#1490 feat(ManagedBrowser): add viewport size configuration for browser launch

Fix/proxy deprecation

.gitignore

@@ -265,7 +265,7 @@ CLAUDE.md
 tests/**/test_site
 tests/**/reports
 tests/**/benchmark_reports
-
+test_scripts/
 docs/**/data
 .codecat/
 

CHANGELOG.md

@@ -5,6 +5,16 @@ All notable changes to Crawl4AI will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Added
+- **🔒 HTTPS Preservation for Internal Links**: New `preserve_https_for_internal_links` configuration flag
+  - Maintains HTTPS scheme for internal links even when servers redirect to HTTP
+  - Prevents security downgrades during deep crawling
+  - Useful for security-conscious crawling and sites supporting both protocols
+  - Fully backward compatible with opt-in flag (default: `False`)
+  - Fixes issue #1410 where HTTPS URLs were being downgraded to HTTP
+
 ## [0.7.3] - 2025-08-09
 
 ### Added

Makefile.telemetry

@@ -1,136 +0,0 @@
-# Makefile for Crawl4AI Telemetry Testing
-# Usage: make test-telemetry, make test-unit, make test-integration, etc.
-
-.PHONY: help test-all test-telemetry test-unit test-integration test-privacy test-performance test-slow test-coverage test-verbose clean
-
-# Default Python executable
-PYTHON := .venv/bin/python
-PYTEST := $(PYTHON) -m pytest
-
-help:
-	@echo "Crawl4AI Telemetry Testing Commands:"
-	@echo ""
-	@echo "  test-all              Run all telemetry tests"
-	@echo "  test-telemetry        Run all telemetry tests (same as test-all)"
-	@echo "  test-unit             Run unit tests only"
-	@echo "  test-integration      Run integration tests only"
-	@echo "  test-privacy          Run privacy compliance tests only"
-	@echo "  test-performance      Run performance tests only"
-	@echo "  test-slow             Run slow tests only"
-	@echo "  test-coverage         Run tests with coverage report"
-	@echo "  test-verbose          Run tests with verbose output"
-	@echo "  test-specific TEST=   Run specific test (e.g., make test-specific TEST=test_telemetry.py::TestTelemetryConfig)"
-	@echo "  clean                 Clean test artifacts"
-	@echo ""
-	@echo "Environment Variables:"
-	@echo "  CRAWL4AI_TELEMETRY_TEST_REAL=1  Enable real telemetry during tests"
-	@echo "  PYTEST_ARGS                    Additional pytest arguments"
-
-# Run all telemetry tests
-test-all test-telemetry:
-	$(PYTEST) tests/telemetry/ -v
-
-# Run unit tests only
-test-unit:
-	$(PYTEST) tests/telemetry/ -m "unit" -v
-
-# Run integration tests only  
-test-integration:
-	$(PYTEST) tests/telemetry/ -m "integration" -v
-
-# Run privacy compliance tests only
-test-privacy:
-	$(PYTEST) tests/telemetry/ -m "privacy" -v
-
-# Run performance tests only
-test-performance:
-	$(PYTEST) tests/telemetry/ -m "performance" -v
-
-# Run slow tests only
-test-slow:
-	$(PYTEST) tests/telemetry/ -m "slow" -v
-
-# Run tests with coverage
-test-coverage:
-	$(PYTEST) tests/telemetry/ --cov=crawl4ai.telemetry --cov-report=html --cov-report=term-missing -v
-
-# Run tests with verbose output
-test-verbose:
-	$(PYTEST) tests/telemetry/ -vvv --tb=long
-
-# Run specific test
-test-specific:
-	$(PYTEST) tests/telemetry/$(TEST) -v
-
-# Run tests excluding slow ones
-test-fast:
-	$(PYTEST) tests/telemetry/ -m "not slow" -v
-
-# Run tests in parallel
-test-parallel:
-	$(PYTEST) tests/telemetry/ -n auto -v
-
-# Clean test artifacts
-clean:
-	rm -rf .pytest_cache/
-	rm -rf htmlcov/
-	rm -rf .coverage
-	find tests/ -name "*.pyc" -delete
-	find tests/ -name "__pycache__" -type d -exec rm -rf {} +
-	rm -rf tests/telemetry/__pycache__/
-
-# Lint test files
-lint-tests:
-	$(PYTHON) -m flake8 tests/telemetry/
-	$(PYTHON) -m pylint tests/telemetry/
-
-# Type check test files
-typecheck-tests:
-	$(PYTHON) -m mypy tests/telemetry/
-
-# Run all quality checks
-check-tests: lint-tests typecheck-tests test-unit
-
-# Install test dependencies
-install-test-deps:
-	$(PYTHON) -m pip install pytest pytest-asyncio pytest-mock pytest-cov pytest-xdist
-
-# Setup development environment for testing
-setup-dev:
-	$(PYTHON) -m pip install -e .
-	$(MAKE) install-test-deps
-
-# Generate test report
-test-report:
-	$(PYTEST) tests/telemetry/ --html=test-report.html --self-contained-html -v
-
-# Run performance benchmarks
-benchmark:
-	$(PYTEST) tests/telemetry/test_privacy_performance.py::TestTelemetryPerformance -v --benchmark-only
-
-# Test different environments
-test-docker-env:
-	CRAWL4AI_DOCKER=true $(PYTEST) tests/telemetry/ -k "docker" -v
-
-test-cli-env:
-	$(PYTEST) tests/telemetry/ -k "cli" -v
-
-# Validate telemetry implementation
-validate:
-	@echo "Running telemetry validation suite..."
-	$(MAKE) test-unit
-	$(MAKE) test-privacy
-	$(MAKE) test-performance
-	@echo "Validation complete!"
-
-# Debug failing tests
-debug:
-	$(PYTEST) tests/telemetry/ --pdb -x -v
-
-# Show test markers
-show-markers:
-	$(PYTEST) --markers
-
-# Show test collection (dry run)
-show-tests:
-	$(PYTEST) tests/telemetry/ --collect-only -q

README.md

@@ -373,7 +373,7 @@ async def main():
     
     async with AsyncWebCrawler(config=browser_config) as crawler:
         result = await crawler.arun(
-            url="https://docs.micronaut.io/4.7.6/guide/",
+            url="https://docs.micronaut.io/4.9.9/guide/",
             config=run_config
         )
         print(len(result.markdown.raw_markdown))
@@ -425,7 +425,7 @@ async def main():
             "type": "attribute",
             "attribute": "src"
         }
-    }
+    ]
 }
 
     extraction_strategy = JsonCssExtractionStrategy(schema, verbose=True)

TELEMETRY_TESTING_IMPLEMENTATION.md

@@ -1,190 +0,0 @@
-# Crawl4AI Telemetry Testing Implementation
-
-## Overview
-
-This document summarizes the comprehensive testing strategy implementation for Crawl4AI's opt-in telemetry system. The implementation provides thorough test coverage across unit tests, integration tests, privacy compliance tests, and performance tests.
-
-## Implementation Summary
-
-### 📊 Test Statistics
-- **Total Tests**: 40 tests
-- **Success Rate**: 100% (40/40 passing)
-- **Test Categories**: 4 categories (Unit, Integration, Privacy, Performance)
-- **Code Coverage**: 51% (625 statements, 308 missing)
-
-### 🗂️ Test Structure
-
-#### 1. **Unit Tests** (`tests/telemetry/test_telemetry.py`)
-- `TestTelemetryConfig`: Configuration management and persistence
-- `TestEnvironmentDetection`: CLI, Docker, API server environment detection
-- `TestTelemetryManager`: Singleton pattern and exception capture
-- `TestConsentManager`: Docker default behavior and environment overrides
-- `TestPublicAPI`: Public enable/disable/status functions
-- `TestIntegration`: Crawler exception capture integration
-
-#### 2. **Integration Tests** (`tests/telemetry/test_integration.py`)
-- `TestTelemetryCLI`: CLI command testing (status, enable, disable)
-- `TestAsyncWebCrawlerIntegration`: Real crawler integration with decorators
-- `TestDockerIntegration`: Docker environment-specific behavior
-- `TestTelemetryProviderIntegration`: Sentry provider initialization and fallbacks
-
-#### 3. **Privacy & Performance Tests** (`tests/telemetry/test_privacy_performance.py`)
-- `TestTelemetryPrivacy`: Data sanitization and PII protection
-- `TestTelemetryPerformance`: Decorator overhead measurement
-- `TestTelemetryScalability`: Multiple and concurrent exception handling
-
-#### 4. **Hello World Test** (`tests/telemetry/test_hello_world_telemetry.py`)
-- Basic telemetry functionality validation
-
-### 🔧 Testing Infrastructure
-
-#### **Pytest Configuration** (`pytest.ini`)
-```ini
-[pytest]
-testpaths = tests/telemetry
-markers =
-    unit: Unit tests
-    integration: Integration tests  
-    privacy: Privacy compliance tests
-    performance: Performance tests
-asyncio_mode = auto
-```
-
-#### **Test Fixtures** (`tests/conftest.py`)
-- `temp_config_dir`: Temporary configuration directory
-- `enabled_telemetry_config`: Pre-configured enabled telemetry
-- `disabled_telemetry_config`: Pre-configured disabled telemetry
-- `mock_sentry_provider`: Mocked Sentry provider for testing
-
-#### **Makefile Targets** (`Makefile.telemetry`)
-```makefile
-test-all: Run all telemetry tests
-test-unit: Run unit tests only
-test-integration: Run integration tests only  
-test-privacy: Run privacy tests only
-test-performance: Run performance tests only
-test-coverage: Run tests with coverage report
-test-watch: Run tests in watch mode
-test-parallel: Run tests in parallel
-```
-
-## 🎯 Key Features Tested
-
-### Privacy Compliance
-- ✅ No URLs captured in telemetry data
-- ✅ No content captured in telemetry data  
-- ✅ No PII (personally identifiable information) captured
-- ✅ Sanitized context only (error types, stack traces without content)
-
-### Performance Impact
-- ✅ Telemetry decorator overhead < 1ms
-- ✅ Async decorator overhead < 1ms
-- ✅ Disabled telemetry has minimal performance impact
-- ✅ Configuration loading performance acceptable
-- ✅ Multiple exception capture scalability
-- ✅ Concurrent exception capture handling
-
-### Integration Points
-- ✅ CLI command integration (status, enable, disable)
-- ✅ AsyncWebCrawler decorator integration
-- ✅ Docker environment auto-detection
-- ✅ Sentry provider initialization
-- ✅ Graceful degradation without Sentry
-- ✅ Environment variable overrides
-
-### Core Functionality
-- ✅ Configuration persistence and loading
-- ✅ Consent management (Docker defaults, user prompts)
-- ✅ Environment detection (CLI, Docker, Jupyter, etc.)
-- ✅ Singleton pattern for TelemetryManager
-- ✅ Exception capture and forwarding
-- ✅ Provider abstraction (Sentry, Null)
-
-## 🚀 Usage Examples
-
-### Run All Tests
-```bash
-make -f Makefile.telemetry test-all
-```
-
-### Run Specific Test Categories
-```bash
-# Unit tests only
-make -f Makefile.telemetry test-unit
-
-# Integration tests only  
-make -f Makefile.telemetry test-integration
-
-# Privacy tests only
-make -f Makefile.telemetry test-privacy
-
-# Performance tests only
-make -f Makefile.telemetry test-performance
-```
-
-### Coverage Report
-```bash
-make -f Makefile.telemetry test-coverage
-```
-
-### Parallel Execution
-```bash
-make -f Makefile.telemetry test-parallel
-```
-
-## 📁 File Structure
-
-```
-tests/
-├── conftest.py                          # Shared pytest fixtures
-└── telemetry/
-    ├── test_hello_world_telemetry.py    # Basic functionality test
-    ├── test_telemetry.py                # Unit tests
-    ├── test_integration.py              # Integration tests
-    └── test_privacy_performance.py      # Privacy & performance tests
-
-# Configuration
-pytest.ini                              # Pytest configuration with markers
-Makefile.telemetry                      # Convenient test execution targets
-```
-
-## 🔍 Test Isolation & Mocking
-
-### Environment Isolation
-- Tests run in isolated temporary directories
-- Environment variables are properly mocked/isolated
-- No interference between test runs
-- Clean state for each test
-
-### Mock Strategies
-- `unittest.mock` for external dependencies
-- Temporary file systems for configuration testing
-- Subprocess mocking for CLI command testing
-- Time measurement for performance testing
-
-## 📈 Coverage Analysis
-
-Current test coverage: **51%** (625 statements)
-
-### Well-Covered Areas:
-- Core configuration management (78%)
-- Telemetry initialization (69%)
-- Environment detection (64%)
-
-### Areas for Future Enhancement:
-- Consent management UI (20% - interactive prompts)
-- Sentry provider implementation (25% - network calls)
-- Base provider abstractions (49% - error handling paths)
-
-## 🎉 Implementation Success
-
-The comprehensive testing strategy has been **successfully implemented** with:
-
-- ✅ **100% test pass rate** (40/40 tests passing)
-- ✅ **Complete test infrastructure** (fixtures, configuration, targets)
-- ✅ **Privacy compliance verification** (no PII, URLs, or content captured)  
-- ✅ **Performance validation** (minimal overhead confirmed)
-- ✅ **Integration testing** (CLI, Docker, AsyncWebCrawler)
-- ✅ **CI/CD ready** (Makefile targets for automation)
-
-The telemetry system now has robust test coverage ensuring reliability, privacy compliance, and performance characteristics while maintaining comprehensive validation of all core functionality.

