
+}
+
+response = requests.post("http://localhost:11235/md", json=llm_payload)
+```
+
+**New Features:**
+- Custom `temperature` parameter for creativity control
+- `base_url` for custom API endpoints
+- Multi-provider environment variable support
+- Docker API integration
+
+## 🔒 HTTPS Preservation
+
+**The Problem:** Modern web apps require HTTPS everywhere. When crawlers downgrade internal links from HTTPS to HTTP, authentication breaks and security warnings appear.
+
+**Solution:** HTTPS preservation maintains secure protocols throughout crawling.
+
+```python
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, FilterChain, URLPatternFilter, BFSDeepCrawlStrategy
+
+async def test_https_preservation():
+    # Enable HTTPS preservation
+    url_filter = URLPatternFilter(
+        patterns=["^(https:\/\/)?quotes\.toscrape\.com(\/.*)?$"]
+    )
+
+    config = CrawlerRunConfig(
+        exclude_external_links=True,
+        preserve_https_for_internal_links=True,  # New in v0.7.5
+        deep_crawl_strategy=BFSDeepCrawlStrategy(
+            max_depth=2,
+            max_pages=5,
+            filter_chain=FilterChain([url_filter])
+        )
+    )
+
+    async with AsyncWebCrawler() as crawler:
+        async for result in await crawler.arun(
+            url="https://quotes.toscrape.com",
+            config=config
+        ):
+            # All internal links maintain HTTPS
+            internal_links = [link['href'] for link in result.links['internal']]
+            https_links = [link for link in internal_links if link.startswith('https://')]
+
+            print(f"HTTPS links preserved: {len(https_links)}/{len(internal_links)}")
+            for link in https_links[:3]:
+                print(f"  → {link}")
+```
+
+## 🛠️ Bug Fixes and Improvements
+
+### Major Fixes
+- **URL Processing**: Fixed '+' sign preservation in query parameters (#1332)
+- **Proxy Configuration**: Enhanced proxy string parsing (old `proxy` parameter deprecated)
+- **Docker Error Handling**: Comprehensive error messages with status codes
+- **Memory Management**: Fixed leaks in long-running sessions
+- **JWT Authentication**: Fixed Docker JWT validation issues (#1442)
+- **Playwright Stealth**: Fixed stealth features for Playwright integration (#1481)
+- **API Configuration**: Fixed config handling to prevent overriding user-provided settings (#1505)
+- **Docker Filter Serialization**: Resolved JSON encoding errors in deep crawl strategy (#1419)
+- **LLM Provider Support**: Fixed custom LLM provider integration for adaptive crawler (#1291)
+- **Performance Issues**: Resolved backoff strategy failures and timeout handling (#989)
+
+### Community-Reported Issues Fixed
+This release addresses multiple issues reported by the community through GitHub issues and Discord discussions:
+- Fixed browser configuration reference errors
+- Resolved dependency conflicts with cssselect
+- Improved error messaging for failed authentications
+- Enhanced compatibility with various proxy configurations
+- Fixed edge cases in URL normalization
+
+### Configuration Updates
+```python
+# Old proxy config (deprecated)
+# browser_config = BrowserConfig(proxy="http://proxy:8080")
+
+# New enhanced proxy config
+browser_config = BrowserConfig(
+    proxy_config={
+        "server": "http://proxy:8080",
+        "username": "optional-user",
+        "password": "optional-pass"
+    }
+)
+```
+
+## 🔄 Breaking Changes
+
+1. **Python 3.10+ Required**: Upgrade from Python 3.9
+2. **Proxy Parameter Deprecated**: Use new `proxy_config` structure
+3. **New Dependency**: Added `cssselect` for better CSS handling
+
+## 🚀 Get Started
+
+```bash
+# Install latest version
+pip install crawl4ai==0.7.5
+
+# Docker deployment
+docker pull unclecode/crawl4ai:latest
+docker run -p 11235:11235 unclecode/crawl4ai:latest
+```
+
+**Try the Demo:**
+```bash
+# Run working examples
+python docs/releases_review/demo_v0.7.5.py
+```
+
+**Resources:**
+- 📖 Documentation: [docs.crawl4ai.com](https://docs.crawl4ai.com)
+- 🐙 GitHub: [github.com/unclecode/crawl4ai](https://github.com/unclecode/crawl4ai)
+- 💬 Discord: [discord.gg/crawl4ai](https://discord.gg/jP8KfhDhyN)
+- 🐦 Twitter: [@unclecode](https://x.com/unclecode)
+
+Happy crawling! 🕷️

docs/md_v2/core/docker-deployment.md

@@ -6,18 +6,6 @@
   - [Option 1: Using Pre-built Docker Hub Images (Recommended)](#option-1-using-pre-built-docker-hub-images-recommended)
   - [Option 2: Using Docker Compose](#option-2-using-docker-compose)
   - [Option 3: Manual Local Build & Run](#option-3-manual-local-build--run)
-- [Dockerfile Parameters](#dockerfile-parameters)
-- [Using the API](#using-the-api)
-  - [Playground Interface](#playground-interface)
-  - [Python SDK](#python-sdk)
-  - [Understanding Request Schema](#understanding-request-schema)
-  - [REST API Examples](#rest-api-examples)
-- [Additional API Endpoints](#additional-api-endpoints)
-  - [HTML Extraction Endpoint](#html-extraction-endpoint)
-  - [Screenshot Endpoint](#screenshot-endpoint)
-  - [PDF Export Endpoint](#pdf-export-endpoint)
-  - [JavaScript Execution Endpoint](#javascript-execution-endpoint)
-  - [Library Context Endpoint](#library-context-endpoint)
 - [MCP (Model Context Protocol) Support](#mcp-model-context-protocol-support)
   - [What is MCP?](#what-is-mcp)
   - [Connecting via MCP](#connecting-via-mcp)
@@ -25,9 +13,36 @@
   - [Available MCP Tools](#available-mcp-tools)
   - [Testing MCP Connections](#testing-mcp-connections)
   - [MCP Schemas](#mcp-schemas)
+- [Additional API Endpoints](#additional-api-endpoints)
+  - [HTML Extraction Endpoint](#html-extraction-endpoint)
+  - [Screenshot Endpoint](#screenshot-endpoint)
+  - [PDF Export Endpoint](#pdf-export-endpoint)
+  - [JavaScript Execution Endpoint](#javascript-execution-endpoint)
+- [User-Provided Hooks API](#user-provided-hooks-api)
+  - [Hook Information Endpoint](#hook-information-endpoint)
+  - [Available Hook Points](#available-hook-points)
+  - [Using Hooks in Requests](#using-hooks-in-requests)
+  - [Hook Examples with Real URLs](#hook-examples-with-real-urls)
+  - [Security Best Practices](#security-best-practices)
+  - [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)
+  - [Python SDK](#python-sdk)
+  - [Understanding Request Schema](#understanding-request-schema)
+  - [REST API Examples](#rest-api-examples)
+  - [LLM Configuration Examples](#llm-configuration-examples)
 - [Metrics & Monitoring](#metrics--monitoring)
-- [Deployment Scenarios](#deployment-scenarios)
-- [Complete Examples](#complete-examples)
 - [Server Configuration](#server-configuration)
   - [Understanding config.yml](#understanding-configyml)
   - [JWT Authentication](#jwt-authentication)
@@ -58,13 +73,13 @@ Pull and run images directly from Docker Hub without building locally.
 
 #### 1. Pull the Image
 
-Our latest release is `0.7.3`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
+Our latest release is `0.7.6`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
 
-> 💡 **Note**: The `latest` tag points to the stable `0.7.3` version.
+> 💡 **Note**: The `latest` tag points to the stable `0.7.6` version.
 
 ```bash
 # Pull the latest version
-docker pull unclecode/crawl4ai:0.7.3
+docker pull unclecode/crawl4ai:0.7.6
 
 # Or pull using the latest tag
 docker pull unclecode/crawl4ai:latest
@@ -136,7 +151,7 @@ docker stop crawl4ai && docker rm crawl4ai
 #### Docker Hub Versioning Explained
 
 *   **Image Name:** `unclecode/crawl4ai`
-*   **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.7.3`)
+*   **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.7.6`)
     *   `LIBRARY_VERSION`: The semantic version of the core `crawl4ai` Python library
     *   `SUFFIX`: Optional tag for release candidates (``) and revisions (`r1`)
 *   **`latest` Tag:** Points to the most recent stable version
@@ -832,6 +847,733 @@ else:
 
 > 💡 **Remember**: Always test your hooks on safe, known websites first before using them on production sites. Never crawl sites that you don't have permission to access or that might be malicious.
 
+### Hooks Utility: Function-Based Approach (Python)
+
+For Python developers, Crawl4AI provides a more convenient way to work with hooks using the `hooks_to_string()` utility function and Docker client integration.
+
+#### Why Use Function-Based Hooks?
+
+**String-Based Approach (shown above)**:
+```python
+hooks_code = {
+    "on_page_context_created": """
+async def hook(page, context, **kwargs):
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+"""
+}
+```
+
+**Function-Based Approach (recommended for Python)**:
+```python
+from crawl4ai import Crawl4aiDockerClient
+
+async def my_hook(page, context, **kwargs):
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+
+async with Crawl4aiDockerClient(base_url="http://localhost:11235") as client:
+    result = await client.crawl(
+        ["https://example.com"],
+        hooks={"on_page_context_created": my_hook}
+    )
+```
+
+**Benefits**:
+- ✅ Write hooks as regular Python functions
+- ✅ Full IDE support (autocomplete, syntax highlighting, type checking)
+- ✅ Easy to test and debug
+- ✅ Reusable hook libraries
+- ✅ Automatic conversion to API format
+
+#### Using the Hooks Utility
+
+The `hooks_to_string()` utility converts Python function objects to the string format required by the API:
+
+```python
+from crawl4ai import hooks_to_string
+
+# Define your hooks as functions
+async def setup_hook(page, context, **kwargs):
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    await context.add_cookies([{
+        "name": "session",
+        "value": "token",
+        "domain": ".example.com"
+    }])
+    return page
+
+async def scroll_hook(page, context, **kwargs):
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    return page
+
+# Convert to string format
+hooks_dict = {
+    "on_page_context_created": setup_hook,
+    "before_retrieve_html": scroll_hook
+}
+hooks_string = hooks_to_string(hooks_dict)
+
+# Now use with REST API or Docker client
+# hooks_string contains the string representations
+```
+
+#### Docker Client with Automatic Conversion
+
+The Docker client automatically detects and converts function objects:
+
+```python
+from crawl4ai import Crawl4aiDockerClient
+
+async def auth_hook(page, context, **kwargs):
+    """Add authentication cookies"""
+    await context.add_cookies([{
+        "name": "auth_token",
+        "value": "your_token",
+        "domain": ".example.com"
+    }])
+    return page
+
+async def performance_hook(page, context, **kwargs):
+    """Block unnecessary resources"""
+    await context.route("**/*.{png,jpg,gif}", lambda r: r.abort())
+    await context.route("**/analytics/*", lambda r: r.abort())
+    return page
+
+async with Crawl4aiDockerClient(base_url="http://localhost:11235") as client:
+    # Pass functions directly - automatic conversion!
+    result = await client.crawl(
+        ["https://example.com"],
+        hooks={
+            "on_page_context_created": performance_hook,
+            "before_goto": auth_hook
+        },
+        hooks_timeout=30  # Optional timeout in seconds (1-120)
+    )
+
+    print(f"Success: {result.success}")
+    print(f"HTML: {len(result.html)} chars")
+```
+
+#### Creating Reusable Hook Libraries
+
+Build collections of reusable hooks:
+
+```python
+# hooks_library.py
+class CrawlHooks:
+    """Reusable hook collection for common crawling tasks"""
+
+    @staticmethod
+    async def block_images(page, context, **kwargs):
+        """Block all images to speed up crawling"""
+        await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda r: r.abort())
+        return page
+
+    @staticmethod
+    async def block_analytics(page, context, **kwargs):
+        """Block analytics and tracking scripts"""
+        tracking_domains = [
+            "**/google-analytics.com/*",
+            "**/googletagmanager.com/*",
+            "**/facebook.com/tr/*",
+            "**/doubleclick.net/*"
+        ]
+        for domain in tracking_domains:
+            await context.route(domain, lambda r: r.abort())
+        return page
+
+    @staticmethod
+    async def scroll_infinite(page, context, **kwargs):
+        """Handle infinite scroll to load more content"""
+        previous_height = 0
+        for i in range(5):  # Max 5 scrolls
+            current_height = await page.evaluate("document.body.scrollHeight")
+            if current_height == previous_height:
+                break
+            await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+            await page.wait_for_timeout(1000)
+            previous_height = current_height
+        return page
+
+    @staticmethod
+    async def wait_for_dynamic_content(page, context, url, response, **kwargs):
+        """Wait for dynamic content to load"""
+        await page.wait_for_timeout(2000)
+        try:
+            # Click "Load More" if present
+            load_more = await page.query_selector('[class*="load-more"]')
+            if load_more:
+                await load_more.click()
+                await page.wait_for_timeout(1000)
+        except:
+            pass
+        return page
+
+# Use in your application
+from hooks_library import CrawlHooks
+from crawl4ai import Crawl4aiDockerClient
+
+async def crawl_with_optimizations(url):
+    async with Crawl4aiDockerClient() as client:
+        result = await client.crawl(
+            [url],
+            hooks={
+                "on_page_context_created": CrawlHooks.block_images,
+                "before_retrieve_html": CrawlHooks.scroll_infinite
+            }
+        )
+        return result
+```
+
+#### Choosing the Right Approach
+
+| Approach | Best For | IDE Support | Language |
+|----------|----------|-------------|----------|
+| **String-based** | Non-Python clients, REST APIs, other languages | ❌ None | Any |
+| **Function-based** | Python applications, local development | ✅ Full | Python only |
+| **Docker Client** | Python apps with automatic conversion | ✅ Full | Python only |
+
+**Recommendation**:
+- **Python applications**: Use Docker client with function objects (easiest)
+- **Non-Python or REST API**: Use string-based hooks (most flexible)
+- **Manual control**: Use `hooks_to_string()` utility (middle ground)
+
+#### Complete Example with Function Hooks
+
+```python
+from crawl4ai import Crawl4aiDockerClient, BrowserConfig, CrawlerRunConfig, CacheMode
+
+# Define hooks as regular Python functions
+async def setup_environment(page, context, **kwargs):
+    """Setup crawling environment"""
+    # Set viewport
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+
+    # Block resources for speed
+    await context.route("**/*.{png,jpg,gif}", lambda r: r.abort())
+
+    # Add custom headers
+    await page.set_extra_http_headers({
+        "Accept-Language": "en-US",
+        "X-Custom-Header": "Crawl4AI"
+    })
+
+    print("[HOOK] Environment configured")
+    return page
+
+async def extract_content(page, context, **kwargs):
+    """Extract and prepare content"""
+    # Scroll to load lazy content
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+
+    # Extract metadata
+    metadata = await page.evaluate('''() => ({
+        title: document.title,
+        links: document.links.length,
+        images: document.images.length
+    })''')
+
+    print(f"[HOOK] Page metadata: {metadata}")
+    return page
+
+async def main():
+    async with Crawl4aiDockerClient(base_url="http://localhost:11235", verbose=True) as client:
+        # Configure crawl
+        browser_config = BrowserConfig(headless=True)
+        crawler_config = CrawlerRunConfig(cache_mode=CacheMode.BYPASS)
+
+        # Crawl with hooks
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            browser_config=browser_config,
+            crawler_config=crawler_config,
+            hooks={
+                "on_page_context_created": setup_environment,
+                "before_retrieve_html": extract_content
+            },
+            hooks_timeout=30
+        )
+
+        if result.success:
+            print(f"✅ Crawl successful!")
