fix(logger): ensure logger is a Logger instance in crawling strategies. ref #1437

- Fix URLPatternFilter serialization by preventing private __slots__ from being serialized as constructor params
  - Add public attributes to URLPatternFilter to store original constructor parameters for proper serialization
  - Handle property descriptors in CrawlResult.model_dump() to prevent JSON serialization errors
  - Ensure filter chains work correctly with Docker client and REST API

  The issue occurred because:
  1. Private implementation details (_simple_suffixes, etc.) were being serialized and passed as constructor arguments during deserialization
  2. Property descriptors were being included in the serialized output, causing "Object of type property is not JSON serializable" errors

  Changes:
  - async_configs.py: Comment out __slots__ serialization logic (lines 100-109)
  - filters.py: Add patterns, use_glob, reverse to URLPatternFilter __slots__ and store as public attributes
  - models.py: Convert property descriptors to strings in model_dump() instead of including them directly

crawl4ai/async_configs.py

@@ -97,13 +97,16 @@ def to_serializable_dict(obj: Any, ignore_default_value : bool = False) -> Dict:
                 if value != param.default and not ignore_default_value:
                     current_values[name] = to_serializable_dict(value)
         
-        if hasattr(obj, '__slots__'):
-            for slot in obj.__slots__:
-                if slot.startswith('_'):  # Handle private slots
-                    attr_name = slot[1:]  # Remove leading '_'
-                    value = getattr(obj, slot, None)
-                    if value is not None:
-                        current_values[attr_name] = to_serializable_dict(value)
+        # Don't serialize private __slots__ - they're internal implementation details
+        # not constructor parameters. This was causing URLPatternFilter to fail
+        # because _simple_suffixes was being serialized as 'simple_suffixes'
+        # if hasattr(obj, '__slots__'):
+        #     for slot in obj.__slots__:
+        #         if slot.startswith('_'):  # Handle private slots
+        #             attr_name = slot[1:]  # Remove leading '_'
+        #             value = getattr(obj, slot, None)
+        #             if value is not None:
+        #                 current_values[attr_name] = to_serializable_dict(value)
 
             
         

crawl4ai/deep_crawling/bff_strategy.py

@@ -47,7 +47,13 @@ class BestFirstCrawlingStrategy(DeepCrawlStrategy):
         self.url_scorer = url_scorer
         self.include_external = include_external
         self.max_pages = max_pages
-        self.logger = logger or logging.getLogger(__name__)
+        # self.logger = logger or logging.getLogger(__name__)
+        # Ensure logger is always a Logger instance, not a dict from serialization
+        if isinstance(logger, logging.Logger):
+            self.logger = logger
+        else:
+            # Create a new logger if logger is None, dict, or any other non-Logger type
+            self.logger = logging.getLogger(__name__)
         self.stats = TraversalStats(start_time=datetime.now())
         self._cancel_event = asyncio.Event()
         self._pages_crawled = 0

crawl4ai/deep_crawling/bfs_strategy.py

@@ -38,7 +38,13 @@ class BFSDeepCrawlStrategy(DeepCrawlStrategy):
         self.include_external = include_external
         self.score_threshold = score_threshold
         self.max_pages = max_pages
-        self.logger = logger or logging.getLogger(__name__)
+        # self.logger = logger or logging.getLogger(__name__)
+        # Ensure logger is always a Logger instance, not a dict from serialization
+        if isinstance(logger, logging.Logger):
+            self.logger = logger
+        else:
+            # Create a new logger if logger is None, dict, or any other non-Logger type
+            self.logger = logging.getLogger(__name__)
         self.stats = TraversalStats(start_time=datetime.now())
         self._cancel_event = asyncio.Event()
         self._pages_crawled = 0

crawl4ai/deep_crawling/filters.py

@@ -120,6 +120,9 @@ class URLPatternFilter(URLFilter):
     """Pattern filter balancing speed and completeness"""
 