crawl4ai/adaptive_crawler.py

@@ -19,7 +19,7 @@ import re
 from pathlib import Path
 
 from crawl4ai.async_webcrawler import AsyncWebCrawler
-from crawl4ai.async_configs import CrawlerRunConfig, LinkPreviewConfig
+from crawl4ai.async_configs import CrawlerRunConfig, LinkPreviewConfig, LLMConfig
 from crawl4ai.models import Link, CrawlResult
 import numpy as np
 
@@ -178,7 +178,7 @@ class AdaptiveConfig:
     
     # Embedding strategy parameters
     embedding_model: str = "sentence-transformers/all-MiniLM-L6-v2"
-    embedding_llm_config: Optional[Dict] = None  # Separate config for embeddings
+    embedding_llm_config: Optional[Union[LLMConfig, Dict]] = None  # Separate config for embeddings
     n_query_variations: int = 10
     coverage_threshold: float = 0.85
     alpha_shape_alpha: float = 0.5
@@ -250,6 +250,30 @@ class AdaptiveConfig:
         assert 0 <= self.embedding_quality_max_confidence <= 1, "embedding_quality_max_confidence must be between 0 and 1"
         assert self.embedding_quality_scale_factor > 0, "embedding_quality_scale_factor must be positive"
         assert 0 <= self.embedding_min_confidence_threshold <= 1, "embedding_min_confidence_threshold must be between 0 and 1"
+    
+    @property
+    def _embedding_llm_config_dict(self) -> Optional[Dict]:
+        """Convert LLMConfig to dict format for backward compatibility."""
+        if self.embedding_llm_config is None:
+            return None
+        
+        if isinstance(self.embedding_llm_config, dict):
+            # Already a dict - return as-is for backward compatibility
+            return self.embedding_llm_config
+        
+        # Convert LLMConfig object to dict format
+        return {
+            'provider': self.embedding_llm_config.provider,
+            'api_token': self.embedding_llm_config.api_token,
+            'base_url': getattr(self.embedding_llm_config, 'base_url', None),
+            'temperature': getattr(self.embedding_llm_config, 'temperature', None),
+            'max_tokens': getattr(self.embedding_llm_config, 'max_tokens', None),
+            'top_p': getattr(self.embedding_llm_config, 'top_p', None),
+            'frequency_penalty': getattr(self.embedding_llm_config, 'frequency_penalty', None),
+            'presence_penalty': getattr(self.embedding_llm_config, 'presence_penalty', None),
+            'stop': getattr(self.embedding_llm_config, 'stop', None),
+            'n': getattr(self.embedding_llm_config, 'n', None),
+        }
 
 
 class CrawlStrategy(ABC):
@@ -593,7 +617,7 @@ class StatisticalStrategy(CrawlStrategy):
 class EmbeddingStrategy(CrawlStrategy):
     """Embedding-based adaptive crawling using semantic space coverage"""
     
-    def __init__(self, embedding_model: str = None, llm_config: Dict = None):
+    def __init__(self, embedding_model: str = None, llm_config: Union[LLMConfig, Dict] = None):
         self.embedding_model = embedding_model or "sentence-transformers/all-MiniLM-L6-v2"
         self.llm_config = llm_config
         self._embedding_cache = {}
@@ -605,14 +629,24 @@ class EmbeddingStrategy(CrawlStrategy):
         self._kb_embeddings_hash = None  # Track KB changes
         self._validation_embeddings_cache = None  # Cache validation query embeddings
         self._kb_similarity_threshold = 0.95  # Threshold for deduplication
+    
+    def _get_embedding_llm_config_dict(self) -> Dict:
+        """Get embedding LLM config as dict with fallback to default."""
+        if hasattr(self, 'config') and self.config:
+            config_dict = self.config._embedding_llm_config_dict
+            if config_dict:
+                return config_dict
+        
+        # Fallback to default if no config provided
+        return {
+            'provider': 'openai/text-embedding-3-small',
+            'api_token': os.getenv('OPENAI_API_KEY')
+        }
         
     async def _get_embeddings(self, texts: List[str]) -> Any:
         """Get embeddings using configured method"""
         from .utils import get_text_embeddings
-        embedding_llm_config = {
-            'provider': 'openai/text-embedding-3-small',
-            'api_token': os.getenv('OPENAI_API_KEY')
-        }
+        embedding_llm_config = self._get_embedding_llm_config_dict()
         return await get_text_embeddings(
             texts, 
             embedding_llm_config,
@@ -679,8 +713,20 @@ class EmbeddingStrategy(CrawlStrategy):
         Return as a JSON array of strings."""
         
         # Use the LLM for query generation
-        provider = self.llm_config.get('provider', 'openai/gpt-4o-mini') if self.llm_config else 'openai/gpt-4o-mini'
-        api_token = self.llm_config.get('api_token') if self.llm_config else None
+        # Convert LLMConfig to dict if needed
+        llm_config_dict = None
+        if self.llm_config:
+            if isinstance(self.llm_config, dict):
+                llm_config_dict = self.llm_config
+            else:
+                # Convert LLMConfig object to dict
+                llm_config_dict = {
+                    'provider': self.llm_config.provider,
+                    'api_token': self.llm_config.api_token
+                }
+        
+        provider = llm_config_dict.get('provider', 'openai/gpt-4o-mini') if llm_config_dict else 'openai/gpt-4o-mini'
+        api_token = llm_config_dict.get('api_token') if llm_config_dict else None
         
         # response = perform_completion_with_backoff(
         #     provider=provider,
@@ -843,10 +889,7 @@ class EmbeddingStrategy(CrawlStrategy):
         
         # Batch embed only uncached links
         if texts_to_embed:
-            embedding_llm_config = {
-                'provider': 'openai/text-embedding-3-small',
-                'api_token': os.getenv('OPENAI_API_KEY')
-            }
+            embedding_llm_config = self._get_embedding_llm_config_dict()
             new_embeddings = await get_text_embeddings(texts_to_embed, embedding_llm_config, self.embedding_model)
 
             # Cache the new embeddings
@@ -1184,10 +1227,7 @@ class EmbeddingStrategy(CrawlStrategy):
             return
             
         # Get embeddings for new texts
-        embedding_llm_config = {
-            'provider': 'openai/text-embedding-3-small',
-            'api_token': os.getenv('OPENAI_API_KEY')
-        }        
+        embedding_llm_config = self._get_embedding_llm_config_dict()      
         new_embeddings = await get_text_embeddings(new_texts, embedding_llm_config, self.embedding_model)
 
         # Deduplicate embeddings before adding to KB
@@ -1256,10 +1296,12 @@ class AdaptiveCrawler:
         if strategy_name == "statistical":
             return StatisticalStrategy()
         elif strategy_name == "embedding":
-            return EmbeddingStrategy(
+            strategy = EmbeddingStrategy(
                 embedding_model=self.config.embedding_model,
                 llm_config=self.config.embedding_llm_config
             )
+            strategy.config = self.config  # Pass config to strategy
+            return strategy
         else:
             raise ValueError(f"Unknown strategy: {strategy_name}")
     

crawl4ai/async_configs.py

@@ -1,5 +1,6 @@
 import os
 from typing import Union
+import warnings
 from .config import (
     DEFAULT_PROVIDER,
     DEFAULT_PROVIDER_API_KEY,
@@ -97,13 +98,16 @@ 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)
 
             
         
@@ -254,24 +258,39 @@ class ProxyConfig:
     
     @staticmethod
     def from_string(proxy_str: str) -> "ProxyConfig":
-        """Create a ProxyConfig from a string in the format 'ip:port:username:password'."""
-        parts = proxy_str.split(":")
-        if len(parts) == 4:  # ip:port:username:password
+        """Create a ProxyConfig from a string.
+
+        Supported formats:
+        - 'http://username:password@ip:port'
+        - 'http://ip:port'
+        - 'socks5://ip:port'
+        - 'ip:port:username:password'
+        - 'ip:port'
+        """
+        s = (proxy_str or "").strip()
+        # URL with credentials
+        if "@" in s and "://" in s:
+            auth_part, server_part = s.split("@", 1)
+            protocol, credentials = auth_part.split("://", 1)
+            if ":" in credentials:
+                username, password = credentials.split(":", 1)
+                return ProxyConfig(
+                    server=f"{protocol}://{server_part}",
+                    username=username,
+                    password=password,
+                )
+        # URL without credentials (keep scheme)
+        if "://" in s and "@" not in s:
+            return ProxyConfig(server=s)
+        # Colon separated forms
+        parts = s.split(":")
+        if len(parts) == 4:
             ip, port, username, password = parts
-            return ProxyConfig(
-                server=f"http://{ip}:{port}",
-                username=username,
-                password=password,
-                ip=ip
-            )
-        elif len(parts) == 2:  # ip:port only
+            return ProxyConfig(server=f"http://{ip}:{port}", username=username, password=password)
+        if len(parts) == 2:
             ip, port = parts
-            return ProxyConfig(
-                server=f"http://{ip}:{port}",
-                ip=ip
-            )
-        else:
-            raise ValueError(f"Invalid proxy string format: {proxy_str}")
+            return ProxyConfig(server=f"http://{ip}:{port}")
+        raise ValueError(f"Invalid proxy string format: {proxy_str}")
     
     @staticmethod
     def from_dict(proxy_dict: Dict) -> "ProxyConfig":
@@ -435,6 +454,7 @@ class BrowserConfig:
         host: str = "localhost",
         enable_stealth: bool = False,
     ):
+        
         self.browser_type = browser_type
         self.headless = headless 
         self.browser_mode = browser_mode
@@ -447,13 +467,22 @@ class BrowserConfig:
         if self.browser_type in ["firefox", "webkit"]:
             self.channel = ""
             self.chrome_channel = ""
+        if proxy:
+            warnings.warn("The 'proxy' parameter is deprecated and will be removed in a future release. Use 'proxy_config' instead.", UserWarning)
         self.proxy = proxy
         self.proxy_config = proxy_config
         if isinstance(self.proxy_config, dict):
             self.proxy_config = ProxyConfig.from_dict(self.proxy_config)
         if isinstance(self.proxy_config, str):
             self.proxy_config = ProxyConfig.from_string(self.proxy_config)
-
+        
+        if self.proxy and self.proxy_config:
+            warnings.warn("Both 'proxy' and 'proxy_config' are provided. 'proxy_config' will take precedence.", UserWarning)
+            self.proxy = None
+        elif self.proxy:
+            # Convert proxy string to ProxyConfig if proxy_config is not provided
+            self.proxy_config = ProxyConfig.from_string(self.proxy)
+            self.proxy = None
 
         self.viewport_width = viewport_width
         self.viewport_height = viewport_height
@@ -831,12 +860,6 @@ class HTTPCrawlerConfig:
         return HTTPCrawlerConfig.from_kwargs(config)
 
 class CrawlerRunConfig():
-    _UNWANTED_PROPS = {
-        'disable_cache' : 'Instead, use cache_mode=CacheMode.DISABLED',
-        'bypass_cache' : 'Instead, use cache_mode=CacheMode.BYPASS',
-        'no_cache_read' : 'Instead, use cache_mode=CacheMode.WRITE_ONLY',
-        'no_cache_write' : 'Instead, use cache_mode=CacheMode.READ_ONLY',
-    }
 