+            print(f"   URL: {result.url}")
+            print(f"   HTML: {len(result.html)} chars")
+            print(f"   Markdown: {len(result.markdown)} chars")
+        else:
+            print(f"❌ Crawl failed: {result.error_message}")
+
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(main())
+```
+
+#### Additional Resources
+
+- **Comprehensive Examples**: See `/docs/examples/hooks_docker_client_example.py` for Python function-based examples
+- **REST API Examples**: See `/docs/examples/hooks_rest_api_example.py` for string-based examples
+- **Comparison Guide**: See `/docs/examples/README_HOOKS.md` for detailed comparison
+- **Utility Documentation**: See `/docs/hooks-utility-guide.md` for complete guide
+
+---
+
+## 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
@@ -892,10 +1634,12 @@ This is the easiest way to translate Python configuration to JSON requests when
 
 Install the SDK: `pip install crawl4ai`
 
+The Python SDK provides a convenient way to interact with the Docker API, including **automatic hook conversion** when using function objects.
+
 ```python
 import asyncio
 from crawl4ai.docker_client import Crawl4aiDockerClient
-from crawl4ai import BrowserConfig, CrawlerRunConfig, CacheMode # Assuming you have crawl4ai installed
+from crawl4ai import BrowserConfig, CrawlerRunConfig, CacheMode
 
 async def main():
     # Point to the correct server port
@@ -907,23 +1651,22 @@ async def main():
         print("--- Running Non-Streaming Crawl ---")
         results = await client.crawl(
             ["https://httpbin.org/html"],
-            browser_config=BrowserConfig(headless=True), # Use library classes for config aid
+            browser_config=BrowserConfig(headless=True),
             crawler_config=CrawlerRunConfig(cache_mode=CacheMode.BYPASS)
         )
-        if results: # client.crawl returns None on failure
+        if results:
-          print(f"Non-streaming results success: {results.success}")
+            print(f"Non-streaming results success: {results.success}")
-          if results.success:
+            if results.success:
-              for result in results: # Iterate through the CrawlResultContainer
+                for result in results:
-                  print(f"URL: {result.url}, Success: {result.success}")
+                    print(f"URL: {result.url}, Success: {result.success}")
         else:
             print("Non-streaming crawl failed.")
 
-
         # Example Streaming crawl
         print("\n--- Running Streaming Crawl ---")
         stream_config = CrawlerRunConfig(stream=True, cache_mode=CacheMode.BYPASS)
         try:
-            async for result in await client.crawl( # client.crawl returns an async generator for streaming
+            async for result in await client.crawl(
                 ["https://httpbin.org/html", "https://httpbin.org/links/5/0"],
                 browser_config=BrowserConfig(headless=True),
                 crawler_config=stream_config
@@ -932,17 +1675,56 @@ async def main():
         except Exception as e:
             print(f"Streaming crawl failed: {e}")
 
+        # Example with hooks (Python function objects)
+        print("\n--- Crawl with Hooks ---")
+
+        async def my_hook(page, context, **kwargs):
+            """Custom hook to optimize performance"""
+            await page.set_viewport_size({"width": 1920, "height": 1080})
+            await context.route("**/*.{png,jpg}", lambda r: r.abort())
+            print("[HOOK] Page optimized")
+            return page
+
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            browser_config=BrowserConfig(headless=True),
+            crawler_config=CrawlerRunConfig(cache_mode=CacheMode.BYPASS),
+            hooks={"on_page_context_created": my_hook},  # Pass function directly!
+            hooks_timeout=30
+        )
+        print(f"Crawl with hooks success: {result.success}")
 
         # Example Get schema
         print("\n--- Getting Schema ---")
         schema = await client.get_schema()
-        print(f"Schema received: {bool(schema)}") # Print whether schema was received
+        print(f"Schema received: {bool(schema)}")
 
 if __name__ == "__main__":
     asyncio.run(main())
 ```
 
-*(SDK parameters like timeout, verify_ssl etc. remain the same)*
+#### SDK Parameters
+
+The Docker client supports the following parameters:
+
+**Client Initialization**:
+- `base_url` (str): URL of the Docker server (default: `http://localhost:8000`)
+- `timeout` (float): Request timeout in seconds (default: 30.0)
+- `verify_ssl` (bool): Verify SSL certificates (default: True)
+- `verbose` (bool): Enable verbose logging (default: True)
+- `log_file` (Optional[str]): Path to log file (default: None)
+
+**crawl() Method**:
+- `urls` (List[str]): List of URLs to crawl
+- `browser_config` (Optional[BrowserConfig]): Browser configuration
+- `crawler_config` (Optional[CrawlerRunConfig]): Crawler configuration
+- `hooks` (Optional[Dict]): Hook functions or strings - **automatically converts function objects!**
+- `hooks_timeout` (int): Timeout for each hook execution in seconds (default: 30)
+
+**Returns**:
+- Single URL: `CrawlResult` object
+- Multiple URLs: `List[CrawlResult]`
+- Streaming: `AsyncGenerator[CrawlResult]`
 
 ### Second Approach: Direct API Calls
 
@@ -1352,19 +2134,40 @@ We're here to help you succeed with Crawl4AI! Here's how to get support:
 
 In this guide, we've covered everything you need to get started with Crawl4AI's Docker deployment:
 - Building and running the Docker container
-- Configuring the environment  
+- Configuring the environment
 - Using the interactive playground for testing
 - Making API requests with proper typing
-- Using the Python SDK
+- Using the Python SDK with **automatic hook conversion**
+- **Working with hooks** - both string-based (REST API) and function-based (Python SDK)
 - Leveraging specialized endpoints for screenshots, PDFs, and JavaScript execution
 - Connecting via the Model Context Protocol (MCP)
 - Monitoring your deployment
 
-The new playground interface at `http://localhost:11235/playground` makes it much easier to test configurations and generate the corresponding JSON for API requests.
+### Key Features
 
-For AI application developers, the MCP integration allows tools like Claude Code to directly access Crawl4AI's capabilities without complex API handling.
+**Hooks Support**: Crawl4AI offers two approaches for working with hooks:
+- **String-based** (REST API): Works with any language, requires manual string formatting
+- **Function-based** (Python SDK): Write hooks as regular Python functions with full IDE support and automatic conversion
 
-Remember, the examples in the `examples` folder are your friends - they show real-world usage patterns that you can adapt for your needs.
+**Playground Interface**: The built-in playground at `http://localhost:11235/playground` makes it easy to test configurations and generate corresponding JSON for API requests.
+
+**MCP Integration**: For AI application developers, the MCP integration allows tools like Claude Code to directly access Crawl4AI's capabilities without complex API handling.
+
+### Next Steps
+
+1. **Explore Examples**: Check out the comprehensive examples in:
+   - `/docs/examples/hooks_docker_client_example.py` - Python function-based hooks
+   - `/docs/examples/hooks_rest_api_example.py` - REST API string-based hooks
+   - `/docs/examples/README_HOOKS.md` - Comparison and guide
+
+2. **Read Documentation**:
+   - `/docs/hooks-utility-guide.md` - Complete hooks utility guide
+   - API documentation for detailed configuration options
+
+3. **Join the Community**:
+   - GitHub: Report issues and contribute
+   - Discord: Get help and share your experiences
+   - Documentation: Comprehensive guides and tutorials
 
 Keep exploring, and don't hesitate to reach out if you need help! We're building something amazing together. 🚀
 

docs/md_v2/index.md

@@ -59,6 +59,27 @@ Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant
 
 > **Note**: If you're looking for the old documentation, you can access it [here](https://old.docs.crawl4ai.com).
 
+## 🆕 AI Assistant Skill Now Available!
+
+<div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 20px; border-radius: 10px; margin: 20px 0; box-shadow: 0 4px 6px rgba(0,0,0,0.1);">
+  <h3 style="color: white; margin: 0 0 10px 0;">🤖 Crawl4AI Skill for Claude & AI Assistants</h3>
+  <p style="color: white; margin: 10px 0;">Supercharge your AI coding assistant with complete Crawl4AI knowledge! Download our comprehensive skill package that includes:</p>
+  <ul style="color: white; margin: 10px 0;">
+    <li>📚 Complete SDK reference (23K+ words)</li>
+    <li>🚀 Ready-to-use extraction scripts</li>
+    <li>⚡ Schema generation for efficient scraping</li>
+    <li>🔧 Version 0.7.4 compatible</li>
+  </ul>
+  <div style="text-align: center; margin-top: 15px;">
+    <a href="assets/crawl4ai-skill.zip" download style="background: white; color: #667eea; padding: 12px 30px; border-radius: 5px; text-decoration: none; font-weight: bold; display: inline-block; transition: transform 0.2s;">
+      📦 Download Skill Package
+    </a>
+  </div>
+  <p style="color: white; margin: 15px 0 0 0; font-size: 0.9em; text-align: center;">
+    Works with Claude, Cursor, Windsurf, and other AI coding assistants. Import the .zip file into your AI assistant's skill/knowledge system.
+  </p>
+</div>
+
 ## 🎯 New: Adaptive Web Crawling
 
 Crawl4AI now features intelligent adaptive crawling that knows when to stop! Using advanced information foraging algorithms, it determines when sufficient information has been gathered to answer your query.

docs/md_v2/marketplace/admin/admin.js

@@ -529,8 +529,19 @@ class AdminDashboard {
                     </label>
                 </div>
                 <div class="form-group full-width">
-                    <label>Integration Guide</label>
+                    <label>Long Description (Markdown - Overview tab)</label>
-                    <textarea id="form-integration" rows="10">${app?.integration_guide || ''}</textarea>
+                    <textarea id="form-long-description" rows="10" placeholder="Enter detailed description with markdown formatting...">${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>
                 </div>
             </div>
         `;
@@ -712,7 +723,9 @@ 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);

docs/md_v2/marketplace/app-detail.css

@@ -510,6 +510,31 @@
     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;

docs/md_v2/marketplace/app-detail.html

@@ -80,20 +80,7 @@
                 <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">
@@ -142,33 +129,14 @@
                 </section>
 
                 <section id="integration-tab" class="tab-content">
-                    <div class="integration-content">
+                    <div class="integration-content" id="app-integration">
-                        <h2>Integration Guide</h2>
+                        <!-- Integration guide markdown content will be rendered here -->
-
-                        <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">
+                    <div class="docs-content" id="app-docs">
-                        <h2>Documentation</h2>
+                        <!-- Documentation markdown content will be rendered here -->
-                        <div id="app-docs" class="doc-sections">
-                            <p>Documentation coming soon.</p>
-                        </div>
                     </div>
                 </section>
 

docs/md_v2/marketplace/app-detail.js

@@ -123,144 +123,132 @@ class AppDetailPage {
         document.getElementById('sidebar-pricing').textContent = this.appData.pricing || 'Free';
         document.getElementById('sidebar-contact').textContent = this.appData.contact_email || 'contact@example.com';
 
-        // Integration guide
+        // Render tab contents from database fields
-        this.renderIntegrationGuide();
+        this.renderTabContents();
     }
 
-    renderIntegrationGuide() {
+    renderTabContents() {
-        // Installation code
+        // Overview tab - use long_description from database
-        const installCode = document.getElementById('install-code');
+        const overviewDiv = document.getElementById('app-overview');
-        if (installCode) {
+        if (overviewDiv) {
-            if (this.appData.type === 'Open Source' && this.appData.github_url) {
+            if (this.appData.long_description) {
-                installCode.textContent = `# Clone from GitHub
+                overviewDiv.innerHTML = this.renderMarkdown(this.appData.long_description);
-git clone ${this.appData.github_url}
+            } else {
-
+                overviewDiv.innerHTML = `<p>${this.appData.description || 'No overview available.'}</p>`;
-# 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'}`;
             }
         }
 
-        // Usage code - customize based on category
+        // Integration tab - use integration_guide field from database
-        const usageCode = document.getElementById('usage-code');
+        const integrationDiv = document.getElementById('app-integration');
-        if (usageCode) {
+        if (integrationDiv) {
-            if (this.appData.category === 'Browser Automation') {
+            if (this.appData.integration_guide) {
-                usageCode.textContent = `from crawl4ai import AsyncWebCrawler
+                integrationDiv.innerHTML = this.renderMarkdown(this.appData.integration_guide);
-from ${this.appData.slug.replace(/-/g, '_')} import ${this.appData.name.replace(/\s+/g, '')}
+                // Add copy buttons to all code blocks
-
+                this.addCopyButtonsToCodeBlocks(integrationDiv);
-async def main():
+            } else {
-    # Initialize ${this.appData.name}
+                integrationDiv.innerHTML = '<p>Integration guide not yet available. Please check the official website for details.</p>';
-    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)`;
             }
         }
 
-        // Integration example
+        // Documentation tab - use documentation field from database
-        const integrationCode = document.getElementById('integration-code');
+        const docsDiv = document.getElementById('app-docs');
-        if (integrationCode) {
+        if (docsDiv) {
-            integrationCode.textContent = this.appData.integration_guide ||
+            if (this.appData.documentation) {
-`# Complete ${this.appData.name} Integration Example
+                docsDiv.innerHTML = this.renderMarkdown(this.appData.documentation);
-
+                // Add copy buttons to all code blocks
-from crawl4ai import AsyncWebCrawler
+                this.addCopyButtonsToCodeBlocks(docsDiv);
-from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
+            } else {
-import json
+                docsDiv.innerHTML = '<p>Documentation coming soon.</p>';
-
+            }
-async def crawl_with_${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}
+    addCopyButtonsToCodeBlocks(container) {
-    async with AsyncWebCrawler(
+        // Find all code blocks and add copy buttons
-        browser_type="chromium",
+        const codeBlocks = container.querySelectorAll('pre code');
-        headless=True,
+        codeBlocks.forEach(codeBlock => {
-        verbose=True
+            const pre = codeBlock.parentElement;
-    ) as crawler:
 
-        # Crawl with extraction
+            // Skip if already has a copy button
-        result = await crawler.arun(
+            if (pre.querySelector('.copy-btn')) return;
-            url="https://example.com/products",
-            extraction_strategy=JsonCssExtractionStrategy(schema),
-            cache_mode="bypass",
-            wait_for="css:.product",
-            screenshot=True
-        )
 
-        # Process results
+            // Create copy button
-        if result.success:
+            const copyBtn = document.createElement('button');
-            products = json.loads(result.extracted_content)
+            copyBtn.className = 'copy-btn';
-            print(f"Found {len(products)} products")
+            copyBtn.textContent = 'Copy';
+            copyBtn.onclick = () => {
+                navigator.clipboard.writeText(codeBlock.textContent).then(() => {
+                    copyBtn.textContent = '✓ Copied!';
+                    setTimeout(() => {
+                        copyBtn.textContent = 'Copy';
+                    }, 2000);
+                });
+            };
 
-            for product in products[:5]:
+            // Add button to pre element
-                print(f"- {product['title']}: {product['price']}")
+            pre.style.position = 'relative';
+            pre.insertBefore(copyBtn, codeBlock);
+        });
+    }
 
-        return products
+    renderMarkdown(text) {
+        if (!text) return '';
 
-# Run the crawler
+        // Store code blocks temporarily to protect them from processing
-if __name__ == "__main__":
+        const codeBlocks = [];
-    import asyncio
+        let processed = text.replace(/```(\w+)?\n([\s\S]*?)```/g, (match, lang, code) => {
-    asyncio.run(crawl_with_${this.appData.slug.replace(/-/g, '_')}())`;
+            const placeholder = `___CODE_BLOCK_${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) {
@@ -289,33 +277,6 @@ if __name__ == "__main__":
                 document.getElementById(`${tabName}-tab`).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);
-                });
-            });
-        });
     }
 
     async loadRelatedApps() {

docs/releases_review/demo_v0.7.5.py

@@ -0,0 +1,338 @@
+"""
+🚀 Crawl4AI v0.7.5 Release Demo - Working Examples
+==================================================
+This demo showcases key features introduced in v0.7.5 with real, executable examples.