     __slots__ = (
+        "patterns",  # Store original patterns for serialization
+        "use_glob",  # Store original use_glob for serialization  
+        "reverse",   # Store original reverse for serialization
         "_simple_suffixes",
         "_simple_prefixes",
         "_domain_patterns",
@@ -142,6 +145,11 @@ class URLPatternFilter(URLFilter):
         reverse: bool = False,
     ):
         super().__init__()
+        # Store original constructor params for serialization
+        self.patterns = patterns
+        self.use_glob = use_glob
+        self.reverse = reverse
+        
         self._reverse = reverse
         patterns = [patterns] if isinstance(patterns, (str, Pattern)) else patterns
 

crawl4ai/models.py

@@ -253,6 +253,16 @@ class CrawlResult(BaseModel):
         requirements change, this is where you would update the logic.
         """
         result = super().model_dump(*args, **kwargs)
+        
+        # Remove any property descriptors that might have been included
+        # These deprecated properties should not be in the serialized output
+        for key in ['fit_html', 'fit_markdown', 'markdown_v2']:
+            if key in result and isinstance(result[key], property):
+                # del result[key]
+                # Nasrin: I decided to convert it to string instead of removing it.
+                result[key] = str(result[key])
+        
+        # Add the markdown field properly
         if self._markdown is not None:
             result["markdown"] = self._markdown.model_dump() 
         return result

deploy/docker/README.md

@@ -692,7 +692,8 @@ app:
 # Default LLM Configuration
 llm:
   provider: "openai/gpt-4o-mini"  # Can be overridden by LLM_PROVIDER env var
-  # api_key: sk-...  # If you pass the API key directly (not recommended)
+  api_key_env: "OPENAI_API_KEY"
+  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored
 
 # Redis Configuration (Used by internal Redis server managed by supervisord)
 redis:

deploy/docker/api.py

@@ -96,7 +96,7 @@ async def handle_llm_qa(
         response = perform_completion_with_backoff(
             provider=config["llm"]["provider"],
             prompt_with_variables=prompt,
-            api_token=get_llm_api_key(config)  # Returns None to let litellm handle it
+            api_token=get_llm_api_key(config)
         )
 
         return response.choices[0].message.content
@@ -127,7 +127,7 @@ async def process_llm_extraction(
                 "error": error_msg
             })
             return
-        api_key = get_llm_api_key(config, provider)  # Returns None to let litellm handle it
+        api_key = get_llm_api_key(config, provider)
         llm_strategy = LLMExtractionStrategy(
             llm_config=LLMConfig(
                 provider=provider or config["llm"]["provider"],
@@ -203,7 +203,7 @@ async def handle_markdown_request(
                 FilterType.LLM: LLMContentFilter(
                     llm_config=LLMConfig(
                         provider=provider or config["llm"]["provider"],
-                        api_token=get_llm_api_key(config, provider),  # Returns None to let litellm handle it
+                        api_token=get_llm_api_key(config, provider),
                     ),
                     instruction=query or "Extract main content"
                 )

deploy/docker/config.yml

@@ -11,7 +11,8 @@ app:
 # Default LLM Configuration
 llm:
   provider: "openai/gpt-4o-mini"
-  # api_key: sk-...  # If you pass the API key directly (not recommended)
+  api_key_env: "OPENAI_API_KEY"
+  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored
 
 # Redis Configuration
 redis:

deploy/docker/utils.py

@@ -71,7 +71,7 @@ def decode_redis_hash(hash_data: Dict[bytes, bytes]) -> Dict[str, str]:
 
 
 
-def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> Optional[str]:
+def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> str:
     """Get the appropriate API key based on the LLM provider.
     
     Args:
@@ -79,14 +79,19 @@ def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> Optional[st
         provider: Optional provider override (e.g., "openai/gpt-4")
     
     Returns:
-        The API key if directly configured, otherwise None to let litellm handle it
+        The API key for the provider, or empty string if not found
     """
-    # Check if direct API key is configured (for backward compatibility)
+        
+    # Use provided provider or fall back to config
+    if not provider:
+        provider = config["llm"]["provider"]
+    
+    # Check if direct API key is configured
     if "api_key" in config["llm"]:
         return config["llm"]["api_key"]
     