     """
     Configuration class for controlling how the crawler runs each crawl operation.
@@ -1043,6 +1066,12 @@ class CrawlerRunConfig():
 
         url: str = None  # This is not a compulsory parameter
     """
+    _UNWANTED_PROPS = {
+        'disable_cache' : 'Instead, use cache_mode=CacheMode.DISABLED',
+        'bypass_cache' : 'Instead, use cache_mode=CacheMode.BYPASS',
+        'no_cache_read' : 'Instead, use cache_mode=CacheMode.WRITE_ONLY',
+        'no_cache_write' : 'Instead, use cache_mode=CacheMode.READ_ONLY',
+    }
 
     def __init__(
         self,
@@ -1121,6 +1150,7 @@ class CrawlerRunConfig():
         exclude_domains: list = None,
         exclude_internal_links: bool = False,
         score_links: bool = False,
+        preserve_https_for_internal_links: bool = False,
         # Debugging and Logging Parameters
         verbose: bool = True,
         log_console: bool = False,
@@ -1244,6 +1274,7 @@ class CrawlerRunConfig():
         self.exclude_domains = exclude_domains or []
         self.exclude_internal_links = exclude_internal_links
         self.score_links = score_links
+        self.preserve_https_for_internal_links = preserve_https_for_internal_links
 
         # Debugging and Logging Parameters
         self.verbose = verbose
@@ -1517,6 +1548,7 @@ class CrawlerRunConfig():
             exclude_domains=kwargs.get("exclude_domains", []),
             exclude_internal_links=kwargs.get("exclude_internal_links", False),
             score_links=kwargs.get("score_links", False),
+            preserve_https_for_internal_links=kwargs.get("preserve_https_for_internal_links", False),
             # Debugging and Logging Parameters
             verbose=kwargs.get("verbose", True),
             log_console=kwargs.get("log_console", False),
@@ -1623,6 +1655,7 @@ class CrawlerRunConfig():
             "exclude_domains": self.exclude_domains,
             "exclude_internal_links": self.exclude_internal_links,
             "score_links": self.score_links,
+            "preserve_https_for_internal_links": self.preserve_https_for_internal_links,
             "verbose": self.verbose,
             "log_console": self.log_console,
             "capture_network_requests": self.capture_network_requests,

crawl4ai/async_webcrawler.py

@@ -49,9 +49,6 @@ from .utils import (
     preprocess_html_for_schema,
 )
 
-# Import telemetry
-from .telemetry import capture_exception, telemetry_decorator, async_telemetry_decorator
-
 
 class AsyncWebCrawler:
     """
@@ -204,7 +201,6 @@ class AsyncWebCrawler:
         """异步空上下文管理器"""
         yield
 
-    @async_telemetry_decorator
     async def arun(
         self,
         url: str,
@@ -358,6 +354,7 @@ class AsyncWebCrawler:
                     ###############################################################
                     # Process the HTML content, Call CrawlerStrategy.process_html #
                     ###############################################################
+                    from urllib.parse import urlparse
                     crawl_result: CrawlResult = await self.aprocess_html(
                         url=url,
                         html=html,
@@ -368,6 +365,7 @@ class AsyncWebCrawler:
                         verbose=config.verbose,
                         is_raw_html=True if url.startswith("raw:") else False,
                         redirected_url=async_response.redirected_url,
+                        original_scheme=urlparse(url).scheme,
                         **kwargs,
                     )
 
@@ -434,7 +432,6 @@ class AsyncWebCrawler:
                     )
                 )
 
-    @async_telemetry_decorator
     async def aprocess_html(
         self,
         url: str,

crawl4ai/browser_manager.py

@@ -15,6 +15,7 @@ from .js_snippet import load_js_script
 from .config import DOWNLOAD_PAGE_TIMEOUT
 from .async_configs import BrowserConfig, CrawlerRunConfig
 from .utils import get_chromium_path
+import warnings
 
 
 BROWSER_DISABLE_OPTIONS = [
@@ -368,6 +369,9 @@ class ManagedBrowser:
             ]
             if self.headless:
                 flags.append("--headless=new")
+            # Add viewport flag if specified in config
+            if self.browser_config.viewport_height and self.browser_config.viewport_width:
+                flags.append(f"--window-size={self.browser_config.viewport_width},{self.browser_config.viewport_height}")
             # merge common launch flags
             flags.extend(self.build_browser_flags(self.browser_config))
         elif self.browser_type == "firefox":
@@ -741,17 +745,18 @@ class BrowserManager:
             )
             os.makedirs(browser_args["downloads_path"], exist_ok=True)
 
-        if self.config.proxy or self.config.proxy_config:
+        if self.config.proxy:
+            warnings.warn(
+                "BrowserConfig.proxy is deprecated and ignored. Use proxy_config instead.",
+                DeprecationWarning,
+            )
+        if self.config.proxy_config:
             from playwright.async_api import ProxySettings
 
-            proxy_settings = (
-                ProxySettings(server=self.config.proxy)
-                if self.config.proxy
-                else ProxySettings(
-                    server=self.config.proxy_config.server,
-                    username=self.config.proxy_config.username,
-                    password=self.config.proxy_config.password,
-                )
+            proxy_settings = ProxySettings(
+                server=self.config.proxy_config.server,
+                username=self.config.proxy_config.username,
+                password=self.config.proxy_config.password,
             )
             browser_args["proxy"] = proxy_settings
 

crawl4ai/cli.py

@@ -1385,97 +1385,6 @@ def profiles_cmd():
     # Run interactive profile manager
     anyio.run(manage_profiles)
 
-@cli.group("telemetry")
-def telemetry_cmd():
-    """Manage telemetry settings for Crawl4AI
-    
-    Telemetry helps improve Crawl4AI by sending anonymous crash reports.
-    No personal data or crawled content is ever collected.
-    """
-    pass
-
-@telemetry_cmd.command("enable")
-@click.option("--email", "-e", help="Optional email for follow-up on critical issues")
-@click.option("--always/--once", default=True, help="Always send errors (default) or just once")
-def telemetry_enable_cmd(email: Optional[str], always: bool):
-    """Enable telemetry to help improve Crawl4AI
-    
-    Examples:
-        crwl telemetry enable                    # Enable telemetry
-        crwl telemetry enable --email me@ex.com  # Enable with email
-        crwl telemetry enable --once             # Send only next error
-    """
-    from crawl4ai.telemetry import enable
-    
-    try:
-        enable(email=email, always=always, once=not always)
-        console.print("[green]✅ Telemetry enabled successfully[/green]")
-        
-        if email:
-            console.print(f"   Email: {email}")
-        console.print(f"   Mode: {'Always send errors' if always else 'Send next error only'}")
-        
-    except Exception as e:
-        console.print(f"[red]❌ Failed to enable telemetry: {e}[/red]")
-        sys.exit(1)
-
-@telemetry_cmd.command("disable")
-def telemetry_disable_cmd():
-    """Disable telemetry
-    
-    Stop sending anonymous crash reports to help improve Crawl4AI.
-    """
-    from crawl4ai.telemetry import disable
-    
-    try:
-        disable()
-        console.print("[green]✅ Telemetry disabled successfully[/green]")
-    except Exception as e:
-        console.print(f"[red]❌ Failed to disable telemetry: {e}[/red]")
-        sys.exit(1)
-
-@telemetry_cmd.command("status")
-def telemetry_status_cmd():
-    """Show current telemetry status
-    
-    Display whether telemetry is enabled and current settings.
-    """
-    from crawl4ai.telemetry import status
-    
-    try:
-        info = status()
-        
-        # Create status table
-        table = Table(title="Telemetry Status", show_header=False)
-        table.add_column("Setting", style="cyan")
-        table.add_column("Value")
-        
-        # Status emoji
-        status_icon = "✅" if info['enabled'] else "❌"
-        
-        table.add_row("Status", f"{status_icon} {'Enabled' if info['enabled'] else 'Disabled'}")
-        table.add_row("Consent", info['consent'].replace('_', ' ').title())
-        
-        if info['email']:
-            table.add_row("Email", info['email'])
-        
-        table.add_row("Environment", info['environment'])
-        table.add_row("Provider", info['provider'])
-        
-        if info['errors_sent'] > 0:
-            table.add_row("Errors Sent", str(info['errors_sent']))
-        
-        console.print(table)
-        
-        # Add helpful messages
-        if not info['enabled']:
-            console.print("\n[yellow]ℹ️  Telemetry is disabled. Enable it to help improve Crawl4AI:[/yellow]")
-            console.print("   [dim]crwl telemetry enable[/dim]")
-        
-    except Exception as e:
-        console.print(f"[red]❌ Failed to get telemetry status: {e}[/red]")
-        sys.exit(1)
-
 @cli.command(name="")
 @click.argument("url", required=False)
 @click.option("--example", is_flag=True, help="Show usage examples")

crawl4ai/content_scraping_strategy.py

@@ -258,7 +258,11 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
                 continue
 
             try:
-                normalized_href = normalize_url(href, url)
+                normalized_href = normalize_url(
+                    href, url,
+                    preserve_https=kwargs.get('preserve_https_for_internal_links', False),
+                    original_scheme=kwargs.get('original_scheme')
+                )
                 link_data = {
                     "href": normalized_href,
                     "text": link.text_content().strip(),

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
@@ -116,11 +122,6 @@ class BestFirstCrawlingStrategy(DeepCrawlStrategy):
                 
             valid_links.append(base_url)
             
-        # If we have more valid links than capacity, limit them
-        if len(valid_links) > remaining_capacity:
-            valid_links = valid_links[:remaining_capacity]
-            self.logger.info(f"Limiting to {remaining_capacity} URLs due to max_pages limit")
-            
         # Record the new depths and add to next_links
         for url in valid_links:
             depths[url] = new_depth
@@ -140,7 +141,8 @@ class BestFirstCrawlingStrategy(DeepCrawlStrategy):
         """
         queue: asyncio.PriorityQueue = asyncio.PriorityQueue()
         # Push the initial URL with score 0 and depth 0.
-        await queue.put((0, 0, start_url, None))
+        initial_score = self.url_scorer.score(start_url) if self.url_scorer else 0
+        await queue.put((-initial_score, 0, start_url, None))
         visited: Set[str] = set()
         depths: Dict[str, int] = {start_url: 0}
 
@@ -187,7 +189,7 @@ class BestFirstCrawlingStrategy(DeepCrawlStrategy):
                 result.metadata = result.metadata or {}
                 result.metadata["depth"] = depth
                 result.metadata["parent_url"] = parent_url
-                result.metadata["score"] = score
+                result.metadata["score"] = -score
                 
                 # Count only successful crawls toward max_pages limit
                 if result.success:
@@ -208,7 +210,7 @@ class BestFirstCrawlingStrategy(DeepCrawlStrategy):
                     for new_url, new_parent in new_links:
                         new_depth = depths.get(new_url, depth + 1)
                         new_score = self.url_scorer.score(new_url) if self.url_scorer else 0
-                        await queue.put((new_score, new_depth, new_url, new_parent))
+                        await queue.put((-new_score, new_depth, new_url, new_parent))
 