+
+Featured Demos:
+1. ✅ Docker Hooks System - Real API calls with custom hooks (string & function-based)
+2. ✅ Enhanced LLM Integration - Working LLM configurations
+3. ✅ HTTPS Preservation - Live crawling with HTTPS maintenance
+
+Requirements:
+- crawl4ai v0.7.5 installed
+- Docker running with crawl4ai image (optional for Docker demos)
+- Valid API keys for LLM demos (optional)
+"""
+
+import asyncio
+import requests
+import time
+import sys
+
+from crawl4ai import (AsyncWebCrawler, CrawlerRunConfig, BrowserConfig,
+                      CacheMode, FilterChain, URLPatternFilter, BFSDeepCrawlStrategy,
+                      hooks_to_string)
+from crawl4ai.docker_client import Crawl4aiDockerClient
+    
+
+def print_section(title: str, description: str = ""):
+    """Print a section header"""
+    print(f"\n{'=' * 60}")
+    print(f"{title}")
+    if description:
+        print(f"{description}")
+    print(f"{'=' * 60}\n")
+
+
+async def demo_1_docker_hooks_system():
+    """Demo 1: Docker Hooks System - Real API calls with custom hooks"""
+    print_section(
+        "Demo 1: Docker Hooks System",
+        "Testing both string-based and function-based hooks (NEW in v0.7.5!)"
+    )
+
+    # Check Docker service availability
+    def check_docker_service():
+        try:
+            response = requests.get("http://localhost:11235/", timeout=3)
+            return response.status_code == 200
+        except:
+            return False
+
+    print("Checking Docker service...")
+    docker_running = check_docker_service()
+
+    if not docker_running:
+        print("⚠️  Docker service not running on localhost:11235")
+        print("To test Docker hooks:")
+        print("1. Run: docker run -p 11235:11235 unclecode/crawl4ai:latest")
+        print("2. Wait for service to start")
+        print("3. Re-run this demo\n")
+        return
+
+    print("✓ Docker service detected!")
+
+    # ============================================================================
+    # PART 1: Traditional String-Based Hooks (Works with REST API)
+    # ============================================================================
+    print("\n" + "─" * 60)
+    print("Part 1: String-Based Hooks (REST API)")
+    print("─" * 60)
+
+    hooks_config_string = {
+        "on_page_context_created": """
+async def hook(page, context, **kwargs):
+    print("[String Hook] Setting up page context")
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    return page
+""",
+        "before_retrieve_html": """
+async def hook(page, context, **kwargs):
+    print("[String Hook] Before retrieving HTML")
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    return page
+"""
+    }
+
+    payload = {
+        "urls": ["https://httpbin.org/html"],
+        "hooks": {
+            "code": hooks_config_string,
+            "timeout": 30
+        }
+    }
+
+    print("🔧 Using string-based hooks for REST API...")
+    try:
+        start_time = time.time()
+        response = requests.post("http://localhost:11235/crawl", json=payload, timeout=60)
+        execution_time = time.time() - start_time
+
+        if response.status_code == 200:
+            result = response.json()
+            print(f"✅ String-based hooks executed in {execution_time:.2f}s")
+            if result.get('results') and result['results'][0].get('success'):
+                html_length = len(result['results'][0].get('html', ''))
+                print(f"   📄 HTML length: {html_length} characters")
+        else:
+            print(f"❌ Request failed: {response.status_code}")
+    except Exception as e:
+        print(f"❌ Error: {str(e)}")
+
+    # ============================================================================
+    # PART 2: NEW Function-Based Hooks with Docker Client (v0.7.5)
+    # ============================================================================
+    print("\n" + "─" * 60)
+    print("Part 2: Function-Based Hooks with Docker Client (✨ NEW!)")
+    print("─" * 60)
+
+    # Define hooks as regular Python functions
+    async def on_page_context_created_func(page, context, **kwargs):
+        """Block images to speed up crawling"""
+        print("[Function Hook] Setting up page context")
+        await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+        await page.set_viewport_size({"width": 1920, "height": 1080})
+        return page
+
+    async def before_goto_func(page, context, url, **kwargs):
+        """Add custom headers before navigation"""
+        print(f"[Function Hook] About to navigate to {url}")
+        await page.set_extra_http_headers({
+            'X-Crawl4AI': 'v0.7.5-function-hooks',
+            'X-Test-Header': 'demo'
+        })
+        return page
+
+    async def before_retrieve_html_func(page, context, **kwargs):
+        """Scroll to load lazy content"""
+        print("[Function Hook] Scrolling page for lazy-loaded content")
+        await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+        await page.wait_for_timeout(500)
+        await page.evaluate("window.scrollTo(0, 0)")
+        return page
+
+    # Use the hooks_to_string utility (can be used standalone)
+    print("\n📦 Converting functions to strings with hooks_to_string()...")
+    hooks_as_strings = hooks_to_string({
+        "on_page_context_created": on_page_context_created_func,
+        "before_goto": before_goto_func,
+        "before_retrieve_html": before_retrieve_html_func
+    })
+    print(f"   ✓ Converted {len(hooks_as_strings)} hooks to string format")
+
+    # OR use Docker Client which does conversion automatically!
+    print("\n🐳 Using Docker Client with automatic conversion...")
+    try:
+        client = Crawl4aiDockerClient(base_url="http://localhost:11235")
+
+        # Pass function objects directly - conversion happens automatically!
+        results = await client.crawl(
+            urls=["https://httpbin.org/html"],
+            hooks={
+                "on_page_context_created": on_page_context_created_func,
+                "before_goto": before_goto_func,
+                "before_retrieve_html": before_retrieve_html_func
+            },
+            hooks_timeout=30
+        )
+
+        if results and results.success:
+            print(f"✅ Function-based hooks executed successfully!")
+            print(f"   📄 HTML length: {len(results.html)} characters")
+            print(f"   🎯 URL: {results.url}")
+        else:
+            print("⚠️ Crawl completed but may have warnings")
+
+    except Exception as e:
+        print(f"❌ Docker client error: {str(e)}")
+
+    # Show the benefits
+    print("\n" + "=" * 60)
+    print("✨ Benefits of Function-Based Hooks:")
+    print("=" * 60)
+    print("✓ Full IDE support (autocomplete, syntax highlighting)")
+    print("✓ Type checking and linting")
+    print("✓ Easier to test and debug")
+    print("✓ Reusable across projects")
+    print("✓ Automatic conversion in Docker client")
+    print("=" * 60)
+
+
+async def demo_2_enhanced_llm_integration():
+    """Demo 2: Enhanced LLM Integration - Working LLM configurations"""
+    print_section(
+        "Demo 2: Enhanced LLM Integration",
+        "Testing custom LLM providers and configurations"
+    )
+
+    print("🤖 Testing Enhanced LLM Integration Features")
+
+    provider = "gemini/gemini-2.5-flash-lite"
+    payload = {
+        "url": "https://example.com",
+        "f": "llm",
+        "q": "Summarize this page in one sentence.",
+        "provider": provider,  # Explicitly set provider
+        "temperature": 0.7
+    }
+    try:
+        response = requests.post(
+            "http://localhost:11235/md",
+            json=payload,
+            timeout=60
+        )
+        if response.status_code == 200:
+            result = response.json()
+            print(f"✓ Request successful with provider: {provider}")
+            print(f"  - Response keys: {list(result.keys())}")
+            print(f"  - Content length: {len(result.get('markdown', ''))} characters")
+            print(f"  - Note: Actual LLM call may fail without valid API key")
+        else:
+            print(f"❌ Request failed: {response.status_code}")
+            print(f"  - Response: {response.text[:500]}")
+            
+    except Exception as e:
+        print(f"[red]Error: {e}[/]")
+
+
+async def demo_3_https_preservation():
+    """Demo 3: HTTPS Preservation - Live crawling with HTTPS maintenance"""
+    print_section(
+        "Demo 3: HTTPS Preservation",
+        "Testing HTTPS preservation for internal links"
+    )
+
+    print("🔒 Testing HTTPS Preservation Feature")
+
+    # Test with HTTPS preservation enabled
+    print("\nTest 1: HTTPS Preservation ENABLED")
+
+    url_filter = URLPatternFilter(
+        patterns=["^(https:\/\/)?quotes\.toscrape\.com(\/.*)?$"]
+    )
+    config = CrawlerRunConfig(
+        exclude_external_links=True, 
+        stream=True, 
+        verbose=False,
+        preserve_https_for_internal_links=True,
+        deep_crawl_strategy=BFSDeepCrawlStrategy(
+            max_depth=2, 
+            max_pages=5,
+            filter_chain=FilterChain([url_filter])
+        )
+    )
+
+    test_url = "https://quotes.toscrape.com"
+    print(f"🎯 Testing URL: {test_url}")
+
+    async with AsyncWebCrawler() as crawler:
+        async for result in await crawler.arun(url=test_url, config=config):
+            print("✓ HTTPS Preservation Test Completed")
+            internal_links = [i['href'] for i in result.links['internal']]
+            for link in internal_links:
+                print(f"  → {link}")
+
+
+async def main():
+    """Run all demos"""
+    print("\n" + "=" * 60)
+    print("🚀 Crawl4AI v0.7.5 Working Demo")
+    print("=" * 60)
+
+    # Check system requirements
+    print("🔍 System Requirements Check:")
+    print(f"  - Python version: {sys.version.split()[0]} {'✓' if sys.version_info >= (3, 10) else '❌ (3.10+ required)'}")
+
+    try:
+        import requests
+        print(f"  - Requests library: ✓")
+    except ImportError:
+        print(f"  - Requests library: ❌")
+
+    print()
+
+    demos = [
+        ("Docker Hooks System", demo_1_docker_hooks_system),
+        ("Enhanced LLM Integration", demo_2_enhanced_llm_integration),
+        ("HTTPS Preservation", demo_3_https_preservation),
+    ]
+
+    for i, (name, demo_func) in enumerate(demos, 1):
+        try:
+            print(f"\n📍 Starting Demo {i}/{len(demos)}: {name}")
+            await demo_func()
+
+            if i < len(demos):
+                print(f"\n✨ Demo {i} complete! Press Enter for next demo...")
+                input()
+
+        except KeyboardInterrupt:
+            print(f"\n⏹️  Demo interrupted by user")
+            break
+        except Exception as e:
+            print(f"❌ Demo {i} error: {str(e)}")
+            print("Continuing to next demo...")
+            continue
+
+    print("\n" + "=" * 60)
+    print("🎉 Demo Complete!")
+    print("=" * 60)
+    print("You've experienced the power of Crawl4AI v0.7.5!")
+    print("")
+    print("Key Features Demonstrated:")
+    print("🔧 Docker Hooks - String-based & function-based (NEW!)")
+    print("   • hooks_to_string() utility for function conversion")
+    print("   • Docker client with automatic conversion")
+    print("   • Full IDE support and type checking")
+    print("🤖 Enhanced LLM - Better AI integration")
+    print("🔒 HTTPS Preservation - Secure link handling")
+    print("")
+    print("Ready to build something amazing? 🚀")
+    print("")
+    print("📖 Docs: https://docs.crawl4ai.com/")
+    print("🐙 GitHub: https://github.com/unclecode/crawl4ai")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    print("🚀 Crawl4AI v0.7.5 Live Demo Starting...")
+    print("Press Ctrl+C anytime to exit\n")
+
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\n👋 Demo stopped by user. Thanks for trying Crawl4AI v0.7.5!")
+    except Exception as e:
+        print(f"\n❌ Demo error: {str(e)}")
+        print("Make sure you have the required dependencies installed.")

docs/releases_review/demo_v0.7.6.py

@@ -0,0 +1,359 @@
+#!/usr/bin/env python3
+"""
+Crawl4AI v0.7.6 Release Demo
+============================
+
+This demo showcases the major feature in v0.7.6:
+**Webhook Support for Docker Job Queue API**
+
+Features Demonstrated:
+1. Asynchronous job processing with webhook notifications
+2. Webhook support for /crawl/job endpoint
+3. Webhook support for /llm/job endpoint
+4. Notification-only vs data-in-payload modes
+5. Custom webhook headers for authentication
+6. Structured extraction with JSON schemas
+7. Exponential backoff retry for reliable delivery
+
+Prerequisites:
+- Crawl4AI Docker container running on localhost:11235
+- Flask installed: pip install flask requests
+- LLM API key configured (for LLM examples)
+
+Usage:
+python docs/releases_review/demo_v0.7.6.py
+"""
+
+import requests
+import json
+import time
+from flask import Flask, request, jsonify
+from threading import Thread
+
+# Configuration
+CRAWL4AI_BASE_URL = "http://localhost:11235"
+WEBHOOK_BASE_URL = "http://localhost:8080"
+
+# Flask app for webhook receiver
+app = Flask(__name__)
+received_webhooks = []
+
+
+@app.route('/webhook', methods=['POST'])
+def webhook_handler():
+    """Universal webhook handler for both crawl and LLM extraction jobs."""
+    payload = request.json
+    task_id = payload['task_id']
+    task_type = payload['task_type']
+    status = payload['status']
+
+    print(f"\n{'='*70}")
+    print(f"📬 Webhook Received!")
+    print(f"   Task ID: {task_id}")
+    print(f"   Task Type: {task_type}")
+    print(f"   Status: {status}")
+    print(f"   Timestamp: {payload['timestamp']}")
+
+    if status == 'completed':
+        if 'data' in payload:
+            print(f"   ✅ Data included in webhook")
+            if task_type == 'crawl':
+                results = payload['data'].get('results', [])
+                print(f"   📊 Crawled {len(results)} URL(s)")
+            elif task_type == 'llm_extraction':
+                extracted = payload['data'].get('extracted_content', {})
+                print(f"   🤖 Extracted: {json.dumps(extracted, indent=6)}")
+        else:
+            print(f"   📥 Notification only (fetch data separately)")
+    elif status == 'failed':
+        print(f"   ❌ Error: {payload.get('error', 'Unknown')}")
+
+    print(f"{'='*70}\n")
+    received_webhooks.append(payload)
+
+    return jsonify({"status": "received"}), 200
+
+
+def start_webhook_server():
+    """Start Flask webhook server in background."""
+    app.run(host='0.0.0.0', port=8080, debug=False, use_reloader=False)
+
+
+def demo_1_crawl_webhook_notification_only():
+    """Demo 1: Crawl job with webhook notification (data fetched separately)."""
+    print("\n" + "="*70)
+    print("DEMO 1: Crawl Job - Webhook Notification Only")
+    print("="*70)
+    print("Submitting crawl job with webhook notification...")
+
+    payload = {
+        "urls": ["https://example.com"],
+        "browser_config": {"headless": True},
+        "crawler_config": {"cache_mode": "bypass"},
+        "webhook_config": {
+            "webhook_url": f"{WEBHOOK_BASE_URL}/webhook",
+            "webhook_data_in_payload": False,
+            "webhook_headers": {
+                "X-Demo": "v0.7.6",
+                "X-Type": "crawl"
+            }
+        }
+    }
+
+    response = requests.post(f"{CRAWL4AI_BASE_URL}/crawl/job", json=payload)
+    if response.ok:
+        task_id = response.json()['task_id']
+        print(f"✅ Job submitted: {task_id}")
+        print("⏳ Webhook will notify when complete...")
+        return task_id
+    else:
+        print(f"❌ Failed: {response.text}")
+        return None
+
+
+def demo_2_crawl_webhook_with_data():
+    """Demo 2: Crawl job with full data in webhook payload."""
+    print("\n" + "="*70)
+    print("DEMO 2: Crawl Job - Webhook with Full Data")
+    print("="*70)
+    print("Submitting crawl job with data included in webhook...")