-    # Return None - litellm will automatically find the right environment variable
-    return None
+    # Fall back to the configured api_key_env if no match
+    return os.environ.get(config["llm"].get("api_key_env", ""), "")
 
 
 def validate_llm_provider(config: Dict, provider: Optional[str] = None) -> tuple[bool, str]:
@@ -99,12 +104,16 @@ def validate_llm_provider(config: Dict, provider: Optional[str] = None) -> tuple
     Returns:
         Tuple of (is_valid, error_message)
     """
-    # If a direct API key is configured, validation passes
-    if "api_key" in config["llm"]:
-        return True, ""
+    # Use provided provider or fall back to config
+    if not provider:
+        provider = config["llm"]["provider"]
+    
+    # Get the API key for this provider
+    api_key = get_llm_api_key(config, provider)
+    
+    if not api_key:
+        return False, f"No API key found for provider '{provider}'. Please set the appropriate environment variable."
     
-    # Otherwise, trust that litellm will find the appropriate environment variable
-    # We can't easily validate this without reimplementing litellm's logic
     return True, ""
 
 

docs/md_v2/core/docker-deployment.md

@@ -176,7 +176,7 @@ The Docker setup now supports flexible LLM provider configuration through three
 
 3. **Config File Default**: Falls back to `config.yml` (default: `openai/gpt-4o-mini`)
 
-The system automatically selects the appropriate API key based on the provider. LiteLLM handles finding the correct environment variable for each provider (e.g., OPENAI_API_KEY for OpenAI, GEMINI_API_TOKEN for Google Gemini, etc.).
+The system automatically selects the appropriate API key based on the configured `api_key_env` in the config file.
 
 #### 3. Build and Run with Compose
 
@@ -693,7 +693,8 @@ app:
 # Default LLM Configuration
 llm:
   provider: "openai/gpt-4o-mini"  # Can be overridden by LLM_PROVIDER env var
-  # api_key: sk-...  # If you pass the API key directly (not recommended)
+  api_key_env: "OPENAI_API_KEY"
+  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored
 