         # End of crawl.
 

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

crawl4ai/telemetry/__init__.py

@@ -1,440 +0,0 @@
-"""
-Crawl4AI Telemetry Module.
-Provides opt-in error tracking to improve stability.
-"""
-
-import os
-import sys
-import functools
-import traceback
-from typing import Optional, Any, Dict, Callable, Type
-from contextlib import contextmanager, asynccontextmanager
-
-from .base import TelemetryProvider, NullProvider
-from .config import TelemetryConfig, TelemetryConsent
-from .consent import ConsentManager
-from .environment import Environment, EnvironmentDetector
-
-
-class TelemetryManager:
-    """
-    Main telemetry manager for Crawl4AI.
-    Coordinates provider, config, and consent management.
-    """
-    
-    _instance: Optional['TelemetryManager'] = None
-    
-    def __init__(self):
-        """Initialize telemetry manager."""
-        self.config = TelemetryConfig()
-        self.consent_manager = ConsentManager(self.config)
-        self.environment = EnvironmentDetector.detect()
-        self._provider: Optional[TelemetryProvider] = None
-        self._initialized = False
-        self._error_count = 0
-        self._max_errors = 100  # Prevent telemetry spam
-        
-        # Load provider based on config
-        self._setup_provider()
-    
-    @classmethod
-    def get_instance(cls) -> 'TelemetryManager':
-        """
-        Get singleton instance of telemetry manager.
-        
-        Returns:
-            TelemetryManager instance
-        """
-        if cls._instance is None:
-            cls._instance = cls()
-        return cls._instance
-    
-    def _setup_provider(self) -> None:
-        """Setup telemetry provider based on configuration."""
-        # Update config from environment
-        self.config.update_from_env()
-        
-        # Check if telemetry is enabled
-        if not self.config.is_enabled():
-            self._provider = NullProvider()
-            return
-        
-        # Try to load Sentry provider
-        try:
-            from .providers.sentry import SentryProvider
-            
-            # Get Crawl4AI version for release tracking
-            try:
-                from crawl4ai import __version__
-                release = f"crawl4ai@{__version__}"
-            except ImportError:
-                release = "crawl4ai@unknown"
-            
-            self._provider = SentryProvider(
-                environment=self.environment.value,
-                release=release
-            )
-            
-            # Initialize provider
-            if not self._provider.initialize():
-                # Fallback to null provider if init fails
-                self._provider = NullProvider()
-                
-        except ImportError:
-            # Sentry not installed - use null provider
-            self._provider = NullProvider()
-        
-        self._initialized = True
-    
-    def capture_exception(
-        self, 
-        exception: Exception,
-        context: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Capture and send an exception.
-        
-        Args:
-            exception: The exception to capture
-            context: Optional additional context
-            
-        Returns:
-            True if exception was sent
-        """
-        # Check error count limit
-        if self._error_count >= self._max_errors:
-            return False
-        
-        # Check consent on first error
-        if self._error_count == 0:
-            consent = self.consent_manager.check_and_prompt()
-            
-            # Update provider if consent changed
-            if consent == TelemetryConsent.DENIED:
-                self._provider = NullProvider()
-                return False
-            elif consent in [TelemetryConsent.ONCE, TelemetryConsent.ALWAYS]:
-                if isinstance(self._provider, NullProvider):
-                    self._setup_provider()
-        
-        # Check if we should send this error
-        if not self.config.should_send_current():
-            return False
-        
-        # Prepare context
-        full_context = EnvironmentDetector.get_environment_context()
-        if context:
-            full_context.update(context)
-        
-        # Add user email if available
-        email = self.config.get_email()
-        if email:
-            full_context['email'] = email
-        
-        # Add source info
-        full_context['source'] = 'crawl4ai'
-        
-        # Send exception
-        try:
-            if self._provider:
-                success = self._provider.send_exception(exception, full_context)
-                if success:
-                    self._error_count += 1
-                return success
-        except Exception:
-            # Telemetry itself failed - ignore
-            pass
-        
-        return False
-    
-    def capture_message(
-        self,
-        message: str,
-        level: str = 'info',
-        context: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Capture a message event.
-        
-        Args:
-            message: Message to send
-            level: Message level (info, warning, error)
-            context: Optional context
-            
-        Returns:
-            True if message was sent
-        """
-        if not self.config.is_enabled():
-            return False
-        
-        payload = {
-            'level': level,
-            'message': message
-        }
-        if context:
-            payload.update(context)
-        
-        try:
-            if self._provider:
-                return self._provider.send_event(message, payload)
-        except Exception:
-            pass
-        
-        return False
-    
-    def enable(
-        self,
-        email: Optional[str] = None,
-        always: bool = True,
-        once: bool = False
-    ) -> None:
-        """
-        Enable telemetry.
-        
-        Args:
-            email: Optional email for follow-up
-            always: If True, always send errors
-            once: If True, send only next error
-        """
-        if once:
-            consent = TelemetryConsent.ONCE
-        elif always:
-            consent = TelemetryConsent.ALWAYS
-        else:
-            consent = TelemetryConsent.ALWAYS
-        
-        self.config.set_consent(consent, email)
-        self._setup_provider()
-        
-        print("✅ Telemetry enabled")
-        if email:
-            print(f"   Email: {email}")
-        print(f"   Mode: {'once' if once else 'always'}")
-    
-    def disable(self) -> None:
-        """Disable telemetry."""
-        self.config.set_consent(TelemetryConsent.DENIED)
-        self._provider = NullProvider()
-        print("✅ Telemetry disabled")
-    
-    def status(self) -> Dict[str, Any]:
-        """
-        Get telemetry status.
-        
-        Returns:
-            Dictionary with status information
-        """
-        return {
-            'enabled': self.config.is_enabled(),
-            'consent': self.config.get_consent().value,
-            'email': self.config.get_email(),
-            'environment': self.environment.value,
-            'provider': type(self._provider).__name__ if self._provider else 'None',
-            'errors_sent': self._error_count
-        }
-    
-    def flush(self) -> None:
-        """Flush any pending telemetry data."""
-        if self._provider:
-            self._provider.flush()
-    
-    def shutdown(self) -> None:
-        """Shutdown telemetry."""
-        if self._provider:
-            self._provider.shutdown()
-
-
-# Global instance
-_telemetry_manager: Optional[TelemetryManager] = None
-
-
-def get_telemetry() -> TelemetryManager:
-    """
-    Get global telemetry manager instance.
-    
-    Returns:
-        TelemetryManager instance
-    """
-    global _telemetry_manager
-    if _telemetry_manager is None:
-        _telemetry_manager = TelemetryManager.get_instance()
-    return _telemetry_manager
-
-
-def capture_exception(
-    exception: Exception,
-    context: Optional[Dict[str, Any]] = None
-) -> bool:
-    """
-    Capture an exception for telemetry.
-    
-    Args:
-        exception: Exception to capture
-        context: Optional context
-        
-    Returns:
-        True if sent successfully
-    """
-    try:
-        return get_telemetry().capture_exception(exception, context)
-    except Exception:
-        return False
-
-
-def telemetry_decorator(func: Callable) -> Callable:
-    """
-    Decorator to capture exceptions from a function.
-    
-    Args:
-        func: Function to wrap
-        
-    Returns:
-        Wrapped function
-    """
-    @functools.wraps(func)
-    def wrapper(*args, **kwargs):
-        try:
-            return func(*args, **kwargs)
-        except Exception as e:
-            # Capture exception
-            capture_exception(e, {
-                'function': func.__name__,
-                'module': func.__module__
-            })
-            # Re-raise the exception
-            raise
-    
-    return wrapper
-
-
-def async_telemetry_decorator(func: Callable) -> Callable:
-    """
-    Decorator to capture exceptions from an async function.
-    
-    Args:
-        func: Async function to wrap
-        
-    Returns:
-        Wrapped async function
-    """
-    @functools.wraps(func)
-    async def wrapper(*args, **kwargs):
-        try:
-            return await func(*args, **kwargs)
-        except Exception as e:
-            # Capture exception
-            capture_exception(e, {
-                'function': func.__name__,
-                'module': func.__module__
-            })
-            # Re-raise the exception
-            raise
-    
-    return wrapper
-
-
-@contextmanager
-def telemetry_context(operation: str):
-    """
-    Context manager for capturing exceptions.
-    
-    Args:
-        operation: Name of the operation
-        
-    Example:
-        with telemetry_context("web_crawl"):
-            # Your code here
-            pass
-    """
-    try:
-        yield
-    except Exception as e:
-        capture_exception(e, {'operation': operation})
-        raise
-
-
-@asynccontextmanager
-async def async_telemetry_context(operation: str):
-    """
-    Async context manager for capturing exceptions in async code.
-    
-    Args:
-        operation: Name of the operation
-        
-    Example:
-        async with async_telemetry_context("async_crawl"):
-            # Your async code here
-            await something()
-    """
-    try:
-        yield
-    except Exception as e:
-        capture_exception(e, {'operation': operation})
-        raise
-
-
-def install_exception_handler():
-    """Install global exception handler for uncaught exceptions."""
-    original_hook = sys.excepthook
-    
-    def telemetry_exception_hook(exc_type, exc_value, exc_traceback):
-        """Custom exception hook with telemetry."""
-        # Don't capture KeyboardInterrupt
-        if not issubclass(exc_type, KeyboardInterrupt):
-            capture_exception(exc_value, {
-                'uncaught': True,
-                'type': exc_type.__name__
-            })
-        
-        # Call original hook
-        original_hook(exc_type, exc_value, exc_traceback)
-    
-    sys.excepthook = telemetry_exception_hook
-
-
-# Public API
-def enable(email: Optional[str] = None, always: bool = True, once: bool = False) -> None:
-    """
-    Enable telemetry.
-    
-    Args:
-        email: Optional email for follow-up
-        always: If True, always send errors (default)
-        once: If True, send only the next error
-    """
-    get_telemetry().enable(email=email, always=always, once=once)
-
-
-def disable() -> None:
-    """Disable telemetry."""
-    get_telemetry().disable()
-
-
-def status() -> Dict[str, Any]:
-    """
-    Get telemetry status.
-    
-    Returns:
-        Dictionary with status information
-    """
-    return get_telemetry().status()
-
-
-# Auto-install exception handler on import
-# (Only for main library usage, not for Docker/API)
-if EnvironmentDetector.detect() not in [Environment.DOCKER, Environment.API_SERVER]:
-    install_exception_handler()
-
-
-__all__ = [
-    'TelemetryManager',
-    'get_telemetry',
-    'capture_exception',
-    'telemetry_decorator',
-    'async_telemetry_decorator',
-    'telemetry_context',
-    'async_telemetry_context',
-    'enable',
-    'disable',
-    'status',
-]