+
+    payload = {
+        "urls": ["https://www.python.org"],
+        "browser_config": {"headless": True},
+        "crawler_config": {"cache_mode": "bypass"},
+        "webhook_config": {
+            "webhook_url": f"{WEBHOOK_BASE_URL}/webhook",
+            "webhook_data_in_payload": True,
+            "webhook_headers": {
+                "X-Demo": "v0.7.6",
+                "X-Type": "crawl-with-data"
+            }
+        }
+    }
+
+    response = requests.post(f"{CRAWL4AI_BASE_URL}/crawl/job", json=payload)
+    if response.ok:
+        task_id = response.json()['task_id']
+        print(f"✅ Job submitted: {task_id}")
+        print("⏳ Webhook will include full results...")
+        return task_id
+    else:
+        print(f"❌ Failed: {response.text}")
+        return None
+
+
+def demo_3_llm_webhook_notification_only():
+    """Demo 3: LLM extraction with webhook notification (NEW in v0.7.6!)."""
+    print("\n" + "="*70)
+    print("DEMO 3: LLM Extraction - Webhook Notification Only (NEW!)")
+    print("="*70)
+    print("Submitting LLM extraction job with webhook notification...")
+
+    payload = {
+        "url": "https://www.example.com",
+        "q": "Extract the main heading and description from this page",
+        "provider": "openai/gpt-4o-mini",
+        "cache": False,
+        "webhook_config": {
+            "webhook_url": f"{WEBHOOK_BASE_URL}/webhook",
+            "webhook_data_in_payload": False,
+            "webhook_headers": {
+                "X-Demo": "v0.7.6",
+                "X-Type": "llm"
+            }
+        }
+    }
+
+    response = requests.post(f"{CRAWL4AI_BASE_URL}/llm/job", json=payload)
+    if response.ok:
+        task_id = response.json()['task_id']
+        print(f"✅ Job submitted: {task_id}")
+        print("⏳ Webhook will notify when LLM extraction completes...")
+        return task_id
+    else:
+        print(f"❌ Failed: {response.text}")
+        return None
+
+
+def demo_4_llm_webhook_with_schema():
+    """Demo 4: LLM extraction with JSON schema and data in webhook (NEW in v0.7.6!)."""
+    print("\n" + "="*70)
+    print("DEMO 4: LLM Extraction - Schema + Full Data in Webhook (NEW!)")
+    print("="*70)
+    print("Submitting LLM extraction with JSON schema...")
+
+    schema = {
+        "type": "object",
+        "properties": {
+            "title": {"type": "string", "description": "Page title"},
+            "description": {"type": "string", "description": "Page description"},
+            "main_topics": {
+                "type": "array",
+                "items": {"type": "string"},
+                "description": "Main topics covered"
+            }
+        },
+        "required": ["title"]
+    }
+
+    payload = {
+        "url": "https://www.python.org",
+        "q": "Extract the title, description, and main topics from this website",
+        "schema": json.dumps(schema),
+        "provider": "openai/gpt-4o-mini",
+        "cache": False,
+        "webhook_config": {
+            "webhook_url": f"{WEBHOOK_BASE_URL}/webhook",
+            "webhook_data_in_payload": True,
+            "webhook_headers": {
+                "X-Demo": "v0.7.6",
+                "X-Type": "llm-with-schema"
+            }
+        }
+    }
+
+    response = requests.post(f"{CRAWL4AI_BASE_URL}/llm/job", json=payload)
+    if response.ok:
+        task_id = response.json()['task_id']
+        print(f"✅ Job submitted: {task_id}")
+        print("⏳ Webhook will include structured extraction results...")
+        return task_id
+    else:
+        print(f"❌ Failed: {response.text}")
+        return None
+
+
+def demo_5_global_webhook_config():
+    """Demo 5: Using global webhook configuration from config.yml."""
+    print("\n" + "="*70)
+    print("DEMO 5: Global Webhook Configuration")
+    print("="*70)
+    print("💡 You can configure a default webhook URL in config.yml:")
+    print("""
+    webhooks:
+      enabled: true
+      default_url: "https://myapp.com/webhooks/default"
+      data_in_payload: false
+      retry:
+        max_attempts: 5
+        initial_delay_ms: 1000
+        max_delay_ms: 32000
+        timeout_ms: 30000
+    """)
+    print("Then submit jobs WITHOUT webhook_config - they'll use the default!")
+    print("This is useful for consistent webhook handling across all jobs.")
+
+
+def demo_6_webhook_retry_logic():
+    """Demo 6: Webhook retry mechanism with exponential backoff."""
+    print("\n" + "="*70)
+    print("DEMO 6: Webhook Retry Logic")
+    print("="*70)
+    print("🔄 Webhook delivery uses exponential backoff retry:")
+    print("   • Max attempts: 5")
+    print("   • Delays: 1s → 2s → 4s → 8s → 16s")
+    print("   • Timeout: 30s per attempt")
+    print("   • Retries on: 5xx errors, network errors, timeouts")
+    print("   • No retry on: 4xx client errors")
+    print("\nThis ensures reliable webhook delivery even with temporary failures!")
+
+
+def print_summary():
+    """Print demo summary and results."""
+    print("\n" + "="*70)
+    print("📊 DEMO SUMMARY")
+    print("="*70)
+    print(f"Total webhooks received: {len(received_webhooks)}")
+
+    crawl_webhooks = [w for w in received_webhooks if w['task_type'] == 'crawl']
+    llm_webhooks = [w for w in received_webhooks if w['task_type'] == 'llm_extraction']
+
+    print(f"\nBreakdown:")
+    print(f"  🕷️  Crawl jobs: {len(crawl_webhooks)}")
+    print(f"  🤖 LLM extraction jobs: {len(llm_webhooks)}")
+
+    print(f"\nDetails:")
+    for i, webhook in enumerate(received_webhooks, 1):
+        icon = "🕷️" if webhook['task_type'] == 'crawl' else "🤖"
+        print(f"  {i}. {icon} {webhook['task_id']}: {webhook['status']}")
+
+    print("\n" + "="*70)
+    print("✨ v0.7.6 KEY FEATURES DEMONSTRATED:")
+    print("="*70)
+    print("✅ Webhook support for /crawl/job")
+    print("✅ Webhook support for /llm/job (NEW!)")
+    print("✅ Notification-only mode (fetch data separately)")
+    print("✅ Data-in-payload mode (get full results in webhook)")
+    print("✅ Custom headers for authentication")
+    print("✅ JSON schema for structured LLM extraction")
+    print("✅ Exponential backoff retry for reliable delivery")
+    print("✅ Global webhook configuration support")
+    print("✅ Universal webhook handler for both job types")
+    print("\n💡 Benefits:")
+    print("   • No more polling - get instant notifications")
+    print("   • Better resource utilization")
+    print("   • Reliable delivery with automatic retries")
+    print("   • Consistent API across crawl and LLM jobs")
+    print("   • Production-ready webhook infrastructure")
+
+
+def main():
+    """Run all demos."""
+    print("\n" + "="*70)
+    print("🚀 Crawl4AI v0.7.6 Release Demo")
+    print("="*70)
+    print("Feature: Webhook Support for Docker Job Queue API")
+    print("="*70)
+
+    # Check if server is running
+    try:
+        health = requests.get(f"{CRAWL4AI_BASE_URL}/health", timeout=5)
+        print(f"✅ Crawl4AI server is running")
+    except:
+        print(f"❌ Cannot connect to Crawl4AI at {CRAWL4AI_BASE_URL}")
+        print("Please start Docker container:")
+        print("  docker run -d -p 11235:11235 --env-file .llm.env unclecode/crawl4ai:0.7.6")
+        return
+
+    # Start webhook server
+    print(f"\n🌐 Starting webhook server at {WEBHOOK_BASE_URL}...")
+    webhook_thread = Thread(target=start_webhook_server, daemon=True)
+    webhook_thread.start()
+    time.sleep(2)
+
+    # Run demos
+    demo_1_crawl_webhook_notification_only()
+    time.sleep(5)
+
+    demo_2_crawl_webhook_with_data()
+    time.sleep(5)
+
+    demo_3_llm_webhook_notification_only()
+    time.sleep(5)
+
+    demo_4_llm_webhook_with_schema()
+    time.sleep(5)
+
+    demo_5_global_webhook_config()
+    demo_6_webhook_retry_logic()
+
+    # Wait for webhooks
+    print("\n⏳ Waiting for all webhooks to arrive...")
+    time.sleep(30)
+
+    # Print summary
+    print_summary()
+
+    print("\n" + "="*70)
+    print("✅ Demo completed!")
+    print("="*70)
+    print("\n📚 Documentation:")
+    print("   • deploy/docker/WEBHOOK_EXAMPLES.md")
+    print("   • docs/examples/docker_webhook_example.py")
+    print("\n🔗 Upgrade:")
+    print("   docker pull unclecode/crawl4ai:0.7.6")
+
+
+if __name__ == "__main__":
+    main()

docs/releases_review/v0.7.5_docker_hooks_demo.py

@@ -0,0 +1,655 @@
+#!/usr/bin/env python3
+"""
+🚀 Crawl4AI v0.7.5 - Docker Hooks System Complete Demonstration
+================================================================
+
+This file demonstrates the NEW Docker Hooks System introduced in v0.7.5.
+
+The Docker Hooks System is a completely NEW feature that provides pipeline
+customization through user-provided Python functions. It offers three approaches:
+
+1. String-based hooks for REST API
+2. hooks_to_string() utility to convert functions
+3. Docker Client with automatic conversion (most convenient)
+
+All three approaches are part of this NEW v0.7.5 feature!
+
+Perfect for video recording and demonstration purposes.
+
+Requirements:
+- Docker container running: docker run -p 11235:11235 unclecode/crawl4ai:latest
+- crawl4ai v0.7.5 installed: pip install crawl4ai==0.7.5
+"""
+
+import asyncio
+import requests
+import json
+import time
+from typing import Dict, Any
+
+# Import Crawl4AI components
+from crawl4ai import hooks_to_string
+from crawl4ai.docker_client import Crawl4aiDockerClient
+
+# Configuration
+DOCKER_URL = "http://localhost:11235"
+# DOCKER_URL = "http://localhost:11234"
+TEST_URLS = [
+    # "https://httpbin.org/html",
+    "https://www.kidocode.com",
+    "https://quotes.toscrape.com",
+]
+
+
+def print_section(title: str, description: str = ""):
+    """Print a formatted section header"""
+    print("\n" + "=" * 70)
+    print(f"  {title}")
+    if description:
+        print(f"  {description}")
+    print("=" * 70 + "\n")
+
+
+def check_docker_service() -> bool:
+    """Check if Docker service is running"""
+    try:
+        response = requests.get(f"{DOCKER_URL}/health", timeout=3)
+        return response.status_code == 200
+    except:
+        return False
+
+
+# ============================================================================
+# REUSABLE HOOK LIBRARY (NEW in v0.7.5)
+# ============================================================================
+
+async def performance_optimization_hook(page, context, **kwargs):
+    """
+    Performance Hook: Block unnecessary resources to speed up crawling
+    """
+    print("  [Hook] 🚀 Optimizing performance - blocking images and ads...")
+
+    # Block images
+    await context.route(
+        "**/*.{png,jpg,jpeg,gif,webp,svg,ico}",
+        lambda route: route.abort()
+    )
+
+    # Block ads and analytics
+    await context.route("**/analytics/*", lambda route: route.abort())
+    await context.route("**/ads/*", lambda route: route.abort())
+    await context.route("**/google-analytics.com/*", lambda route: route.abort())
+
+    print("  [Hook] ✓ Performance optimization applied")
+    return page
+
+
+async def viewport_setup_hook(page, context, **kwargs):
+    """
+    Viewport Hook: Set consistent viewport size for rendering
+    """
+    print("  [Hook] 🖥️  Setting viewport to 1920x1080...")
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    print("  [Hook] ✓ Viewport configured")
+    return page
+
+
+async def authentication_headers_hook(page, context, url, **kwargs):
+    """
+    Headers Hook: Add custom authentication and tracking headers
+    """
+    print(f"  [Hook] 🔐 Adding custom headers for {url[:50]}...")
+
+    await page.set_extra_http_headers({
+        'X-Crawl4AI-Version': '0.7.5',
+        'X-Custom-Hook': 'function-based-demo',
+        'Accept-Language': 'en-US,en;q=0.9',
+        'User-Agent': 'Crawl4AI/0.7.5 (Educational Demo)'
+    })
+
+    print("  [Hook] ✓ Custom headers added")
+    return page
+
+
+async def lazy_loading_handler_hook(page, context, **kwargs):
+    """
+    Content Hook: Handle lazy-loaded content by scrolling
+    """
+    print("  [Hook] 📜 Scrolling to load lazy content...")
+
+    # Scroll to bottom
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+
+    # Scroll to middle
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight / 2)")
+    await page.wait_for_timeout(500)
+
+    # Scroll back to top
+    await page.evaluate("window.scrollTo(0, 0)")
+    await page.wait_for_timeout(500)
+
+    print("  [Hook] ✓ Lazy content loaded")
+    return page
+
+
+async def page_analytics_hook(page, context, **kwargs):
+    """
+    Analytics Hook: Log page metrics before extraction
+    """
+    print("  [Hook] 📊 Collecting page analytics...")
+
+    metrics = await page.evaluate('''
+        () => ({
+            title: document.title,
+            images: document.images.length,
+            links: document.links.length,
+            scripts: document.scripts.length,
+            headings: document.querySelectorAll('h1, h2, h3').length,
+            paragraphs: document.querySelectorAll('p').length
+        })
+    ''')
+
+    print(f"  [Hook] 📈 Page: {metrics['title'][:50]}...")
+    print(f"         Links: {metrics['links']}, Images: {metrics['images']}, "
+          f"Headings: {metrics['headings']}, Paragraphs: {metrics['paragraphs']}")
+
+    return page
+
+
+# ============================================================================
+# DEMO 1: String-Based Hooks (NEW Docker Hooks System)
+# ============================================================================
+
+def demo_1_string_based_hooks():
+    """
+    Demonstrate string-based hooks with REST API (part of NEW Docker Hooks System)
+    """
+    print_section(
+        "DEMO 1: String-Based Hooks (REST API)",
+        "Part of the NEW Docker Hooks System - hooks as strings"
+    )
+
+    # Define hooks as strings
+    hooks_config = {
+        "on_page_context_created": """
+async def hook(page, context, **kwargs):
+    print("  [String Hook] Setting up page context...")
+    # Block images for performance
+    await context.route("**/*.{png,jpg,jpeg,gif,webp}", lambda route: route.abort())
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+""",
+
+        "before_goto": """
+async def hook(page, context, url, **kwargs):
+    print(f"  [String Hook] Navigating to {url[:50]}...")
+    await page.set_extra_http_headers({
+        'X-Crawl4AI': 'string-based-hooks',
+        'X-Demo': 'v0.7.5'
+    })
+    return page
+""",
+
+        "before_retrieve_html": """
+async def hook(page, context, **kwargs):
+    print("  [String Hook] Scrolling page...")