 # Redis Configuration (Used by internal Redis server managed by supervisord)
 redis:

tests/docker/test_filter_deep_crawl.py

@@ -0,0 +1,201 @@
+"""
+Test the complete fix for both the filter serialization and JSON serialization issues.
+"""
+
+import asyncio
+import httpx
+
+from crawl4ai import BrowserConfig, CacheMode, CrawlerRunConfig
+from crawl4ai.deep_crawling import BFSDeepCrawlStrategy, FilterChain, URLPatternFilter
+
+BASE_URL = "http://localhost:11234/"  # Adjust port as needed
+
+async def test_with_docker_client():
+    """Test using the Docker client (same as 1419.py)."""
+    from crawl4ai.docker_client import Crawl4aiDockerClient
+    
+    print("=" * 60)
+    print("Testing with Docker Client")
+    print("=" * 60)
+    
+    try:
+        async with Crawl4aiDockerClient(
+            base_url=BASE_URL,
+            verbose=True,
+        ) as client:
+            
+            # Create filter chain - testing the serialization fix
+            filter_chain = [
+                URLPatternFilter(
+                    # patterns=["*about*", "*privacy*", "*terms*"],
+                    patterns=["*advanced*"],
+                    reverse=True
+                ),
+            ]
+            
+            crawler_config = CrawlerRunConfig(
+                deep_crawl_strategy=BFSDeepCrawlStrategy(
+                    max_depth=2,  # Keep it shallow for testing
+                    # max_pages=5,  # Limit pages for testing
+                    filter_chain=FilterChain(filter_chain)
+                ),
+                cache_mode=CacheMode.BYPASS,
+            )
+            
+            print("\n1. Testing crawl with filters...")
+            results = await client.crawl(
+                ["https://docs.crawl4ai.com"],  # Simple test page
+                browser_config=BrowserConfig(headless=True),
+                crawler_config=crawler_config,
+            )
+            
+            if results:
+                print(f"✅ Crawl succeeded! Type: {type(results)}")
+                if hasattr(results, 'success'):
+                    print(f"✅ Results success: {results.success}")
+                    # Test that we can iterate results without JSON errors
+                    if hasattr(results, '__iter__'):
+                        for i, result in enumerate(results):
+                            if hasattr(result, 'url'):
+                                print(f"   Result {i}: {result.url[:50]}...")
+                            else:
+                                print(f"   Result {i}: {str(result)[:50]}...")
+                else:
+                    # Handle list of results
+                    print(f"✅ Got {len(results)} results")
+                    for i, result in enumerate(results[:3]):  # Show first 3
+                        print(f"   Result {i}: {result.url[:50]}...")
+            else:
+                print("❌ Crawl failed - no results returned")
+                return False
+                
+        print("\n✅ Docker client test completed successfully!")
+        return True
+        
+    except Exception as e:
+        print(f"❌ Docker client test failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+
+async def test_with_rest_api():
+    """Test using REST API directly."""
+    print("\n" + "=" * 60)
+    print("Testing with REST API")
+    print("=" * 60)
+    
+    # Create filter configuration
+    deep_crawl_strategy_payload = {
+        "type": "BFSDeepCrawlStrategy",
+        "params": {
+            "max_depth": 2,
+            # "max_pages": 5,
+            "filter_chain": {
+                "type": "FilterChain",
+                "params": {
+                    "filters": [
+                        {
+                            "type": "URLPatternFilter",
+                            "params": {
+                                "patterns": ["*advanced*"],
+                                "reverse": True
+                            }
+                        }
+                    ]
+                }
+            }
+        }
+    }
+    
+    crawl_payload = {
+        "urls": ["https://docs.crawl4ai.com"],
+        "browser_config": {"type": "BrowserConfig", "params": {"headless": True}},
+        "crawler_config": {
+            "type": "CrawlerRunConfig",
+            "params": {
+                "deep_crawl_strategy": deep_crawl_strategy_payload,
+                "cache_mode": "bypass"
+            }
+        }
+    }
+    
+    try:
+        async with httpx.AsyncClient() as client:
+            print("\n1. Sending crawl request to REST API...")
+            response = await client.post(
+                f"{BASE_URL}crawl",
+                json=crawl_payload,
+                timeout=30
+            )
+            
+            if response.status_code == 200:
+                print(f"✅ REST API returned 200 OK")
+                data = response.json()
+                if data.get("success"):
+                    results = data.get("results", [])
+                    print(f"✅ Got {len(results)} results")
+                    for i, result in enumerate(results[:3]):
+                        print(f"   Result {i}: {result.get('url', 'unknown')[:50]}...")
+                else:
+                    print(f"❌ Crawl not successful: {data}")
+                    return False
+            else:
+                print(f"❌ REST API returned {response.status_code}")
+                print(f"   Response: {response.text[:500]}")
+                return False
+                
+        print("\n✅ REST API test completed successfully!")
+        return True
+        
+    except Exception as e:
+        print(f"❌ REST API test failed: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+
+async def main():
+    """Run all tests."""
+    print("\n🧪 TESTING COMPLETE FIX FOR DOCKER FILTER AND JSON ISSUES")
+    print("=" * 60)
+    print("Make sure the server is running with the updated code!")
+    print("=" * 60)
+    
+    results = []
+    
+    # Test 1: Docker client
+    docker_passed = await test_with_docker_client()
+    results.append(("Docker Client", docker_passed))
+    
+    # Test 2: REST API
+    rest_passed = await test_with_rest_api()
+    results.append(("REST API", rest_passed))
+    
+    # Summary
+    print("\n" + "=" * 60)
+    print("FINAL TEST SUMMARY")
+    print("=" * 60)
+    
+    all_passed = True
+    for test_name, passed in results:
+        status = "✅ PASSED" if passed else "❌ FAILED"
+        print(f"{test_name:20} {status}")
+        if not passed:
+            all_passed = False
+    
+    print("=" * 60)
+    if all_passed:
+        print("🎉 ALL TESTS PASSED! Both issues are fully resolved!")
+        print("\nThe fixes:")
+        print("1. Filter serialization: Fixed by not serializing private __slots__")
+        print("2. JSON serialization: Fixed by removing property descriptors from model_dump()")
+    else:
+        print("⚠️ Some tests failed. Please check the server logs for details.")
+    
+    return 0 if all_passed else 1
+
+
+if __name__ == "__main__":
+    import sys
+    sys.exit(asyncio.run(main()))