crawl4ai/telemetry/base.py

@@ -1,140 +0,0 @@
-"""
-Base telemetry provider interface for Crawl4AI.
-Provides abstraction for different telemetry backends.
-"""
-
-from abc import ABC, abstractmethod
-from typing import Dict, Any, Optional, Union
-import traceback
-
-
-class TelemetryProvider(ABC):
-    """Abstract base class for telemetry providers."""
-    
-    def __init__(self, **kwargs):
-        """Initialize the provider with optional configuration."""
-        self.config = kwargs
-        self._initialized = False
-    
-    @abstractmethod
-    def initialize(self) -> bool:
-        """
-        Initialize the telemetry provider.
-        Returns True if initialization successful, False otherwise.
-        """
-        pass
-    
-    @abstractmethod
-    def send_exception(
-        self, 
-        exc: Exception, 
-        context: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Send an exception to the telemetry backend.
-        
-        Args:
-            exc: The exception to report
-            context: Optional context data (email, environment, etc.)
-            
-        Returns:
-            True if sent successfully, False otherwise
-        """
-        pass
-    
-    @abstractmethod
-    def send_event(
-        self, 
-        event_name: str, 
-        payload: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Send a generic telemetry event.
-        
-        Args:
-            event_name: Name of the event
-            payload: Optional event data
-            
-        Returns:
-            True if sent successfully, False otherwise
-        """
-        pass
-    
-    @abstractmethod
-    def flush(self) -> None:
-        """Flush any pending telemetry data."""
-        pass
-    
-    @abstractmethod
-    def shutdown(self) -> None:
-        """Clean shutdown of the provider."""
-        pass
-    
-    def sanitize_data(self, data: Dict[str, Any]) -> Dict[str, Any]:
-        """
-        Remove sensitive information from telemetry data.
-        Override in subclasses for custom sanitization.
-        
-        Args:
-            data: Raw data dictionary
-            
-        Returns:
-            Sanitized data dictionary
-        """
-        # Default implementation - remove common sensitive fields
-        sensitive_keys = {
-            'password', 'token', 'api_key', 'secret', 'credential',
-            'auth', 'authorization', 'cookie', 'session'
-        }
-        
-        def _sanitize_dict(d: Dict) -> Dict:
-            sanitized = {}
-            for key, value in d.items():
-                key_lower = key.lower()
-                if any(sensitive in key_lower for sensitive in sensitive_keys):
-                    sanitized[key] = '[REDACTED]'
-                elif isinstance(value, dict):
-                    sanitized[key] = _sanitize_dict(value)
-                elif isinstance(value, list):
-                    sanitized[key] = [
-                        _sanitize_dict(item) if isinstance(item, dict) else item 
-                        for item in value
-                    ]
-                else:
-                    sanitized[key] = value
-            return sanitized
-        
-        return _sanitize_dict(data) if isinstance(data, dict) else data
-
-
-class NullProvider(TelemetryProvider):
-    """No-op provider for when telemetry is disabled."""
-    
-    def initialize(self) -> bool:
-        """No initialization needed for null provider."""
-        self._initialized = True
-        return True
-    
-    def send_exception(
-        self, 
-        exc: Exception, 
-        context: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """No-op exception sending."""
-        return True
-    
-    def send_event(
-        self, 
-        event_name: str, 
-        payload: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """No-op event sending."""
-        return True
-    
-    def flush(self) -> None:
-        """No-op flush."""
-        pass
-    
-    def shutdown(self) -> None:
-        """No-op shutdown."""
-        pass

crawl4ai/telemetry/config.py

@@ -1,196 +0,0 @@
-"""
-Configuration management for Crawl4AI telemetry.
-Handles user preferences and persistence.
-"""
-
-import json
-import os
-from pathlib import Path
-from typing import Dict, Any, Optional
-from enum import Enum
-
-
-class TelemetryConsent(Enum):
-    """Telemetry consent levels."""
-    NOT_SET = "not_set"
-    DENIED = "denied"
-    ONCE = "once"  # Send current error only
-    ALWAYS = "always"  # Send all errors
-
-
-class TelemetryConfig:
-    """Manages telemetry configuration and persistence."""
-    
-    def __init__(self, config_dir: Optional[Path] = None):
-        """
-        Initialize configuration manager.
-        
-        Args:
-            config_dir: Optional custom config directory
-        """
-        if config_dir:
-            self.config_dir = config_dir
-        else:
-            # Default to ~/.crawl4ai/
-            self.config_dir = Path.home() / '.crawl4ai'
-        
-        self.config_file = self.config_dir / 'config.json'
-        self._config: Dict[str, Any] = {}
-        self._load_config()
-    
-    def _ensure_config_dir(self) -> None:
-        """Ensure configuration directory exists."""
-        self.config_dir.mkdir(parents=True, exist_ok=True)
-    
-    def _load_config(self) -> None:
-        """Load configuration from disk."""
-        if self.config_file.exists():
-            try:
-                with open(self.config_file, 'r') as f:
-                    self._config = json.load(f)
-            except (json.JSONDecodeError, IOError):
-                # Corrupted or inaccessible config - start fresh
-                self._config = {}
-        else:
-            self._config = {}
-    
-    def _save_config(self) -> bool:
-        """
-        Save configuration to disk.
-        
-        Returns:
-            True if saved successfully
-        """
-        try:
-            self._ensure_config_dir()
-            
-            # Write to temporary file first
-            temp_file = self.config_file.with_suffix('.tmp')
-            with open(temp_file, 'w') as f:
-                json.dump(self._config, f, indent=2)
-            
-            # Atomic rename
-            temp_file.replace(self.config_file)
-            return True
-            
-        except (IOError, OSError):
-            return False
-    
-    def get_telemetry_settings(self) -> Dict[str, Any]:
-        """
-        Get current telemetry settings.
-        
-        Returns:
-            Dictionary with telemetry settings
-        """
-        return self._config.get('telemetry', {
-            'consent': TelemetryConsent.NOT_SET.value,
-            'email': None
-        })
-    
-    def get_consent(self) -> TelemetryConsent:
-        """
-        Get current consent status.
-        
-        Returns:
-            TelemetryConsent enum value
-        """
-        settings = self.get_telemetry_settings()
-        consent_value = settings.get('consent', TelemetryConsent.NOT_SET.value)
-        
-        # Handle legacy boolean values
-        if isinstance(consent_value, bool):
-            consent_value = TelemetryConsent.ALWAYS.value if consent_value else TelemetryConsent.DENIED.value
-        
-        try:
-            return TelemetryConsent(consent_value)
-        except ValueError:
-            return TelemetryConsent.NOT_SET
-    
-    def set_consent(
-        self, 
-        consent: TelemetryConsent, 
-        email: Optional[str] = None
-    ) -> bool:
-        """
-        Set telemetry consent and optional email.
-        
-        Args:
-            consent: Consent level
-            email: Optional email for follow-up
-            
-        Returns:
-            True if saved successfully
-        """
-        if 'telemetry' not in self._config:
-            self._config['telemetry'] = {}
-        
-        self._config['telemetry']['consent'] = consent.value
-        
-        # Only update email if provided
-        if email is not None:
-            self._config['telemetry']['email'] = email
-        
-        return self._save_config()
-    
-    def get_email(self) -> Optional[str]:
-        """
-        Get stored email if any.
-        
-        Returns:
-            Email address or None
-        """
-        settings = self.get_telemetry_settings()
-        return settings.get('email')
-    
-    def is_enabled(self) -> bool:
-        """
-        Check if telemetry is enabled.
-        
-        Returns:
-            True if telemetry should send data
-        """
-        consent = self.get_consent()
-        return consent in [TelemetryConsent.ONCE, TelemetryConsent.ALWAYS]
-    
-    def should_send_current(self) -> bool:
-        """
-        Check if current error should be sent.
-        Used for one-time consent.
-        
-        Returns:
-            True if current error should be sent
-        """
-        consent = self.get_consent()
-        if consent == TelemetryConsent.ONCE:
-            # After sending once, reset to NOT_SET
-            self.set_consent(TelemetryConsent.NOT_SET)
-            return True
-        return consent == TelemetryConsent.ALWAYS
-    
-    def clear(self) -> bool:
-        """
-        Clear all telemetry settings.
-        
-        Returns:
-            True if cleared successfully
-        """
-        if 'telemetry' in self._config:
-            del self._config['telemetry']
-            return self._save_config()
-        return True
-    
-    def update_from_env(self) -> None:
-        """Update configuration from environment variables."""
-        # Check for telemetry disable flag
-        if os.environ.get('CRAWL4AI_TELEMETRY') == '0':
-            self.set_consent(TelemetryConsent.DENIED)
-        
-        # Check for email override
-        env_email = os.environ.get('CRAWL4AI_TELEMETRY_EMAIL')
-        if env_email and self.is_enabled():
-            current_settings = self.get_telemetry_settings()
-            self.set_consent(
-                TelemetryConsent(current_settings['consent']),
-                email=env_email
-            )