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    return page
+"""
+    }
+
+    # Prepare request payload
+    payload = {
+        "urls": [TEST_URLS[0]],
+        "hooks": {
+            "code": hooks_config,
+            "timeout": 30
+        },
+        "crawler_config": {
+            "cache_mode": "bypass"
+        }
+    }
+
+    print(f"🎯 Target URL: {TEST_URLS[0]}")
+    print(f"🔧 Configured {len(hooks_config)} string-based hooks")
+    print(f"📡 Sending request to Docker API...\n")
+
+    try:
+        start_time = time.time()
+        response = requests.post(f"{DOCKER_URL}/crawl", json=payload, timeout=60)
+        execution_time = time.time() - start_time
+
+        if response.status_code == 200:
+            result = response.json()
+
+            print(f"\n✅ Request successful! (took {execution_time:.2f}s)")
+
+            # Display results
+            if result.get('results') and result['results'][0].get('success'):
+                crawl_result = result['results'][0]
+                html_length = len(crawl_result.get('html', ''))
+                markdown_length = len(crawl_result.get('markdown', ''))
+
+                print(f"\n📊 Results:")
+                print(f"   • HTML length: {html_length:,} characters")
+                print(f"   • Markdown length: {markdown_length:,} characters")
+                print(f"   • URL: {crawl_result.get('url')}")
+
+                # Check hooks execution
+                if 'hooks' in result:
+                    hooks_info = result['hooks']
+                    print(f"\n🎣 Hooks Execution:")
+                    print(f"   • Status: {hooks_info['status']['status']}")
+                    print(f"   • Attached hooks: {len(hooks_info['status']['attached_hooks'])}")
+
+                    if 'summary' in hooks_info:
+                        summary = hooks_info['summary']
+                        print(f"   • Total executions: {summary['total_executions']}")
+                        print(f"   • Successful: {summary['successful']}")
+                        print(f"   • Success rate: {summary['success_rate']:.1f}%")
+            else:
+                print(f"⚠️ Crawl completed but no results")
+
+        else:
+            print(f"❌ Request failed with status {response.status_code}")
+            print(f"   Error: {response.text[:200]}")
+
+    except requests.exceptions.Timeout:
+        print("⏰ Request timed out after 60 seconds")
+    except Exception as e:
+        print(f"❌ Error: {str(e)}")
+
+    print("\n" + "─" * 70)
+    print("✓ String-based hooks demo complete\n")
+
+
+# ============================================================================
+# DEMO 2: Function-Based Hooks with hooks_to_string() Utility
+# ============================================================================
+
+def demo_2_hooks_to_string_utility():
+    """
+    Demonstrate the new hooks_to_string() utility for converting functions
+    """
+    print_section(
+        "DEMO 2: hooks_to_string() Utility (NEW! ✨)",
+        "Convert Python functions to strings for REST API"
+    )
+
+    print("📦 Creating hook functions...")
+    print("   • performance_optimization_hook")
+    print("   • viewport_setup_hook")
+    print("   • authentication_headers_hook")
+    print("   • lazy_loading_handler_hook")
+
+    # Convert function objects to strings using the NEW utility
+    print("\n🔄 Converting functions to strings with hooks_to_string()...")
+
+    hooks_dict = {
+        "on_page_context_created": performance_optimization_hook,
+        "before_goto": authentication_headers_hook,
+        "before_retrieve_html": lazy_loading_handler_hook,
+    }
+
+    hooks_as_strings = hooks_to_string(hooks_dict)
+
+    print(f"✅ Successfully converted {len(hooks_as_strings)} functions to strings")
+
+    # Show a preview
+    print("\n📝 Sample converted hook (first 250 characters):")
+    print("─" * 70)
+    sample_hook = list(hooks_as_strings.values())[0]
+    print(sample_hook[:250] + "...")
+    print("─" * 70)
+
+    # Use the converted hooks with REST API
+    print("\n📡 Using converted hooks with REST API...")
+
+    payload = {
+        "urls": [TEST_URLS[0]],
+        "hooks": {
+            "code": hooks_as_strings,
+            "timeout": 30
+        }
+    }
+
+    try:
+        start_time = time.time()
+        response = requests.post(f"{DOCKER_URL}/crawl", json=payload, timeout=60)
+        execution_time = time.time() - start_time
+
+        if response.status_code == 200:
+            result = response.json()
+            print(f"\n✅ Request successful! (took {execution_time:.2f}s)")
+
+            if result.get('results') and result['results'][0].get('success'):
+                crawl_result = result['results'][0]
+                print(f"   • HTML length: {len(crawl_result.get('html', '')):,} characters")
+                print(f"   • Hooks executed successfully!")
+        else:
+            print(f"❌ Request failed: {response.status_code}")
+
+    except Exception as e:
+        print(f"❌ Error: {str(e)}")
+
+    print("\n💡 Benefits of hooks_to_string():")
+    print("   ✓ Write hooks as regular Python functions")
+    print("   ✓ Full IDE support (autocomplete, syntax highlighting)")
+    print("   ✓ Type checking and linting")
+    print("   ✓ Easy to test and debug")
+    print("   ✓ Reusable across projects")
+    print("   ✓ Works with any REST API client")
+
+    print("\n" + "─" * 70)
+    print("✓ hooks_to_string() utility demo complete\n")
+
+
+# ============================================================================
+# DEMO 3: Docker Client with Automatic Conversion (RECOMMENDED! 🌟)
+# ============================================================================
+
+async def demo_3_docker_client_auto_conversion():
+    """
+    Demonstrate Docker Client with automatic hook conversion (RECOMMENDED)
+    """
+    print_section(
+        "DEMO 3: Docker Client with Auto-Conversion (RECOMMENDED! 🌟)",
+        "Pass function objects directly - conversion happens automatically!"
+    )
+
+    print("🐳 Initializing Crawl4AI Docker Client...")
+    client = Crawl4aiDockerClient(base_url=DOCKER_URL)
+
+    print("✅ Client ready!\n")
+
+    # Use our reusable hook library - just pass the function objects!
+    print("📚 Using reusable hook library:")
+    print("   • performance_optimization_hook")
+    print("   • viewport_setup_hook")
+    print("   • authentication_headers_hook")
+    print("   • lazy_loading_handler_hook")
+    print("   • page_analytics_hook")
+
+    print("\n🎯 Target URL: " + TEST_URLS[1])
+    print("🚀 Starting crawl with automatic hook conversion...\n")
+
+    try:
+        start_time = time.time()
+
+        # Pass function objects directly - NO manual conversion needed! ✨
+        results = await client.crawl(
+            urls=[TEST_URLS[0]],
+            hooks={
+                "on_page_context_created": performance_optimization_hook,
+                "before_goto": authentication_headers_hook,
+                "before_retrieve_html": lazy_loading_handler_hook,
+                "before_return_html": page_analytics_hook,
+            },
+            hooks_timeout=30
+        )
+
+        execution_time = time.time() - start_time
+
+        print(f"\n✅ Crawl completed! (took {execution_time:.2f}s)\n")
+
+        # Display results
+        if results and results.success:
+            result = results
+            print(f"📊 Results:")
+            print(f"   • URL: {result.url}")
+            print(f"   • Success: {result.success}")
+            print(f"   • HTML length: {len(result.html):,} characters")
+            print(f"   • Markdown length: {len(result.markdown):,} characters")
+
+            # Show metadata
+            if result.metadata:
+                print(f"\n📋 Metadata:")
+                print(f"   • Title: {result.metadata.get('title', 'N/A')}")
+                print(f"   • Description: {result.metadata.get('description', 'N/A')}")
+
+            # Show links
+            if result.links:
+                internal_count = len(result.links.get('internal', []))
+                external_count = len(result.links.get('external', []))
+                print(f"\n🔗 Links Found:")
+                print(f"   • Internal: {internal_count}")
+                print(f"   • External: {external_count}")
+        else:
+            print(f"⚠️ Crawl completed but no successful results")
+            if results:
+                print(f"   Error: {results.error_message}")
+
+    except Exception as e:
+        print(f"❌ Error: {str(e)}")
+        import traceback
+        traceback.print_exc()
+
+    print("\n🌟 Why Docker Client is RECOMMENDED:")
+    print("   ✓ Automatic function-to-string conversion")
+    print("   ✓ No manual hooks_to_string() calls needed")
+    print("   ✓ Cleaner, more Pythonic code")
+    print("   ✓ Full type hints and IDE support")
+    print("   ✓ Built-in error handling")
+    print("   ✓ Async/await support")
+
+    print("\n" + "─" * 70)
+    print("✓ Docker Client auto-conversion demo complete\n")
+
+
+# ============================================================================
+# DEMO 4: Advanced Use Case - Complete Hook Pipeline
+# ============================================================================
+
+async def demo_4_complete_hook_pipeline():
+    """
+    Demonstrate a complete hook pipeline using all 8 hook points
+    """
+    print_section(
+        "DEMO 4: Complete Hook Pipeline",
+        "Using all 8 available hook points for comprehensive control"
+    )
+
+    # Define all 8 hooks
+    async def on_browser_created_hook(browser, **kwargs):
+        """Hook 1: Called after browser is created"""
+        print("  [Pipeline] 1/8 Browser created")
+        return browser
+
+    async def on_page_context_created_hook(page, context, **kwargs):
+        """Hook 2: Called after page context is created"""
+        print("  [Pipeline] 2/8 Page context created - setting up...")
+        await page.set_viewport_size({"width": 1920, "height": 1080})
+        return page
+
+    async def on_user_agent_updated_hook(page, context, user_agent, **kwargs):
+        """Hook 3: Called when user agent is updated"""
+        print(f"  [Pipeline] 3/8 User agent updated: {user_agent[:50]}...")
+        return page
+
+    async def before_goto_hook(page, context, url, **kwargs):
+        """Hook 4: Called before navigating to URL"""
+        print(f"  [Pipeline] 4/8 Before navigation to: {url[:60]}...")
+        return page
+
+    async def after_goto_hook(page, context, url, response, **kwargs):
+        """Hook 5: Called after navigation completes"""
+        print(f"  [Pipeline] 5/8 After navigation - Status: {response.status if response else 'N/A'}")
+        await page.wait_for_timeout(1000)
+        return page
+
+    async def on_execution_started_hook(page, context, **kwargs):
+        """Hook 6: Called when JavaScript execution starts"""
+        print("  [Pipeline] 6/8 JavaScript execution started")
+        return page
+
+    async def before_retrieve_html_hook(page, context, **kwargs):
+        """Hook 7: Called before retrieving HTML"""
+        print("  [Pipeline] 7/8 Before HTML retrieval - scrolling...")
+        await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+        return page
+
+    async def before_return_html_hook(page, context, html, **kwargs):
+        """Hook 8: Called before returning HTML"""
+        print(f"  [Pipeline] 8/8 Before return - HTML length: {len(html):,} chars")
+        return page
+
+    print("🎯 Target URL: " + TEST_URLS[0])
+    print("🔧 Configured ALL 8 hook points for complete pipeline control\n")
+
+    client = Crawl4aiDockerClient(base_url=DOCKER_URL)
+
+    try:
+        print("🚀 Starting complete pipeline crawl...\n")
+        start_time = time.time()
+
+        results = await client.crawl(
+            urls=[TEST_URLS[0]],
+            hooks={
+                "on_browser_created": on_browser_created_hook,
+                "on_page_context_created": on_page_context_created_hook,
+                "on_user_agent_updated": on_user_agent_updated_hook,
+                "before_goto": before_goto_hook,
+                "after_goto": after_goto_hook,
+                "on_execution_started": on_execution_started_hook,
+                "before_retrieve_html": before_retrieve_html_hook,
+                "before_return_html": before_return_html_hook,
+            },
+            hooks_timeout=45
+        )
+
+        execution_time = time.time() - start_time
+
+        if results and results.success:
+            print(f"\n✅ Complete pipeline executed successfully! (took {execution_time:.2f}s)")
+            print(f"   • All 8 hooks executed in sequence")
+            print(f"   • HTML length: {len(results.html):,} characters")
+        else:
+            print(f"⚠️ Pipeline completed with warnings")
+
+    except Exception as e:
+        print(f"❌ Error: {str(e)}")
+
+    print("\n📚 Available Hook Points:")
+    print("   1. on_browser_created - Browser initialization")
+    print("   2. on_page_context_created - Page context setup")
+    print("   3. on_user_agent_updated - User agent configuration")
+    print("   4. before_goto - Pre-navigation setup")
+    print("   5. after_goto - Post-navigation processing")
+    print("   6. on_execution_started - JavaScript execution start")
+    print("   7. before_retrieve_html - Pre-extraction processing")
+    print("   8. before_return_html - Final HTML processing")
+
+    print("\n" + "─" * 70)
+    print("✓ Complete hook pipeline demo complete\n")
+
+
+# ============================================================================
+# MAIN EXECUTION
+# ============================================================================
+
+async def main():
+    """
+    Run all demonstrations
+    """
+    print("\n" + "=" * 70)
+    print("  🚀 Crawl4AI v0.7.5 - Docker Hooks Complete Demonstration")
+    print("=" * 70)
+
+    # Check Docker service
+    print("\n🔍 Checking Docker service status...")
+    if not check_docker_service():
+        print("❌ Docker service is not running!")
+        print("\n📋 To start the Docker service:")
+        print("   docker run -p 11235:11235 unclecode/crawl4ai:latest")
+        print("\nPlease start the service and run this demo again.")
+        return
+
+    print("✅ Docker service is running!\n")
+
+    # Run all demos
+    demos = [
+        ("String-Based Hooks (REST API)", demo_1_string_based_hooks, False),
+        ("hooks_to_string() Utility", demo_2_hooks_to_string_utility, False),
+        ("Docker Client Auto-Conversion", demo_3_docker_client_auto_conversion, True),
+        # ("Complete Hook Pipeline", demo_4_complete_hook_pipeline, True),
+    ]
+
+    for i, (name, demo_func, is_async) in enumerate(demos, 1):
+        print(f"\n{'🔷' * 35}")
+        print(f"Starting Demo {i}/{len(demos)}: {name}")
+        print(f"{'🔷' * 35}\n")
+
+        try:
+            if is_async:
+                await demo_func()
+            else:
+                demo_func()
+
+            print(f"✅ Demo {i} completed successfully!")
+
+            # Pause between demos (except the last one)
+            if i < len(demos):
+                print("\n⏸️  Press Enter to continue to next demo...")
+                # input()
+
+        except KeyboardInterrupt:
+            print(f"\n⏹️  Demo interrupted by user")
+            break
+        except Exception as e:
+            print(f"\n❌ Demo {i} failed: {str(e)}")
+            import traceback
+            traceback.print_exc()
+            print("\nContinuing to next demo...\n")
+            continue
+
+    # Final summary
+    print("\n" + "=" * 70)
+    print("  🎉 All Demonstrations Complete!")
+    print("=" * 70)
+
+    print("\n📊 Summary of v0.7.5 Docker Hooks System:")
+    print("\n🆕 COMPLETELY NEW FEATURE in v0.7.5:")
+    print("   The Docker Hooks System lets you customize the crawling pipeline")
+    print("   with user-provided Python functions at 8 strategic points.")
+
+    print("\n✨ Three Ways to Use Docker Hooks (All NEW!):")
+    print("   1. String-based - Write hooks as strings for REST API")
+    print("   2. hooks_to_string() - Convert Python functions to strings")
+    print("   3. Docker Client - Automatic conversion (RECOMMENDED)")
+
+    print("\n💡 Key Benefits:")
+    print("   ✓ Full IDE support (autocomplete, syntax highlighting)")
+    print("   ✓ Type checking and linting")
+    print("   ✓ Easy to test and debug")
+    print("   ✓ Reusable across projects")
+    print("   ✓ Complete pipeline control")
+
+    print("\n🎯 8 Hook Points Available:")
+    print("   • on_browser_created, on_page_context_created")
+    print("   • on_user_agent_updated, before_goto, after_goto")
+    print("   • on_execution_started, before_retrieve_html, before_return_html")
+
+    print("\n📚 Resources:")
+    print("   • Docs: https://docs.crawl4ai.com")
+    print("   • GitHub: https://github.com/unclecode/crawl4ai")
+    print("   • Discord: https://discord.gg/jP8KfhDhyN")
+
+    print("\n" + "=" * 70)
+    print("  Happy Crawling with v0.7.5! 🕷️")
+    print("=" * 70 + "\n")
+
+
+if __name__ == "__main__":
+    print("\n🎬 Starting Crawl4AI v0.7.5 Docker Hooks Demonstration...")