crawl4ai/telemetry/consent.py

@@ -1,314 +0,0 @@
-"""
-User consent handling for Crawl4AI telemetry.
-Provides interactive prompts for different environments.
-"""
-
-import sys
-from typing import Optional, Tuple
-from .config import TelemetryConsent, TelemetryConfig
-from .environment import Environment, EnvironmentDetector
-
-
-class ConsentManager:
-    """Manages user consent for telemetry."""
-    
-    def __init__(self, config: Optional[TelemetryConfig] = None):
-        """
-        Initialize consent manager.
-        
-        Args:
-            config: Optional TelemetryConfig instance
-        """
-        self.config = config or TelemetryConfig()
-        self.environment = EnvironmentDetector.detect()
-    
-    def check_and_prompt(self) -> TelemetryConsent:
-        """
-        Check consent status and prompt if needed.
-        
-        Returns:
-            Current consent status
-        """
-        current_consent = self.config.get_consent()
-        
-        # If already set, return current value
-        if current_consent != TelemetryConsent.NOT_SET:
-            return current_consent
-        
-        # Docker/API server: default enabled (check env var)
-        if self.environment in [Environment.DOCKER, Environment.API_SERVER]:
-            return self._handle_docker_consent()
-        
-        # Interactive environments: prompt user
-        if EnvironmentDetector.is_interactive():
-            return self._prompt_for_consent()
-        
-        # Non-interactive: default disabled
-        return TelemetryConsent.DENIED
-    
-    def _handle_docker_consent(self) -> TelemetryConsent:
-        """
-        Handle consent in Docker environment.
-        Default enabled unless disabled via env var.
-        """
-        import os
-        
-        if os.environ.get('CRAWL4AI_TELEMETRY') == '0':
-            self.config.set_consent(TelemetryConsent.DENIED)
-            return TelemetryConsent.DENIED
-        
-        # Default enabled for Docker
-        self.config.set_consent(TelemetryConsent.ALWAYS)
-        return TelemetryConsent.ALWAYS
-    
-    def _prompt_for_consent(self) -> TelemetryConsent:
-        """
-        Prompt user for consent based on environment.
-        
-        Returns:
-            User's consent choice
-        """
-        if self.environment == Environment.CLI:
-            return self._cli_prompt()
-        elif self.environment in [Environment.JUPYTER, Environment.COLAB]:
-            return self._notebook_prompt()
-        else:
-            return TelemetryConsent.DENIED
-    
-    def _cli_prompt(self) -> TelemetryConsent:
-        """
-        Show CLI prompt for consent.
-        
-        Returns:
-            User's consent choice
-        """
-        print("\n" + "="*60)
-        print("🚨 Crawl4AI Error Detection")
-        print("="*60)
-        print("\nWe noticed an error occurred. Help improve Crawl4AI by")
-        print("sending anonymous crash reports?")
-        print("\n[1] Yes, send this error only")
-        print("[2] Yes, always send errors")
-        print("[3] No, don't send")
-        print("\n" + "-"*60)
-        
-        # Get choice
-        while True:
-            try:
-                choice = input("Your choice (1/2/3): ").strip()
-                if choice == '1':
-                    consent = TelemetryConsent.ONCE
-                    break
-                elif choice == '2':
-                    consent = TelemetryConsent.ALWAYS
-                    break
-                elif choice == '3':
-                    consent = TelemetryConsent.DENIED
-                    break
-                else:
-                    print("Please enter 1, 2, or 3")
-            except (KeyboardInterrupt, EOFError):
-                # User cancelled - treat as denial
-                consent = TelemetryConsent.DENIED
-                break
-        
-        # Optional email
-        email = None
-        if consent != TelemetryConsent.DENIED:
-            print("\nOptional: Enter email for follow-up (or press Enter to skip):")
-            try:
-                email_input = input("Email: ").strip()
-                if email_input and '@' in email_input:
-                    email = email_input
-            except (KeyboardInterrupt, EOFError):
-                pass
-        
-        # Save choice
-        self.config.set_consent(consent, email)
-        
-        if consent != TelemetryConsent.DENIED:
-            print("\n✅ Thank you for helping improve Crawl4AI!")
-        else:
-            print("\n✅ Telemetry disabled. You can enable it anytime with:")
-            print("   crawl4ai telemetry enable")
-        
-        print("="*60 + "\n")
-        
-        return consent
-    
-    def _notebook_prompt(self) -> TelemetryConsent:
-        """
-        Show notebook prompt for consent.
-        Uses widgets if available, falls back to print + code.
-        
-        Returns:
-            User's consent choice
-        """
-        if EnvironmentDetector.supports_widgets():
-            return self._widget_prompt()
-        else:
-            return self._notebook_fallback_prompt()
-    
-    def _widget_prompt(self) -> TelemetryConsent:
-        """
-        Show interactive widget prompt in Jupyter/Colab.
-        
-        Returns:
-            User's consent choice
-        """
-        try:
-            import ipywidgets as widgets
-            from IPython.display import display, HTML
-            
-            # Create styled HTML
-            html = HTML("""
-            <div style="padding: 15px; border: 2px solid #ff6b6b; border-radius: 8px; background: #fff5f5;">
-                <h3 style="color: #c92a2a; margin-top: 0;">🚨 Crawl4AI Error Detected</h3>
-                <p style="color: #495057;">Help us improve by sending anonymous crash reports?</p>
-            </div>
-            """)
-            display(html)
-            
-            # Create buttons
-            btn_once = widgets.Button(
-                description='Send this error',
-                button_style='info',
-                icon='check'
-            )
-            btn_always = widgets.Button(
-                description='Always send',
-                button_style='success',
-                icon='check-circle'
-            )
-            btn_never = widgets.Button(
-                description='Don\'t send',
-                button_style='danger',
-                icon='times'
-            )
-            
-            # Email input
-            email_input = widgets.Text(
-                placeholder='Optional: your@email.com',
-                description='Email:',
-                style={'description_width': 'initial'}
-            )
-            
-            # Output area for feedback
-            output = widgets.Output()
-            
-            # Container
-            button_box = widgets.HBox([btn_once, btn_always, btn_never])
-            container = widgets.VBox([button_box, email_input, output])
-            
-            # Variable to store choice
-            consent_choice = {'value': None}
-            
-            def on_button_click(btn):
-                """Handle button click."""
-                with output:
-                    output.clear_output()
-                    
-                    if btn == btn_once:
-                        consent_choice['value'] = TelemetryConsent.ONCE
-                        print("✅ Sending this error only")
-                    elif btn == btn_always:
-                        consent_choice['value'] = TelemetryConsent.ALWAYS
-                        print("✅ Always sending errors")
-                    else:
-                        consent_choice['value'] = TelemetryConsent.DENIED
-                        print("✅ Telemetry disabled")
-                    
-                    # Save with email if provided
-                    email = email_input.value.strip() if email_input.value else None
-                    self.config.set_consent(consent_choice['value'], email)
-                    
-                    # Disable buttons after choice
-                    btn_once.disabled = True
-                    btn_always.disabled = True
-                    btn_never.disabled = True
-                    email_input.disabled = True
-            
-            # Attach handlers
-            btn_once.on_click(on_button_click)
-            btn_always.on_click(on_button_click)
-            btn_never.on_click(on_button_click)
-            
-            # Display widget
-            display(container)
-            
-            # Wait for user choice (in notebook, this is non-blocking)
-            # Return NOT_SET for now, actual choice will be saved via callback
-            return consent_choice.get('value', TelemetryConsent.NOT_SET)
-            
-        except Exception:
-            # Fallback if widgets fail
-            return self._notebook_fallback_prompt()
-    
-    def _notebook_fallback_prompt(self) -> TelemetryConsent:
-        """
-        Fallback prompt for notebooks without widget support.
-        
-        Returns:
-            User's consent choice (defaults to DENIED)
-        """
-        try:
-            from IPython.display import display, Markdown
-            
-            markdown_content = """
-### 🚨 Crawl4AI Error Detected
-
-Help us improve by sending anonymous crash reports.
-
-**Telemetry is currently OFF.** To enable, run:
-
-```python
-import crawl4ai
-crawl4ai.telemetry.enable(email="your@email.com", always=True)
-```
-
-To send just this error:
-```python
-crawl4ai.telemetry.enable(once=True)
-```
-
-To keep telemetry disabled:
-```python
-crawl4ai.telemetry.disable()
-```
-            """
-            
-            display(Markdown(markdown_content))
-            
-        except ImportError:
-            # Pure print fallback
-            print("\n" + "="*60)
-            print("🚨 Crawl4AI Error Detected")
-            print("="*60)
-            print("\nTelemetry is OFF. To enable, run:")
-            print("\nimport crawl4ai")
-            print('crawl4ai.telemetry.enable(email="you@example.com", always=True)')
-            print("\n" + "="*60)
-        
-        # Default to disabled in fallback mode
-        return TelemetryConsent.DENIED
-    
-    def force_prompt(self) -> Tuple[TelemetryConsent, Optional[str]]:
-        """
-        Force a consent prompt regardless of current settings.
-        Used for manual telemetry configuration.
-        
-        Returns:
-            Tuple of (consent choice, optional email)
-        """
-        # Temporarily reset consent to force prompt
-        original_consent = self.config.get_consent()
-        self.config.set_consent(TelemetryConsent.NOT_SET)
-        
-        try:
-            new_consent = self._prompt_for_consent()
-            email = self.config.get_email()
-            return new_consent, email
-        except Exception:
-            # Restore original on error
-            self.config.set_consent(original_consent)
-            raise

crawl4ai/telemetry/environment.py

@@ -1,199 +0,0 @@
-"""
-Environment detection for Crawl4AI telemetry.
-Detects whether we're running in CLI, Docker, Jupyter, etc.
-"""
-
-import os
-import sys
-from enum import Enum
-from typing import Optional
-
-
-class Environment(Enum):
-    """Detected runtime environment."""
-    CLI = "cli"
-    DOCKER = "docker"
-    JUPYTER = "jupyter"
-    COLAB = "colab"
-    API_SERVER = "api_server"
-    UNKNOWN = "unknown"
-
-
-class EnvironmentDetector:
-    """Detects the current runtime environment."""
-    
-    @staticmethod
-    def detect() -> Environment:
-        """
-        Detect current runtime environment.
-        
-        Returns:
-            Environment enum value
-        """
-        # Check for Docker
-        if EnvironmentDetector._is_docker():
-            # Further check if it's API server
-            if EnvironmentDetector._is_api_server():
-                return Environment.API_SERVER
-            return Environment.DOCKER
-        
-        # Check for Google Colab
-        if EnvironmentDetector._is_colab():
-            return Environment.COLAB
-        
-        # Check for Jupyter
-        if EnvironmentDetector._is_jupyter():
-            return Environment.JUPYTER
-        
-        # Check for CLI
-        if EnvironmentDetector._is_cli():
-            return Environment.CLI
-        
-        return Environment.UNKNOWN
-    
-    @staticmethod
-    def _is_docker() -> bool:
-        """Check if running inside Docker container."""
-        # Check for Docker-specific files
-        if os.path.exists('/.dockerenv'):
-            return True
-        
-        # Check cgroup for docker signature
-        try:
-            with open('/proc/1/cgroup', 'r') as f:
-                return 'docker' in f.read()
-        except (IOError, OSError):
-            pass
-        
-        # Check environment variable (if set in Dockerfile)
-        return os.environ.get('CRAWL4AI_DOCKER', '').lower() == 'true'
-    
-    @staticmethod
-    def _is_api_server() -> bool:
-        """Check if running as API server."""
-        # Check for API server indicators
-        return (
-            os.environ.get('CRAWL4AI_API_SERVER', '').lower() == 'true' or
-            'deploy/docker/server.py' in ' '.join(sys.argv) or
-            'deploy/docker/api.py' in ' '.join(sys.argv)
-        )
-    
-    @staticmethod
-    def _is_jupyter() -> bool:
-        """Check if running in Jupyter notebook."""
-        try:
-            # Check for IPython
-            from IPython import get_ipython
-            ipython = get_ipython()
-            
-            if ipython is None:
-                return False
-            
-            # Check for notebook kernel
-            if 'IPKernelApp' in ipython.config:
-                return True
-            
-            # Check for Jupyter-specific attributes
-            if hasattr(ipython, 'kernel'):
-                return True
-                
-        except (ImportError, AttributeError):
-            pass
-        
-        return False
-    
-    @staticmethod
-    def _is_colab() -> bool:
-        """Check if running in Google Colab."""
-        try:
-            import google.colab
-            return True
-        except ImportError:
-            pass
-        
-        # Alternative check
-        return 'COLAB_GPU' in os.environ or 'COLAB_TPU_ADDR' in os.environ
-    
-    @staticmethod
-    def _is_cli() -> bool:
-        """Check if running from command line."""
-        # Check if we have a terminal
-        return (
-            hasattr(sys, 'ps1') or 
-            sys.stdin.isatty() or
-            bool(os.environ.get('TERM'))
-        )
-    
-    @staticmethod
-    def is_interactive() -> bool:
-        """
-        Check if environment supports interactive prompts.
-        
-        Returns:
-            True if interactive prompts are supported
-        """
-        env = EnvironmentDetector.detect()
-        
-        # Docker/API server are non-interactive
-        if env in [Environment.DOCKER, Environment.API_SERVER]:
-            return False
-        
-        # CLI with TTY is interactive
-        if env == Environment.CLI:
-            return sys.stdin.isatty()
-        
-        # Jupyter/Colab can be interactive with widgets
-        if env in [Environment.JUPYTER, Environment.COLAB]:
-            return True
-        
-        return False
-    
-    @staticmethod
-    def supports_widgets() -> bool:
-        """
-        Check if environment supports IPython widgets.
-        
-        Returns:
-            True if widgets are supported
-        """
-        env = EnvironmentDetector.detect()
-        
-        if env not in [Environment.JUPYTER, Environment.COLAB]:
-            return False
-        
-        try:
-            import ipywidgets
-            from IPython.display import display
-            return True
-        except ImportError:
-            return False
-    
-    @staticmethod
-    def get_environment_context() -> dict:
-        """
-        Get environment context for telemetry.
-        
-        Returns:
-            Dictionary with environment information
-        """
-        env = EnvironmentDetector.detect()
-        
-        context = {
-            'environment_type': env.value,
-            'python_version': f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}",
-            'platform': sys.platform,
-        }
-        
-        # Add environment-specific context
-        if env == Environment.DOCKER:
-            context['docker'] = True
-            context['container_id'] = os.environ.get('HOSTNAME', 'unknown')
-        
-        elif env == Environment.COLAB:
-            context['colab'] = True
-            context['gpu'] = bool(os.environ.get('COLAB_GPU'))
-        
-        elif env == Environment.JUPYTER:
-            context['jupyter'] = True
-        
-        return context

crawl4ai/telemetry/providers/__init__.py

@@ -1,15 +0,0 @@
-"""
-Telemetry providers for Crawl4AI.
-"""
-
-from ..base import TelemetryProvider, NullProvider
-
-__all__ = ['TelemetryProvider', 'NullProvider']
-
-# Try to import Sentry provider if available
-try:
-    from .sentry import SentryProvider
-    __all__.append('SentryProvider')
-except ImportError:
-    # Sentry SDK not installed
-    pass