+    print("Press Ctrl+C anytime to exit\n")
+
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\n\n👋 Demo stopped by user. Thanks for exploring Crawl4AI v0.7.5!")
+    except Exception as e:
+        print(f"\n\n❌ Demo error: {str(e)}")
+        import traceback
+        traceback.print_exc()

mkdocs.yml

@@ -7,6 +7,7 @@ docs_dir: docs/md_v2
 
 nav:
   - Home: 'index.md'
+  - "📚 Complete SDK Reference": "complete-sdk-reference.md"
   - "Ask AI": "core/ask-ai.md"
   - "Quick Start": "core/quickstart.md"
   - "Code Examples": "core/examples.md"

test_llm_webhook_feature.py

@@ -0,0 +1,401 @@
+#!/usr/bin/env python3
+"""
+Test script to validate webhook implementation for /llm/job endpoint.
+
+This tests that the /llm/job endpoint now supports webhooks
+following the same pattern as /crawl/job.
+"""
+
+import sys
+import os
+
+# Add deploy/docker to path
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'deploy', 'docker'))
+
+def test_llm_job_payload_model():
+    """Test that LlmJobPayload includes webhook_config field"""
+    print("=" * 60)
+    print("TEST 1: LlmJobPayload Model")
+    print("=" * 60)
+
+    try:
+        from job import LlmJobPayload
+        from schemas import WebhookConfig
+        from pydantic import ValidationError
+
+        # Test with webhook_config
+        payload_dict = {
+            "url": "https://example.com",
+            "q": "Extract main content",
+            "schema": None,
+            "cache": False,
+            "provider": None,
+            "webhook_config": {
+                "webhook_url": "https://myapp.com/webhook",
+                "webhook_data_in_payload": True,
+                "webhook_headers": {"X-Secret": "token"}
+            }
+        }
+
+        payload = LlmJobPayload(**payload_dict)
+
+        print(f"✅ LlmJobPayload accepts webhook_config")
+        print(f"   - URL: {payload.url}")
+        print(f"   - Query: {payload.q}")
+        print(f"   - Webhook URL: {payload.webhook_config.webhook_url}")
+        print(f"   - Data in payload: {payload.webhook_config.webhook_data_in_payload}")
+
+        # Test without webhook_config (should be optional)
+        minimal_payload = {
+            "url": "https://example.com",
+            "q": "Extract content"
+        }
+
+        payload2 = LlmJobPayload(**minimal_payload)
+        assert payload2.webhook_config is None, "webhook_config should be optional"
+        print(f"✅ LlmJobPayload works without webhook_config (optional)")
+
+        return True
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_handle_llm_request_signature():
+    """Test that handle_llm_request accepts webhook_config parameter"""
+    print("\n" + "=" * 60)
+    print("TEST 2: handle_llm_request Function Signature")
+    print("=" * 60)
+
+    try:
+        from api import handle_llm_request
+        import inspect
+
+        sig = inspect.signature(handle_llm_request)
+        params = list(sig.parameters.keys())
+
+        print(f"Function parameters: {params}")
+
+        if 'webhook_config' in params:
+            print(f"✅ handle_llm_request has webhook_config parameter")
+
+            # Check that it's optional with default None
+            webhook_param = sig.parameters['webhook_config']
+            if webhook_param.default is None or webhook_param.default == inspect.Parameter.empty:
+                print(f"✅ webhook_config is optional (default: {webhook_param.default})")
+            else:
+                print(f"⚠️  webhook_config default is: {webhook_param.default}")
+
+            return True
+        else:
+            print(f"❌ handle_llm_request missing webhook_config parameter")
+            return False
+
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_process_llm_extraction_signature():
+    """Test that process_llm_extraction accepts webhook_config parameter"""
+    print("\n" + "=" * 60)
+    print("TEST 3: process_llm_extraction Function Signature")
+    print("=" * 60)
+
+    try:
+        from api import process_llm_extraction
+        import inspect
+
+        sig = inspect.signature(process_llm_extraction)
+        params = list(sig.parameters.keys())
+
+        print(f"Function parameters: {params}")
+
+        if 'webhook_config' in params:
+            print(f"✅ process_llm_extraction has webhook_config parameter")
+
+            webhook_param = sig.parameters['webhook_config']
+            if webhook_param.default is None or webhook_param.default == inspect.Parameter.empty:
+                print(f"✅ webhook_config is optional (default: {webhook_param.default})")
+            else:
+                print(f"⚠️  webhook_config default is: {webhook_param.default}")
+
+            return True
+        else:
+            print(f"❌ process_llm_extraction missing webhook_config parameter")
+            return False
+
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_webhook_integration_in_api():
+    """Test that api.py properly integrates webhook notifications"""
+    print("\n" + "=" * 60)
+    print("TEST 4: Webhook Integration in process_llm_extraction")
+    print("=" * 60)
+
+    try:
+        api_file = os.path.join(os.path.dirname(__file__), 'deploy', 'docker', 'api.py')
+
+        with open(api_file, 'r') as f:
+            api_content = f.read()
+
+        # Check for WebhookDeliveryService initialization
+        if 'webhook_service = WebhookDeliveryService(config)' in api_content:
+            print("✅ process_llm_extraction initializes WebhookDeliveryService")
+        else:
+            print("❌ Missing WebhookDeliveryService initialization in process_llm_extraction")
+            return False
+
+        # Check for notify_job_completion calls with llm_extraction
+        if 'task_type="llm_extraction"' in api_content:
+            print("✅ Uses correct task_type='llm_extraction' for notifications")
+        else:
+            print("❌ Missing task_type='llm_extraction' in webhook notifications")
+            return False
+
+        # Count webhook notification calls (should have at least 3: success + 2 failure paths)
+        notification_count = api_content.count('await webhook_service.notify_job_completion')
+        # Find only in process_llm_extraction function
+        llm_func_start = api_content.find('async def process_llm_extraction')
+        llm_func_end = api_content.find('\nasync def ', llm_func_start + 1)
+        if llm_func_end == -1:
+            llm_func_end = len(api_content)
+
+        llm_func_content = api_content[llm_func_start:llm_func_end]
+        llm_notification_count = llm_func_content.count('await webhook_service.notify_job_completion')
+
+        print(f"✅ Found {llm_notification_count} webhook notification calls in process_llm_extraction")
+
+        if llm_notification_count >= 3:
+            print(f"✅ Sufficient notification points (success + failure paths)")
+        else:
+            print(f"⚠️  Expected at least 3 notification calls, found {llm_notification_count}")
+
+        return True
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_job_endpoint_integration():
+    """Test that /llm/job endpoint extracts and passes webhook_config"""
+    print("\n" + "=" * 60)
+    print("TEST 5: /llm/job Endpoint Integration")
+    print("=" * 60)
+
+    try:
+        job_file = os.path.join(os.path.dirname(__file__), 'deploy', 'docker', 'job.py')
+
+        with open(job_file, 'r') as f:
+            job_content = f.read()
+
+        # Find the llm_job_enqueue function
+        llm_job_start = job_content.find('async def llm_job_enqueue')
+        llm_job_end = job_content.find('\n\n@router', llm_job_start + 1)
+        if llm_job_end == -1:
+            llm_job_end = job_content.find('\n\nasync def', llm_job_start + 1)
+
+        llm_job_func = job_content[llm_job_start:llm_job_end]
+
+        # Check for webhook_config extraction
+        if 'webhook_config = None' in llm_job_func:
+            print("✅ llm_job_enqueue initializes webhook_config variable")
+        else:
+            print("❌ Missing webhook_config initialization")
+            return False
+
+        if 'if payload.webhook_config:' in llm_job_func:
+            print("✅ llm_job_enqueue checks for payload.webhook_config")
+        else:
+            print("❌ Missing webhook_config check")
+            return False
+
+        if 'webhook_config = payload.webhook_config.model_dump(mode=\'json\')' in llm_job_func:
+            print("✅ llm_job_enqueue converts webhook_config to dict")
+        else:
+            print("❌ Missing webhook_config.model_dump conversion")
+            return False
+
+        if 'webhook_config=webhook_config' in llm_job_func:
+            print("✅ llm_job_enqueue passes webhook_config to handle_llm_request")
+        else:
+            print("❌ Missing webhook_config parameter in handle_llm_request call")
+            return False
+
+        return True
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_create_new_task_integration():
+    """Test that create_new_task stores webhook_config in Redis"""
+    print("\n" + "=" * 60)
+    print("TEST 6: create_new_task Webhook Storage")
+    print("=" * 60)
+
+    try:
+        api_file = os.path.join(os.path.dirname(__file__), 'deploy', 'docker', 'api.py')
+
+        with open(api_file, 'r') as f:
+            api_content = f.read()
+
+        # Find create_new_task function
+        create_task_start = api_content.find('async def create_new_task')
+        create_task_end = api_content.find('\nasync def ', create_task_start + 1)
+        if create_task_end == -1:
+            create_task_end = len(api_content)
+
+        create_task_func = api_content[create_task_start:create_task_end]
+
+        # Check for webhook_config storage
+        if 'if webhook_config:' in create_task_func:
+            print("✅ create_new_task checks for webhook_config")
+        else:
+            print("❌ Missing webhook_config check in create_new_task")
+            return False
+
+        if 'task_data["webhook_config"] = json.dumps(webhook_config)' in create_task_func:
+            print("✅ create_new_task stores webhook_config in Redis task data")
+        else:
+            print("❌ Missing webhook_config storage in task_data")
+            return False
+
+        # Check that webhook_config is passed to process_llm_extraction
+        if 'webhook_config' in create_task_func and 'background_tasks.add_task' in create_task_func:
+            print("✅ create_new_task passes webhook_config to background task")
+        else:
+            print("⚠️  Could not verify webhook_config passed to background task")
+
+        return True
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_pattern_consistency():
+    """Test that /llm/job follows the same pattern as /crawl/job"""
+    print("\n" + "=" * 60)
+    print("TEST 7: Pattern Consistency with /crawl/job")
+    print("=" * 60)
+
+    try:
+        api_file = os.path.join(os.path.dirname(__file__), 'deploy', 'docker', 'api.py')
+
+        with open(api_file, 'r') as f:
+            api_content = f.read()
+
+        # Find handle_crawl_job to compare pattern
+        crawl_job_start = api_content.find('async def handle_crawl_job')
+        crawl_job_end = api_content.find('\nasync def ', crawl_job_start + 1)
+        if crawl_job_end == -1:
+            crawl_job_end = len(api_content)
+        crawl_job_func = api_content[crawl_job_start:crawl_job_end]
+
+        # Find process_llm_extraction
+        llm_extract_start = api_content.find('async def process_llm_extraction')
+        llm_extract_end = api_content.find('\nasync def ', llm_extract_start + 1)
+        if llm_extract_end == -1:
+            llm_extract_end = len(api_content)
+        llm_extract_func = api_content[llm_extract_start:llm_extract_end]
+
+        print("Checking pattern consistency...")
+
+        # Both should initialize WebhookDeliveryService
+        crawl_has_service = 'webhook_service = WebhookDeliveryService(config)' in crawl_job_func
+        llm_has_service = 'webhook_service = WebhookDeliveryService(config)' in llm_extract_func
+
+        if crawl_has_service and llm_has_service:
+            print("✅ Both initialize WebhookDeliveryService")
+        else:
+            print(f"❌ Service initialization mismatch (crawl: {crawl_has_service}, llm: {llm_has_service})")
+            return False
+
+        # Both should call notify_job_completion on success
+        crawl_notifies_success = 'status="completed"' in crawl_job_func and 'notify_job_completion' in crawl_job_func
+        llm_notifies_success = 'status="completed"' in llm_extract_func and 'notify_job_completion' in llm_extract_func
+
+        if crawl_notifies_success and llm_notifies_success:
+            print("✅ Both notify on success")
+        else:
+            print(f"❌ Success notification mismatch (crawl: {crawl_notifies_success}, llm: {llm_notifies_success})")
+            return False
+
+        # Both should call notify_job_completion on failure
+        crawl_notifies_failure = 'status="failed"' in crawl_job_func and 'error=' in crawl_job_func
+        llm_notifies_failure = 'status="failed"' in llm_extract_func and 'error=' in llm_extract_func
+
+        if crawl_notifies_failure and llm_notifies_failure:
+            print("✅ Both notify on failure")
+        else:
+            print(f"❌ Failure notification mismatch (crawl: {crawl_notifies_failure}, llm: {llm_notifies_failure})")
+            return False
+
+        print("✅ /llm/job follows the same pattern as /crawl/job")
+        return True
+
+    except Exception as e:
+        print(f"❌ Failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def main():
+    """Run all tests"""
+    print("\n🧪 LLM Job Webhook Feature Validation")
+    print("=" * 60)
+    print("Testing that /llm/job now supports webhooks like /crawl/job")
+    print("=" * 60 + "\n")
+
+    results = []
+
+    # Run all tests
+    results.append(("LlmJobPayload Model", test_llm_job_payload_model()))
+    results.append(("handle_llm_request Signature", test_handle_llm_request_signature()))
+    results.append(("process_llm_extraction Signature", test_process_llm_extraction_signature()))
+    results.append(("Webhook Integration", test_webhook_integration_in_api()))
+    results.append(("/llm/job Endpoint", test_job_endpoint_integration()))
+    results.append(("create_new_task Storage", test_create_new_task_integration()))
+    results.append(("Pattern Consistency", test_pattern_consistency()))
+
+    # Print summary
+    print("\n" + "=" * 60)
+    print("TEST SUMMARY")
+    print("=" * 60)
+
+    passed = sum(1 for _, result in results if result)
+    total = len(results)
+
+    for test_name, result in results:
+        status = "✅ PASS" if result else "❌ FAIL"
+        print(f"{status} - {test_name}")
+
+    print(f"\n{'=' * 60}")
+    print(f"Results: {passed}/{total} tests passed")
+    print(f"{'=' * 60}")
+
+    if passed == total:
+        print("\n🎉 All tests passed! /llm/job webhook feature is correctly implemented.")
+        print("\n📝 Summary of changes:")
+        print("  1. LlmJobPayload model includes webhook_config field")
+        print("  2. /llm/job endpoint extracts and passes webhook_config")
+        print("  3. handle_llm_request accepts webhook_config parameter")
+        print("  4. create_new_task stores webhook_config in Redis")
+        print("  5. process_llm_extraction sends webhook notifications")
+        print("  6. Follows the same pattern as /crawl/job")
+        return 0
+    else:
+        print(f"\n⚠️  {total - passed} test(s) failed. Please review the output above.")
+        return 1
+
+if __name__ == "__main__":
+    exit(main())

test_webhook_implementation.py

@@ -0,0 +1,307 @@
+"""
+Simple test script to validate webhook implementation without running full server.
+
+This script tests:
+1. Webhook module imports and syntax
+2. WebhookDeliveryService initialization
+3. Payload construction logic
+4. Configuration parsing
+"""
+
+import sys
+import os
+import json
+from datetime import datetime, timezone
+
+# Add deploy/docker to path to import modules
+# sys.path.insert(0, '/home/user/crawl4ai/deploy/docker')
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'deploy', 'docker'))
+
+def test_imports():
+    """Test that all webhook-related modules can be imported"""
+    print("=" * 60)
+    print("TEST 1: Module Imports")
+    print("=" * 60)
+
+    try:
+        from webhook import WebhookDeliveryService
+        print("✅ webhook.WebhookDeliveryService imported successfully")
+    except Exception as e:
+        print(f"❌ Failed to import webhook module: {e}")
+        return False
+
+    try:
+        from schemas import WebhookConfig, WebhookPayload
+        print("✅ schemas.WebhookConfig imported successfully")
+        print("✅ schemas.WebhookPayload imported successfully")
+    except Exception as e:
+        print(f"❌ Failed to import schemas: {e}")
+        return False
+
+    return True
+
+def test_webhook_service_init():
+    """Test WebhookDeliveryService initialization"""
+    print("\n" + "=" * 60)
+    print("TEST 2: WebhookDeliveryService Initialization")
+    print("=" * 60)
+
+    try:
+        from webhook import WebhookDeliveryService
+
+        # Test with default config
+        config = {
+            "webhooks": {
+                "enabled": True,
+                "default_url": None,
+                "data_in_payload": False,
+                "retry": {
+                    "max_attempts": 5,
+                    "initial_delay_ms": 1000,
+                    "max_delay_ms": 32000,
+                    "timeout_ms": 30000
+                },
+                "headers": {
+                    "User-Agent": "Crawl4AI-Webhook/1.0"
+                }
+            }
+        }
+
+        service = WebhookDeliveryService(config)
+
+        print(f"✅ Service initialized successfully")
+        print(f"   - Max attempts: {service.max_attempts}")
+        print(f"   - Initial delay: {service.initial_delay}s")
+        print(f"   - Max delay: {service.max_delay}s")
+        print(f"   - Timeout: {service.timeout}s")
+
+        # Verify calculations
+        assert service.max_attempts == 5, "Max attempts should be 5"
+        assert service.initial_delay == 1.0, "Initial delay should be 1.0s"
+        assert service.max_delay == 32.0, "Max delay should be 32.0s"
+        assert service.timeout == 30.0, "Timeout should be 30.0s"
+
+        print("✅ All configuration values correct")
+
+        return True
+    except Exception as e:
+        print(f"❌ Service initialization failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_webhook_config_model():
+    """Test WebhookConfig Pydantic model"""
+    print("\n" + "=" * 60)
+    print("TEST 3: WebhookConfig Model Validation")
+    print("=" * 60)
+
+    try:
+        from schemas import WebhookConfig
+        from pydantic import ValidationError
+
+        # Test valid config
+        valid_config = {
+            "webhook_url": "https://example.com/webhook",
+            "webhook_data_in_payload": True,
+            "webhook_headers": {"X-Secret": "token123"}
+        }
+
+        config = WebhookConfig(**valid_config)
+        print(f"✅ Valid config accepted:")
+        print(f"   - URL: {config.webhook_url}")
+        print(f"   - Data in payload: {config.webhook_data_in_payload}")
+        print(f"   - Headers: {config.webhook_headers}")
+
+        # Test minimal config
+        minimal_config = {
+            "webhook_url": "https://example.com/webhook"
+        }
+
+        config2 = WebhookConfig(**minimal_config)
+        print(f"✅ Minimal config accepted (defaults applied):")
+        print(f"   - URL: {config2.webhook_url}")
+        print(f"   - Data in payload: {config2.webhook_data_in_payload}")
+        print(f"   - Headers: {config2.webhook_headers}")
+
+        # Test invalid URL
+        try:
+            invalid_config = {
+                "webhook_url": "not-a-url"
+            }
+            config3 = WebhookConfig(**invalid_config)
+            print(f"❌ Invalid URL should have been rejected")
+            return False
+        except ValidationError as e:
+            print(f"✅ Invalid URL correctly rejected")
+
+        return True
+    except Exception as e:
+        print(f"❌ Model validation test failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_payload_construction():
+    """Test webhook payload construction logic"""
+    print("\n" + "=" * 60)
+    print("TEST 4: Payload Construction")
+    print("=" * 60)
+
+    try:
+        # Simulate payload construction from notify_job_completion
+        task_id = "crawl_abc123"
+        task_type = "crawl"
+        status = "completed"
+        urls = ["https://example.com"]
+
+        payload = {
+            "task_id": task_id,
+            "task_type": task_type,
+            "status": status,
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "urls": urls
+        }
+
+        print(f"✅ Basic payload constructed:")
+        print(json.dumps(payload, indent=2))
+
+        # Test with error
+        error_payload = {
+            "task_id": "crawl_xyz789",
+            "task_type": "crawl",
+            "status": "failed",
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "urls": ["https://example.com"],
+            "error": "Connection timeout"
+        }
+
+        print(f"\n✅ Error payload constructed:")
+        print(json.dumps(error_payload, indent=2))
+
+        # Test with data
+        data_payload = {
+            "task_id": "crawl_def456",
+            "task_type": "crawl",
+            "status": "completed",
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "urls": ["https://example.com"],
+            "data": {
+                "results": [
+                    {"url": "https://example.com", "markdown": "# Example"}
+                ]
+            }
+        }
+
+        print(f"\n✅ Data payload constructed:")
+        print(json.dumps(data_payload, indent=2))
+
+        return True
+    except Exception as e:
+        print(f"❌ Payload construction failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def test_exponential_backoff():
+    """Test exponential backoff calculation"""
+    print("\n" + "=" * 60)
+    print("TEST 5: Exponential Backoff Calculation")
+    print("=" * 60)
+
+    try:
+        initial_delay = 1.0  # 1 second
+        max_delay = 32.0     # 32 seconds
+
+        print("Backoff delays for 5 attempts:")
+        for attempt in range(5):
+            delay = min(initial_delay * (2 ** attempt), max_delay)
+            print(f"  Attempt {attempt + 1}: {delay}s")
+
+        # Verify the sequence: 1s, 2s, 4s, 8s, 16s
+        expected = [1.0, 2.0, 4.0, 8.0, 16.0]
+        actual = [min(initial_delay * (2 ** i), max_delay) for i in range(5)]
+
+        assert actual == expected, f"Expected {expected}, got {actual}"
+        print("✅ Exponential backoff sequence correct")
+
+        return True
+    except Exception as e:
+        print(f"❌ Backoff calculation failed: {e}")
+        return False
+
+def test_api_integration():
+    """Test that api.py imports webhook module correctly"""
+    print("\n" + "=" * 60)
+    print("TEST 6: API Integration")
+    print("=" * 60)
+
+    try:
+        # Check if api.py can import webhook module
+        api_path = os.path.join(os.path.dirname(__file__), 'deploy', 'docker', 'api.py')
+        with open(api_path, 'r') as f:
+            api_content = f.read()
+
+        if 'from webhook import WebhookDeliveryService' in api_content:
+            print("✅ api.py imports WebhookDeliveryService")
+        else:
+            print("❌ api.py missing webhook import")
+            return False
+
+        if 'WebhookDeliveryService(config)' in api_content:
+            print("✅ api.py initializes WebhookDeliveryService")
+        else:
+            print("❌ api.py doesn't initialize WebhookDeliveryService")
+            return False
+
+        if 'notify_job_completion' in api_content:
+            print("✅ api.py calls notify_job_completion")
+        else:
+            print("❌ api.py doesn't call notify_job_completion")
+            return False
+
+        return True
+    except Exception as e:
+        print(f"❌ API integration check failed: {e}")
+        return False
+
+def main():
+    """Run all tests"""
+    print("\n🧪 Webhook Implementation Validation Tests")
+    print("=" * 60)
+
+    results = []
+
+    # Run tests
+    results.append(("Module Imports", test_imports()))
+    results.append(("Service Initialization", test_webhook_service_init()))
+    results.append(("Config Model", test_webhook_config_model()))
+    results.append(("Payload Construction", test_payload_construction()))
+    results.append(("Exponential Backoff", test_exponential_backoff()))
+    results.append(("API Integration", test_api_integration()))
+
+    # Print summary
+    print("\n" + "=" * 60)
+    print("TEST SUMMARY")
+    print("=" * 60)
+
+    passed = sum(1 for _, result in results if result)
+    total = len(results)
+
+    for test_name, result in results:
+        status = "✅ PASS" if result else "❌ FAIL"
+        print(f"{status} - {test_name}")
+
+    print(f"\n{'=' * 60}")
+    print(f"Results: {passed}/{total} tests passed")
+    print(f"{'=' * 60}")
+
+    if passed == total:
+        print("\n🎉 All tests passed! Webhook implementation is valid.")
+        return 0
+    else:
+        print(f"\n⚠️  {total - passed} test(s) failed. Please review the output above.")
+        return 1
+
+if __name__ == "__main__":
+    exit(main())

tests/WEBHOOK_TEST_README.md

@@ -0,0 +1,251 @@
+# Webhook Feature Test Script
+
+This directory contains a comprehensive test script for the webhook feature implementation.
+
+## Overview
+
+The `test_webhook_feature.sh` script automates the entire process of testing the webhook feature:
+
+1. ✅ Fetches and switches to the webhook feature branch
+2. ✅ Activates the virtual environment
+3. ✅ Installs all required dependencies
+4. ✅ Starts Redis server in background
+5. ✅ Starts Crawl4AI server in background
+6. ✅ Runs webhook integration test
+7. ✅ Verifies job completion via webhook
+8. ✅ Cleans up and returns to original branch
+
+## Prerequisites
+
+- Python 3.10+
+- Virtual environment already created (`venv/` in project root)
+- Git repository with the webhook feature branch
+- `redis-server` (script will attempt to install if missing)
+- `curl` and `lsof` commands available
+
+## Usage
+
+### Quick Start
+
+From the project root:
+
+```bash
+./tests/test_webhook_feature.sh
+```
+
+Or from the tests directory:
+
+```bash
+cd tests
+./test_webhook_feature.sh
+```
+
+### What the Script Does
+
+#### Step 1: Branch Management
+- Saves your current branch
+- Fetches the webhook feature branch from remote
+- Switches to the webhook feature branch
+
+#### Step 2: Environment Setup
+- Activates your existing virtual environment
+- Installs dependencies from `deploy/docker/requirements.txt`
+- Installs Flask for the webhook receiver
+
+#### Step 3: Service Startup
+- Starts Redis server on port 6379
+- Starts Crawl4AI server on port 11235
+- Waits for server health check to pass
+
+#### Step 4: Webhook Test
+- Creates a webhook receiver on port 8080
+- Submits a crawl job for `https://example.com` with webhook config
+- Waits for webhook notification (60s timeout)
+- Verifies webhook payload contains expected data
+
+#### Step 5: Cleanup
+- Stops webhook receiver
+- Stops Crawl4AI server
+- Stops Redis server
+- Returns to your original branch
+
+## Expected Output
+
+```
+[INFO] Starting webhook feature test script
+[INFO] Project root: /path/to/crawl4ai
+[INFO] Step 1: Fetching PR branch...
+[INFO] Current branch: develop
+[SUCCESS] Branch fetched
+[INFO] Step 2: Switching to branch: claude/implement-webhook-crawl-feature-011CULZY1Jy8N5MUkZqXkRVp
+[SUCCESS] Switched to webhook feature branch
+[INFO] Step 3: Activating virtual environment...
+[SUCCESS] Virtual environment activated
+[INFO] Step 4: Installing server dependencies...
+[SUCCESS] Dependencies installed
+[INFO] Step 5a: Starting Redis...
+[SUCCESS] Redis started (PID: 12345)
+[INFO] Step 5b: Starting server on port 11235...
+[INFO] Server started (PID: 12346)
+[INFO] Waiting for server to be ready...
+[SUCCESS] Server is ready!
+[INFO] Step 6: Creating webhook test script...
+[INFO] Running webhook test...
+
+🚀 Submitting crawl job with webhook...
+✅ Job submitted successfully, task_id: crawl_abc123
+⏳ Waiting for webhook notification...
+
+✅ Webhook received: {
+  "task_id": "crawl_abc123",
+  "task_type": "crawl",
+  "status": "completed",
+  "timestamp": "2025-10-22T00:00:00.000000+00:00",
+  "urls": ["https://example.com"],
+  "data": { ... }
+}
+
+✅ Webhook received!
+   Task ID: crawl_abc123
+   Status: completed
+   URLs: ['https://example.com']
+   ✅ Data included in webhook payload
+   📄 Crawled 1 URL(s)
+      - https://example.com: 1234 chars
+
+🎉 Webhook test PASSED!
+
+[INFO] Step 7: Verifying test results...
+[SUCCESS] ✅ Webhook test PASSED!
+[SUCCESS] All tests completed successfully! 🎉
+[INFO] Cleanup will happen automatically...
+[INFO] Starting cleanup...
+[INFO] Stopping webhook receiver...
+[INFO] Stopping server...
+[INFO] Stopping Redis...
+[INFO] Switching back to branch: develop
+[SUCCESS] Cleanup complete
+```
+
+## Troubleshooting
+
+### Server Failed to Start
+
+If the server fails to start, check the logs:
+
+```bash
+tail -100 /tmp/crawl4ai_server.log
+```
+
+Common issues:
+- Port 11235 already in use: `lsof -ti:11235 | xargs kill -9`
+- Missing dependencies: Check that all packages are installed
+
+### Redis Connection Failed
+
+Check if Redis is running:
+
+```bash
+redis-cli ping
+# Should return: PONG
+```
+
+If not running:
+
+```bash
+redis-server --port 6379 --daemonize yes
+```
+
+### Webhook Not Received
+
+The script has a 60-second timeout for webhook delivery. If the webhook isn't received:
+
+1. Check server logs: `/tmp/crawl4ai_server.log`
+2. Verify webhook receiver is running on port 8080
+3. Check network connectivity between components
+
+### Script Interruption
+
+If the script is interrupted (Ctrl+C), cleanup happens automatically via trap. The script will:
+- Kill all background processes
+- Stop Redis
+- Return to your original branch
+
+To manually cleanup if needed:
+
+```bash
+# Kill processes by port
+lsof -ti:11235 | xargs kill -9  # Server
+lsof -ti:8080 | xargs kill -9   # Webhook receiver
+lsof -ti:6379 | xargs kill -9   # Redis
+
+# Return to your branch
+git checkout develop  # or your branch name
+```
+
+## Testing Different URLs
+
+To test with a different URL, modify the script or create a custom test:
+
+```python
+payload = {
+    "urls": ["https://your-url-here.com"],
+    "browser_config": {"headless": True},
+    "crawler_config": {"cache_mode": "bypass"},
+    "webhook_config": {
+        "webhook_url": "http://localhost:8080/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+```
+
+## Files Generated
+
+The script creates temporary files:
+
+- `/tmp/crawl4ai_server.log` - Server output logs
+- `/tmp/test_webhook.py` - Webhook test Python script
+
+These are not cleaned up automatically so you can review them after the test.
+
+## Exit Codes
+
+- `0` - All tests passed successfully
+- `1` - Test failed (check output for details)
+
+## Safety Features
+
+- ✅ Automatic cleanup on exit, interrupt, or error
+- ✅ Returns to original branch on completion
+- ✅ Kills all background processes
+- ✅ Comprehensive error handling
+- ✅ Colored output for easy reading
+- ✅ Detailed logging at each step
+
+## Notes
+
+- The script uses `set -e` to exit on any command failure
+- All background processes are tracked and cleaned up
+- The virtual environment must exist before running
+- Redis must be available (installed or installable via apt-get/brew)
+
+## Integration with CI/CD
+
+This script can be integrated into CI/CD pipelines:
+
+```yaml
+# Example GitHub Actions
+- name: Test Webhook Feature
+  run: |
+    chmod +x tests/test_webhook_feature.sh
+    ./tests/test_webhook_feature.sh
+```
+
+## Support
+
+If you encounter issues:
+
+1. Check the troubleshooting section above
+2. Review server logs at `/tmp/crawl4ai_server.log`
+3. Ensure all prerequisites are met
+4. Open an issue with the full output of the script

tests/docker/test_hooks_utility.py

@@ -0,0 +1,193 @@
+"""
+Test script demonstrating the hooks_to_string utility and Docker client integration.
+"""
+import asyncio
+from crawl4ai import Crawl4aiDockerClient, hooks_to_string
+
+
+# Define hook functions as regular Python functions
+async def auth_hook(page, context, **kwargs):
+    """Add authentication cookies."""