crawl4ai/telemetry/providers/sentry.py

@@ -1,234 +0,0 @@
-"""
-Sentry telemetry provider for Crawl4AI.
-"""
-
-import os
-from typing import Dict, Any, Optional
-from ..base import TelemetryProvider
-
-# Hardcoded DSN for Crawl4AI project
-# This is safe to embed as it's the public part of the DSN
-# TODO: Replace with actual Crawl4AI Sentry project DSN before release
-# Format: "https://<public_key>@<organization>.ingest.sentry.io/<project_id>"
-DEFAULT_SENTRY_DSN = "https://your-public-key@sentry.io/your-project-id"
-
-
-class SentryProvider(TelemetryProvider):
-    """Sentry implementation of telemetry provider."""
-    
-    def __init__(self, dsn: Optional[str] = None, **kwargs):
-        """
-        Initialize Sentry provider.
-        
-        Args:
-            dsn: Optional DSN override (for testing/development)
-            **kwargs: Additional Sentry configuration
-        """
-        super().__init__(**kwargs)
-        
-        # Allow DSN override via environment variable or parameter
-        self.dsn = (
-            dsn or 
-            os.environ.get('CRAWL4AI_SENTRY_DSN') or 
-            DEFAULT_SENTRY_DSN
-        )
-        
-        self._sentry_sdk = None
-        self.environment = kwargs.get('environment', 'production')
-        self.release = kwargs.get('release', None)
-    
-    def initialize(self) -> bool:
-        """Initialize Sentry SDK."""
-        try:
-            import sentry_sdk
-            from sentry_sdk.integrations.stdlib import StdlibIntegration
-            from sentry_sdk.integrations.excepthook import ExcepthookIntegration
-            
-            # Initialize Sentry with minimal integrations
-            sentry_sdk.init(
-                dsn=self.dsn,
-                
-                environment=self.environment,
-                release=self.release,
-                
-                # Performance monitoring disabled by default
-                traces_sample_rate=0.0,
-                
-                # Only capture errors, not transactions
-                # profiles_sample_rate=0.0,
-                
-                # Minimal integrations
-                integrations=[
-                    StdlibIntegration(),
-                    ExcepthookIntegration(always_run=False),
-                ],
-                
-                # Privacy settings
-                send_default_pii=False,
-                attach_stacktrace=True,
-                
-                # Before send hook for additional sanitization
-                before_send=self._before_send,
-                
-                # Disable automatic breadcrumbs
-                max_breadcrumbs=0,
-                
-                # Disable request data collection
-                # request_bodies='never',
-                
-                # # Custom transport options
-                # transport_options={
-                #     'keepalive': True,
-                # },
-            )
-
-            self._sentry_sdk = sentry_sdk
-            self._initialized = True
-            return True
-            
-        except ImportError:
-            # Sentry SDK not installed
-            return False
-        except Exception:
-            # Initialization failed silently
-            return False
-    
-    def _before_send(self, event: Dict[str, Any], hint: Dict[str, Any]) -> Optional[Dict[str, Any]]:
-        """
-        Process event before sending to Sentry.
-        Provides additional privacy protection.
-        """
-        # Remove sensitive data
-        if 'request' in event:
-            event['request'] = self._sanitize_request(event['request'])
-        
-        # Remove local variables that might contain sensitive data
-        if 'exception' in event and 'values' in event['exception']:
-            for exc in event['exception']['values']:
-                if 'stacktrace' in exc and 'frames' in exc['stacktrace']:
-                    for frame in exc['stacktrace']['frames']:
-                        # Remove local variables from frames
-                        frame.pop('vars', None)
-        
-        # Apply general sanitization
-        event = self.sanitize_data(event)
-        
-        return event
-    
-    def _sanitize_request(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
-        """Sanitize request data to remove sensitive information."""
-        sanitized = request_data.copy()
-        
-        # Remove sensitive fields
-        sensitive_fields = ['cookies', 'headers', 'data', 'query_string', 'env']
-        for field in sensitive_fields:
-            if field in sanitized:
-                sanitized[field] = '[REDACTED]'
-        
-        # Keep only safe fields
-        safe_fields = ['method', 'url']
-        return {k: v for k, v in sanitized.items() if k in safe_fields}
-    
-    def send_exception(
-        self, 
-        exc: Exception, 
-        context: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Send exception to Sentry.
-        
-        Args:
-            exc: Exception to report
-            context: Optional context (email, environment info)
-            
-        Returns:
-            True if sent successfully
-        """
-        if not self._initialized:
-            if not self.initialize():
-                return False
-        
-        try:
-            if self._sentry_sdk:
-                with self._sentry_sdk.push_scope() as scope:
-                    # Add user context if email provided
-                    if context and 'email' in context:
-                        scope.set_user({'email': context['email']})
-                    
-                    # Add additional context
-                    if context:
-                        for key, value in context.items():
-                            if key != 'email':
-                                scope.set_context(key, value)
-                    
-                    # Add tags for filtering
-                    scope.set_tag('source', context.get('source', 'unknown'))
-                    scope.set_tag('environment_type', context.get('environment_type', 'unknown'))
-                    
-                    # Capture the exception
-                    self._sentry_sdk.capture_exception(exc)
-                    
-                return True
-                
-        except Exception:
-            # Silently fail - telemetry should never crash the app
-            return False
-        
-        return False
-    
-    def send_event(
-        self, 
-        event_name: str, 
-        payload: Optional[Dict[str, Any]] = None
-    ) -> bool:
-        """
-        Send custom event to Sentry.
-        
-        Args:
-            event_name: Name of the event
-            payload: Event data
-            
-        Returns:
-            True if sent successfully
-        """
-        if not self._initialized:
-            if not self.initialize():
-                return False
-        
-        try:
-            if self._sentry_sdk:
-                # Sanitize payload
-                safe_payload = self.sanitize_data(payload) if payload else {}
-                
-                # Send as a message with extra data
-                self._sentry_sdk.capture_message(
-                    event_name,
-                    level='info',
-                    extras=safe_payload
-                )
-                return True
-                
-        except Exception:
-            return False
-        
-        return False
-    
-    def flush(self) -> None:
-        """Flush pending events to Sentry."""
-        if self._initialized and self._sentry_sdk:
-            try:
-                self._sentry_sdk.flush(timeout=2.0)
-            except Exception:
-                pass
-    
-    def shutdown(self) -> None:
-        """Shutdown Sentry client."""
-        if self._initialized and self._sentry_sdk:
-            try:
-                self._sentry_sdk.flush(timeout=2.0)
-                # Note: sentry_sdk doesn't have a shutdown method
-                # Flush is sufficient for cleanup
-            except Exception:
-                pass
-            finally:
-                self._initialized = False

crawl4ai/utils.py

@@ -1790,6 +1790,10 @@ def perform_completion_with_backoff(
         except RateLimitError as e:
             print("Rate limit error:", str(e))
 
+            if attempt == max_attempts - 1:
+                # Last attempt failed, raise the error.
+                raise
+
             # Check if we have exhausted our max attempts
             if attempt < max_attempts - 1:
                 # Calculate the delay and wait
@@ -2146,7 +2150,9 @@ def normalize_url(
     drop_query_tracking=True,
     sort_query=True,
     keep_fragment=False,
-    extra_drop_params=None
+    extra_drop_params=None,
+    preserve_https=False,
+    original_scheme=None
 ):
     """
     Extended URL normalizer
@@ -2176,6 +2182,17 @@ def normalize_url(
 
     # Resolve relative paths first
     full_url = urljoin(base_url, href.strip())
+    
+    # Preserve HTTPS if requested and original scheme was HTTPS
+    if preserve_https and original_scheme == 'https':
+        parsed_full = urlparse(full_url)
+        parsed_base = urlparse(base_url)
+        # Only preserve HTTPS for same-domain links (not protocol-relative URLs)
+        # Protocol-relative URLs (//example.com) should follow the base URL's scheme
+        if (parsed_full.scheme == 'http' and 
+            parsed_full.netloc == parsed_base.netloc and
+            not href.strip().startswith('//')):
+            full_url = full_url.replace('http://', 'https://', 1)
 
     # Parse once, edit parts, then rebuild
     parsed = urlparse(full_url)
@@ -2184,8 +2201,10 @@ def normalize_url(
     netloc = parsed.netloc.lower()
 
     # ── path ──
-    # Strip duplicate slashes and trailing “/” (except root)
-    path = quote(unquote(parsed.path))
+    # Strip duplicate slashes and trailing "/" (except root)
+    # IMPORTANT: Don't use quote(unquote()) as it mangles + signs in URLs
+    # The path from urlparse is already properly encoded
+    path = parsed.path
     if path.endswith('/') and path != '/':
         path = path.rstrip('/')
 
@@ -2225,7 +2244,7 @@ def normalize_url(
     return normalized
 
 
-def normalize_url_for_deep_crawl(href, base_url):
+def normalize_url_for_deep_crawl(href, base_url, preserve_https=False, original_scheme=None):
     """Normalize URLs to ensure consistent format"""
     from urllib.parse import urljoin, urlparse, urlunparse, parse_qs, urlencode
 
@@ -2236,6 +2255,17 @@ def normalize_url_for_deep_crawl(href, base_url):
     # Use urljoin to handle relative URLs
     full_url = urljoin(base_url, href.strip())
     
+    # Preserve HTTPS if requested and original scheme was HTTPS
+    if preserve_https and original_scheme == 'https':
+        parsed_full = urlparse(full_url)
+        parsed_base = urlparse(base_url)
+        # Only preserve HTTPS for same-domain links (not protocol-relative URLs)
+        # Protocol-relative URLs (//example.com) should follow the base URL's scheme
+        if (parsed_full.scheme == 'http' and 
+            parsed_full.netloc == parsed_base.netloc and
+            not href.strip().startswith('//')):
+            full_url = full_url.replace('http://', 'https://', 1)
+    
     # Parse the URL for normalization
     parsed = urlparse(full_url)
     
@@ -2273,7 +2303,7 @@ def normalize_url_for_deep_crawl(href, base_url):
     return normalized
 
 @lru_cache(maxsize=10000)
-def efficient_normalize_url_for_deep_crawl(href, base_url):
+def efficient_normalize_url_for_deep_crawl(href, base_url, preserve_https=False, original_scheme=None):
     """Efficient URL normalization with proper parsing"""
     from urllib.parse import urljoin
     
@@ -2283,6 +2313,17 @@ def efficient_normalize_url_for_deep_crawl(href, base_url):
     # Resolve relative URLs
     full_url = urljoin(base_url, href.strip())
     
+    # Preserve HTTPS if requested and original scheme was HTTPS
+    if preserve_https and original_scheme == 'https':
+        parsed_full = urlparse(full_url)
+        parsed_base = urlparse(base_url)
+        # Only preserve HTTPS for same-domain links (not protocol-relative URLs)
+        # Protocol-relative URLs (//example.com) should follow the base URL's scheme
+        if (parsed_full.scheme == 'http' and 
+            parsed_full.netloc == parsed_base.netloc and
+            not href.strip().startswith('//')):
+            full_url = full_url.replace('http://', 'https://', 1)
+    
     # Use proper URL parsing
     parsed = urlparse(full_url)
     

deploy/docker/.llm.env.example

@@ -10,4 +10,23 @@ GEMINI_API_TOKEN=your_gemini_key_here
 # Optional: Override the default LLM provider
 # Examples: "openai/gpt-4", "anthropic/claude-3-opus", "deepseek/chat", etc.
 # If not set, uses the provider specified in config.yml (default: openai/gpt-4o-mini)
-# LLM_PROVIDER=anthropic/claude-3-opus
+# LLM_PROVIDER=anthropic/claude-3-opus
+
+# Optional: Global LLM temperature setting (0.0-2.0)
+# Controls randomness in responses. Lower = more focused, Higher = more creative
+# LLM_TEMPERATURE=0.7
+
+# Optional: Global custom API base URL
+# Use this to point to custom endpoints or proxy servers
+# LLM_BASE_URL=https://api.custom.com/v1
+
+# Optional: Provider-specific temperature overrides
+# These take precedence over the global LLM_TEMPERATURE
+# OPENAI_TEMPERATURE=0.5
+# ANTHROPIC_TEMPERATURE=0.3
+# GROQ_TEMPERATURE=0.8
+
+# Optional: Provider-specific base URL overrides
+# Use for provider-specific proxy endpoints
+# OPENAI_BASE_URL=https://custom-openai.company.com/v1
+# GROQ_BASE_URL=https://custom-groq.company.com/v1