+    await context.add_cookies([{
+        'name': 'test_cookie',
+        'value': 'test_value',
+        'domain': '.httpbin.org',
+        'path': '/'
+    }])
+    return page
+
+
+async def scroll_hook(page, context, **kwargs):
+    """Scroll to load lazy content."""
+    await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
+    await page.wait_for_timeout(1000)
+    return page
+
+
+async def viewport_hook(page, context, **kwargs):
+    """Set custom viewport."""
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+
+
+async def test_hooks_utility():
+    """Test the hooks_to_string utility function."""
+    print("=" * 60)
+    print("Testing hooks_to_string utility")
+    print("=" * 60)
+
+    # Create hooks dictionary with function objects
+    hooks_dict = {
+        "on_page_context_created": auth_hook,
+        "before_retrieve_html": scroll_hook
+    }
+
+    # Convert to string format
+    hooks_string = hooks_to_string(hooks_dict)
+
+    print("\n✓ Successfully converted function objects to strings")
+    print(f"\n✓ Converted {len(hooks_string)} hooks:")
+    for hook_name in hooks_string.keys():
+        print(f"  - {hook_name}")
+
+    print("\n✓ Preview of converted hook:")
+    print("-" * 60)
+    print(hooks_string["on_page_context_created"][:200] + "...")
+    print("-" * 60)
+
+    return hooks_string
+
+
+async def test_docker_client_with_functions():
+    """Test Docker client with function objects (automatic conversion)."""
+    print("\n" + "=" * 60)
+    print("Testing Docker Client with Function Objects")
+    print("=" * 60)
+
+    # Note: This requires a running Crawl4AI Docker server
+    # Uncomment the following to test with actual server:
+
+    async with Crawl4aiDockerClient(base_url="http://localhost:11234", verbose=True) as client:
+        # Pass function objects directly - they'll be converted automatically
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            hooks={
+                "on_page_context_created": auth_hook,
+                "before_retrieve_html": scroll_hook
+            },
+            hooks_timeout=30
+        )
+        print(f"\n✓ Crawl successful: {result.success}")
+        print(f"✓ URL: {result.url}")
+
+    print("\n✓ Docker client accepts function objects directly")
+    print("✓ Automatic conversion happens internally")
+    print("✓ No manual string formatting needed!")
+
+
+async def test_docker_client_with_strings():
+    """Test Docker client with pre-converted strings."""
+    print("\n" + "=" * 60)
+    print("Testing Docker Client with String Hooks")
+    print("=" * 60)
+
+    # Convert hooks to strings first
+    hooks_dict = {
+        "on_page_context_created": viewport_hook,
+        "before_retrieve_html": scroll_hook
+    }
+    hooks_string = hooks_to_string(hooks_dict)
+
+    # Note: This requires a running Crawl4AI Docker server
+    # Uncomment the following to test with actual server:
+
+    async with Crawl4aiDockerClient(base_url="http://localhost:11234", verbose=True) as client:
+        # Pass string hooks - they'll be used as-is
+        result = await client.crawl(
+            ["https://httpbin.org/html"],
+            hooks=hooks_string,
+            hooks_timeout=30
+        )
+        print(f"\n✓ Crawl successful: {result.success}")
+
+    print("\n✓ Docker client also accepts pre-converted strings")
+    print("✓ Backward compatible with existing code")
+
+
+async def show_usage_patterns():
+    """Show different usage patterns."""
+    print("\n" + "=" * 60)
+    print("Usage Patterns")
+    print("=" * 60)
+
+    print("\n1. Direct function usage (simplest):")
+    print("-" * 60)
+    print("""
+    async def my_hook(page, context, **kwargs):
+        await page.set_viewport_size({"width": 1920, "height": 1080})
+        return page
+
+    result = await client.crawl(
+        ["https://example.com"],
+        hooks={"on_page_context_created": my_hook}
+    )
+    """)
+
+    print("\n2. Convert then use:")
+    print("-" * 60)
+    print("""
+    hooks_dict = {"on_page_context_created": my_hook}
+    hooks_string = hooks_to_string(hooks_dict)
+
+    result = await client.crawl(
+        ["https://example.com"],
+        hooks=hooks_string
+    )
+    """)
+
+    print("\n3. Manual string (backward compatible):")
+    print("-" * 60)
+    print("""
+    hooks_string = {
+        "on_page_context_created": '''
+async def hook(page, context, **kwargs):
+    await page.set_viewport_size({"width": 1920, "height": 1080})
+    return page
+'''
+    }
+
+    result = await client.crawl(
+        ["https://example.com"],
+        hooks=hooks_string
+    )
+    """)
+
+
+async def main():
+    """Run all tests."""
+    print("\n🚀 Crawl4AI Hooks Utility Test Suite\n")
+
+    # Test the utility function
+    # await test_hooks_utility()
+
+    # Show usage with Docker client
+    # await test_docker_client_with_functions()
+    await test_docker_client_with_strings()
+
+    # Show different patterns
+    # await show_usage_patterns()
+
+    # print("\n" + "=" * 60)
+    # print("✓ All tests completed successfully!")
+    # print("=" * 60)
+    # print("\nKey Benefits:")
+    # print("  • Write hooks as regular Python functions")
+    # print("  • IDE support with autocomplete and type checking")
+    # print("  • Automatic conversion to API format")
+    # print("  • Backward compatible with string hooks")
+    # print("  • Same utility used everywhere")
+    # print("\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

tests/test_webhook_feature.sh

@@ -0,0 +1,305 @@
+#!/bin/bash
+
+#############################################################################
+# Webhook Feature Test Script
+#
+# This script tests the webhook feature implementation by:
+# 1. Switching to the webhook feature branch
+# 2. Installing dependencies
+# 3. Starting the server
+# 4. Running webhook tests
+# 5. Cleaning up and returning to original branch
+#
+# Usage: ./test_webhook_feature.sh
+#############################################################################
+
+set -e  # Exit on error
+
+# Colors for output
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m' # No Color
+
+# Configuration
+BRANCH_NAME="claude/implement-webhook-crawl-feature-011CULZY1Jy8N5MUkZqXkRVp"
+VENV_PATH="venv"
+SERVER_PORT=11235
+WEBHOOK_PORT=8080
+PROJECT_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+
+# PID files for cleanup
+REDIS_PID=""
+SERVER_PID=""
+WEBHOOK_PID=""
+
+#############################################################################
+# Utility Functions
+#############################################################################
+
+log_info() {
+    echo -e "${BLUE}[INFO]${NC} $1"
+}
+
+log_success() {
+    echo -e "${GREEN}[SUCCESS]${NC} $1"
+}
+
+log_warning() {
+    echo -e "${YELLOW}[WARNING]${NC} $1"
+}
+
+log_error() {
+    echo -e "${RED}[ERROR]${NC} $1"
+}
+
+cleanup() {
+    log_info "Starting cleanup..."
+
+    # Kill webhook receiver if running
+    if [ ! -z "$WEBHOOK_PID" ] && kill -0 $WEBHOOK_PID 2>/dev/null; then
+        log_info "Stopping webhook receiver (PID: $WEBHOOK_PID)..."
+        kill $WEBHOOK_PID 2>/dev/null || true
+    fi
+
+    # Kill server if running
+    if [ ! -z "$SERVER_PID" ] && kill -0 $SERVER_PID 2>/dev/null; then
+        log_info "Stopping server (PID: $SERVER_PID)..."
+        kill $SERVER_PID 2>/dev/null || true
+    fi
+
+    # Kill Redis if running
+    if [ ! -z "$REDIS_PID" ] && kill -0 $REDIS_PID 2>/dev/null; then
+        log_info "Stopping Redis (PID: $REDIS_PID)..."
+        kill $REDIS_PID 2>/dev/null || true
+    fi
+
+    # Also kill by port if PIDs didn't work
+    lsof -ti:$SERVER_PORT | xargs kill -9 2>/dev/null || true
+    lsof -ti:$WEBHOOK_PORT | xargs kill -9 2>/dev/null || true
+    lsof -ti:6379 | xargs kill -9 2>/dev/null || true
+
+    # Return to original branch
+    if [ ! -z "$ORIGINAL_BRANCH" ]; then
+        log_info "Switching back to branch: $ORIGINAL_BRANCH"
+        git checkout $ORIGINAL_BRANCH 2>/dev/null || true
+    fi
+
+    log_success "Cleanup complete"
+}
+
+# Set trap to cleanup on exit
+trap cleanup EXIT INT TERM
+
+#############################################################################
+# Main Script
+#############################################################################
+
+log_info "Starting webhook feature test script"
+log_info "Project root: $PROJECT_ROOT"
+
+cd "$PROJECT_ROOT"
+
+# Step 1: Save current branch and fetch PR
+log_info "Step 1: Fetching PR branch..."
+ORIGINAL_BRANCH=$(git rev-parse --abbrev-ref HEAD)
+log_info "Current branch: $ORIGINAL_BRANCH"
+
+git fetch origin $BRANCH_NAME
+log_success "Branch fetched"
+
+# Step 2: Switch to new branch
+log_info "Step 2: Switching to branch: $BRANCH_NAME"
+git checkout $BRANCH_NAME
+log_success "Switched to webhook feature branch"
+
+# Step 3: Activate virtual environment
+log_info "Step 3: Activating virtual environment..."
+if [ ! -d "$VENV_PATH" ]; then
+    log_error "Virtual environment not found at $VENV_PATH"
+    log_info "Creating virtual environment..."
+    python3 -m venv $VENV_PATH
+fi
+
+source $VENV_PATH/bin/activate
+log_success "Virtual environment activated: $(which python)"
+
+# Step 4: Install server dependencies
+log_info "Step 4: Installing server dependencies..."
+pip install -q -r deploy/docker/requirements.txt
+log_success "Dependencies installed"
+
+# Check if Redis is available
+log_info "Checking Redis availability..."
+if ! command -v redis-server &> /dev/null; then
+    log_warning "Redis not found, attempting to install..."
+    if command -v apt-get &> /dev/null; then
+        sudo apt-get update && sudo apt-get install -y redis-server
+    elif command -v brew &> /dev/null; then
+        brew install redis
+    else
+        log_error "Cannot install Redis automatically. Please install Redis manually."
+        exit 1
+    fi
+fi
+
+# Step 5: Start Redis in background
+log_info "Step 5a: Starting Redis..."
+redis-server --port 6379 --daemonize yes
+sleep 2
+REDIS_PID=$(pgrep redis-server)
+log_success "Redis started (PID: $REDIS_PID)"
+
+# Step 5b: Start server in background
+log_info "Step 5b: Starting server on port $SERVER_PORT..."
+cd deploy/docker
+
+# Start server in background
+python3 -m uvicorn server:app --host 0.0.0.0 --port $SERVER_PORT > /tmp/crawl4ai_server.log 2>&1 &
+SERVER_PID=$!
+cd "$PROJECT_ROOT"
+
+log_info "Server started (PID: $SERVER_PID)"
+
+# Wait for server to be ready
+log_info "Waiting for server to be ready..."
+for i in {1..30}; do
+    if curl -s http://localhost:$SERVER_PORT/health > /dev/null 2>&1; then
+        log_success "Server is ready!"
+        break
+    fi
+    if [ $i -eq 30 ]; then
+        log_error "Server failed to start within 30 seconds"
+        log_info "Server logs:"
+        tail -50 /tmp/crawl4ai_server.log
+        exit 1
+    fi
+    echo -n "."
+    sleep 1
+done
+echo ""
+
+# Step 6: Create and run webhook test
+log_info "Step 6: Creating webhook test script..."
+
+cat > /tmp/test_webhook.py << 'PYTHON_SCRIPT'
+import requests
+import json
+import time
+from flask import Flask, request, jsonify
+from threading import Thread, Event
+
+# Configuration
+CRAWL4AI_BASE_URL = "http://localhost:11235"
+WEBHOOK_BASE_URL = "http://localhost:8080"
+
+# Flask app for webhook receiver
+app = Flask(__name__)
+webhook_received = Event()
+webhook_data = {}
+
+@app.route('/webhook', methods=['POST'])
+def handle_webhook():
+    global webhook_data
+    webhook_data = request.json
+    webhook_received.set()
+    print(f"\n✅ Webhook received: {json.dumps(webhook_data, indent=2)}")
+    return jsonify({"status": "received"}), 200
+
+def start_webhook_server():
+    app.run(host='0.0.0.0', port=8080, debug=False, use_reloader=False)
+
+# Start webhook server in background
+webhook_thread = Thread(target=start_webhook_server, daemon=True)
+webhook_thread.start()
+time.sleep(2)
+
+print("🚀 Submitting crawl job with webhook...")
+
+# Submit job with webhook
+payload = {
+    "urls": ["https://example.com"],
+    "browser_config": {"headless": True},
+    "crawler_config": {"cache_mode": "bypass"},
+    "webhook_config": {
+        "webhook_url": f"{WEBHOOK_BASE_URL}/webhook",
+        "webhook_data_in_payload": True
+    }
+}
+
+response = requests.post(
+    f"{CRAWL4AI_BASE_URL}/crawl/job",
+    json=payload,
+    headers={"Content-Type": "application/json"}
+)
+
+if not response.ok:
+    print(f"❌ Failed to submit job: {response.text}")
+    exit(1)
+
+task_id = response.json()['task_id']
+print(f"✅ Job submitted successfully, task_id: {task_id}")
+
+# Wait for webhook (with timeout)
+print("⏳ Waiting for webhook notification...")
+if webhook_received.wait(timeout=60):
+    print(f"✅ Webhook received!")
+    print(f"   Task ID: {webhook_data.get('task_id')}")
+    print(f"   Status: {webhook_data.get('status')}")
+    print(f"   URLs: {webhook_data.get('urls')}")
+
+    if webhook_data.get('status') == 'completed':
+        if 'data' in webhook_data:
+            print(f"   ✅ Data included in webhook payload")
+            results = webhook_data['data'].get('results', [])
+            if results:
+                print(f"   📄 Crawled {len(results)} URL(s)")
+                for result in results:
+                    print(f"      - {result.get('url')}: {len(result.get('markdown', ''))} chars")
+        print("\n🎉 Webhook test PASSED!")
+        exit(0)
+    else:
+        print(f"   ❌ Job failed: {webhook_data.get('error')}")
+        exit(1)
+else:
+    print("❌ Webhook not received within 60 seconds")
+    # Try polling as fallback
+    print("⏳ Trying to poll job status...")
+    for i in range(10):
+        status_response = requests.get(f"{CRAWL4AI_BASE_URL}/crawl/job/{task_id}")
+        if status_response.ok:
+            status = status_response.json()
+            print(f"   Status: {status.get('status')}")
+            if status.get('status') in ['completed', 'failed']:
+                break
+        time.sleep(2)
+    exit(1)
+PYTHON_SCRIPT
+
+# Install Flask for webhook receiver
+pip install -q flask
+
+# Run the webhook test
+log_info "Running webhook test..."
+python3 /tmp/test_webhook.py &
+WEBHOOK_PID=$!
+
+# Wait for test to complete
+wait $WEBHOOK_PID
+TEST_EXIT_CODE=$?
+
+# Step 7: Verify results
+log_info "Step 7: Verifying test results..."
+if [ $TEST_EXIT_CODE -eq 0 ]; then
+    log_success "✅ Webhook test PASSED!"
+else
+    log_error "❌ Webhook test FAILED (exit code: $TEST_EXIT_CODE)"
+    log_info "Server logs:"
+    tail -100 /tmp/crawl4ai_server.log
+    exit 1
+fi
+
+# Step 8: Cleanup happens automatically via trap
+log_success "All tests completed successfully! 🎉"
+log_info "Cleanup will happen automatically..."