deploy/docker/README.md

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

deploy/docker/api.py

@@ -4,7 +4,7 @@ import asyncio
 from typing import List, Tuple, Dict
 from functools import partial
 from uuid import uuid4
-from datetime import datetime
+from datetime import datetime, timezone
 from base64 import b64encode
 
 import logging
@@ -42,7 +42,9 @@ from utils import (
     should_cleanup_task,
     decode_redis_hash,
     get_llm_api_key,
-    validate_llm_provider
+    validate_llm_provider,
+    get_llm_temperature,
+    get_llm_base_url
 )
 
 import psutil, time
@@ -96,7 +98,9 @@ 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)
+            api_token=get_llm_api_key(config),  # Returns None to let litellm handle it
+            temperature=get_llm_temperature(config),
+            base_url=get_llm_base_url(config)
         )
 
         return response.choices[0].message.content
@@ -115,7 +119,9 @@ async def process_llm_extraction(
     instruction: str,
     schema: Optional[str] = None,
     cache: str = "0",
-    provider: Optional[str] = None
+    provider: Optional[str] = None,
+    temperature: Optional[float] = None,
+    base_url: Optional[str] = None
 ) -> None:
     """Process LLM extraction in background."""
     try:
@@ -127,11 +133,13 @@ async def process_llm_extraction(
                 "error": error_msg
             })
             return
-        api_key = get_llm_api_key(config, provider)
+        api_key = get_llm_api_key(config, provider)  # Returns None to let litellm handle it
         llm_strategy = LLMExtractionStrategy(
             llm_config=LLMConfig(
                 provider=provider or config["llm"]["provider"],
-                api_token=api_key
+                api_token=api_key,
+                temperature=temperature or get_llm_temperature(config, provider),
+                base_url=base_url or get_llm_base_url(config, provider)
             ),
             instruction=instruction,
             schema=json.loads(schema) if schema else None,
@@ -178,7 +186,9 @@ async def handle_markdown_request(
     query: Optional[str] = None,
     cache: str = "0",
     config: Optional[dict] = None,
-    provider: Optional[str] = None
+    provider: Optional[str] = None,
+    temperature: Optional[float] = None,
+    base_url: Optional[str] = None
 ) -> str:
     """Handle markdown generation requests."""
     try:
@@ -203,7 +213,9 @@ 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),
+                        api_token=get_llm_api_key(config, provider),  # Returns None to let litellm handle it
+                        temperature=temperature or get_llm_temperature(config, provider),
+                        base_url=base_url or get_llm_base_url(config, provider)
                     ),
                     instruction=query or "Extract main content"
                 )
@@ -248,7 +260,9 @@ async def handle_llm_request(
     schema: Optional[str] = None,
     cache: str = "0",
     config: Optional[dict] = None,
-    provider: Optional[str] = None
+    provider: Optional[str] = None,
+    temperature: Optional[float] = None,
+    api_base_url: Optional[str] = None
 ) -> JSONResponse:
     """Handle LLM extraction requests."""
     base_url = get_base_url(request)
@@ -279,7 +293,9 @@ async def handle_llm_request(
             cache,
             base_url,
             config,
-            provider
+            provider,
+            temperature,
+            api_base_url
         )
 
     except Exception as e:
@@ -324,7 +340,9 @@ async def create_new_task(
     cache: str,
     base_url: str,
     config: dict,
-    provider: Optional[str] = None
+    provider: Optional[str] = None,
+    temperature: Optional[float] = None,
+    api_base_url: Optional[str] = None
 ) -> JSONResponse:
     """Create and initialize a new task."""
     decoded_url = unquote(input_path)
@@ -349,7 +367,9 @@ async def create_new_task(
         query,
         schema,
         cache,
-        provider
+        provider,
+        temperature,
+        api_base_url
     )
 
     return JSONResponse({
@@ -393,6 +413,9 @@ async def stream_results(crawler: AsyncWebCrawler, results_gen: AsyncGenerator)
                 server_memory_mb = _get_memory_mb()
                 result_dict = result.model_dump()
                 result_dict['server_memory_mb'] = server_memory_mb
+                # Ensure fit_html is JSON-serializable
+                if "fit_html" in result_dict and not (result_dict["fit_html"] is None or isinstance(result_dict["fit_html"], str)):
+                    result_dict["fit_html"] = None
                 # If PDF exists, encode it to base64
                 if result_dict.get('pdf') is not None:
                     result_dict['pdf'] = b64encode(result_dict['pdf']).decode('utf-8')
@@ -473,6 +496,9 @@ async def handle_crawl_request(
         processed_results = []
         for result in results:
             result_dict = result.model_dump()
+            # if fit_html is not a string, set it to None to avoid serialization errors
+            if "fit_html" in result_dict and not (result_dict["fit_html"] is None or isinstance(result_dict["fit_html"], str)):
+                result_dict["fit_html"] = None
             # If PDF exists, encode it to base64
             if result_dict.get('pdf') is not None:
                 result_dict['pdf'] = b64encode(result_dict['pdf']).decode('utf-8')
@@ -576,7 +602,7 @@ async def handle_crawl_job(
     task_id = f"crawl_{uuid4().hex[:8]}"
     await redis.hset(f"task:{task_id}", mapping={
         "status": TaskStatus.PROCESSING,         # <-- keep enum values consistent
-        "created_at": datetime.utcnow().isoformat(),
+        "created_at": datetime.now(timezone.utc).replace(tzinfo=None).isoformat(),
         "url": json.dumps(urls),                 # store list as JSON string
         "result": "",
         "error": "",

deploy/docker/auth.py

@@ -28,25 +28,43 @@ def create_access_token(data: dict, expires_delta: Optional[timedelta] = None) -
     signing_key = get_jwk_from_secret(SECRET_KEY)
     return instance.encode(to_encode, signing_key, alg='HS256')
 
-def verify_token(credentials: HTTPAuthorizationCredentials = Depends(security)) -> Dict:
+def verify_token(credentials: HTTPAuthorizationCredentials) -> Dict:
     """Verify the JWT token from the Authorization header."""
-
-    if credentials is None:
-        return None
+    
+    if not credentials or not credentials.credentials:
+        raise HTTPException(
+            status_code=401, 
+            detail="No token provided",
+            headers={"WWW-Authenticate": "Bearer"}
+        )
+    
     token = credentials.credentials
     verifying_key = get_jwk_from_secret(SECRET_KEY)
     try:
         payload = instance.decode(token, verifying_key, do_time_check=True, algorithms='HS256')
         return payload
-    except Exception:
-        raise HTTPException(status_code=401, detail="Invalid or expired token")
+    except Exception as e:
+        raise HTTPException(
+            status_code=401, 
+            detail=f"Invalid or expired token: {str(e)}",
+            headers={"WWW-Authenticate": "Bearer"}
+        )
 
 
 def get_token_dependency(config: Dict):
     """Return the token dependency if JWT is enabled, else a function that returns None."""
-
+    
     if config.get("security", {}).get("jwt_enabled", False):
-        return verify_token
+        def jwt_required(credentials: HTTPAuthorizationCredentials = Depends(security)) -> Dict:
+            """Enforce JWT authentication when enabled."""
+            if credentials is None:
+                raise HTTPException(
+                    status_code=401, 
+                    detail="Authentication required. Please provide a valid Bearer token.",
+                    headers={"WWW-Authenticate": "Bearer"}
+                )
+            return verify_token(credentials)
+        return jwt_required
     else:
         return lambda: None
 

deploy/docker/c4ai-code-context.md

@@ -7520,17 +7520,18 @@ class BrowserManager:
             )
             os.makedirs(browser_args["downloads_path"], exist_ok=True)
 
-        if self.config.proxy or self.config.proxy_config:
+        if self.config.proxy:
+            warnings.warn(
+                "BrowserConfig.proxy is deprecated and ignored. Use proxy_config instead.",
+                DeprecationWarning,
+            )
+        if self.config.proxy_config:
             from playwright.async_api import ProxySettings
 
-            proxy_settings = (
-                ProxySettings(server=self.config.proxy)
-                if self.config.proxy
-                else ProxySettings(
-                    server=self.config.proxy_config.server,
-                    username=self.config.proxy_config.username,
-                    password=self.config.proxy_config.password,
-                )
+            proxy_settings = ProxySettings(
+                server=self.config.proxy_config.server,
+                username=self.config.proxy_config.username,
+                password=self.config.proxy_config.password,
             )
             browser_args["proxy"] = proxy_settings
 

deploy/docker/c4ai-doc-context.md

@@ -2241,7 +2241,7 @@ docker build -t crawl4ai
 
 | Argument | Description | Default | Options |
 |----------|-------------|---------|----------|
-| PYTHON_VERSION | Python version | 3.10 | 3.8, 3.9, 3.10 |
+| PYTHON_VERSION | Python version | 3.10 | 3.10, 3.11, 3.12, 3.13 |
 | INSTALL_TYPE | Feature set | default | default, all, torch, transformer |
 | ENABLE_GPU | GPU support | false | true, false |
 | APP_HOME | Install path | /app | any valid path |

deploy/docker/config.yml

@@ -11,8 +11,7 @@ app:
 # Default LLM Configuration
 llm:
   provider: "openai/gpt-4o-mini"
-  api_key_env: "OPENAI_API_KEY"
-  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored
+  # api_key: sk-...  # If you pass the API key directly (not recommended)
 
 # Redis Configuration
 redis:
@@ -39,8 +38,8 @@ rate_limiting:
 
 # Security Configuration
 security:
-  enabled: false 
-  jwt_enabled: false 
+  enabled: false
+  jwt_enabled: false
   https_redirect: false
   trusted_hosts: ["*"]
   headers:

deploy/docker/job.py

@@ -37,6 +37,8 @@ class LlmJobPayload(BaseModel):
     schema: Optional[str] = None
     cache:  bool = False
     provider: Optional[str] = None
+    temperature: Optional[float] = None
+    base_url: Optional[str] = None
 
 
 class CrawlJobPayload(BaseModel):
@@ -63,6 +65,8 @@ async def llm_job_enqueue(
         cache=payload.cache,
         config=_config,
         provider=payload.provider,
+        temperature=payload.temperature,
+        api_base_url=payload.base_url,
     )
 
 
@@ -72,7 +76,7 @@ async def llm_job_status(
     task_id: str,
     _td: Dict = Depends(lambda: _token_dep())
 ):
-    return await handle_task_status(_redis, task_id)
+    return await handle_task_status(_redis, task_id, base_url=str(request.base_url))
 
 
 # ---------- CRAWL job -------------------------------------------------------

deploy/docker/requirements.txt

@@ -15,4 +15,3 @@ PyJWT==2.10.1
 mcp>=1.6.0
 websockets>=15.0.1
 httpx[http2]>=0.27.2
-sentry-sdk>=2.0.0

deploy/docker/schemas.py

@@ -16,6 +16,8 @@ class MarkdownRequest(BaseModel):
     q:   Optional[str] = Field(None,  description="Query string used by BM25/LLM filters")
     c:   Optional[str] = Field("0",   description="Cache‑bust / revision counter")
     provider: Optional[str] = Field(None, description="LLM provider override (e.g., 'anthropic/claude-3-opus')")
+    temperature: Optional[float] = Field(None, description="LLM temperature override (0.0-2.0)")
+    base_url: Optional[str] = Field(None, description="LLM API base URL override")
 
 
 class RawCode(BaseModel):

deploy/docker/server.py

@@ -74,32 +74,6 @@ setup_logging(config)
 
 __version__ = "0.5.1-d1"
 
-# ───────────────────── telemetry setup ────────────────────────
-# Docker/API server telemetry: enabled by default unless CRAWL4AI_TELEMETRY=0
-import os as _os
-if _os.environ.get('CRAWL4AI_TELEMETRY') != '0':
-    # Set environment variable to indicate we're in API server mode
-    _os.environ['CRAWL4AI_API_SERVER'] = 'true'
-    
-    # Import and enable telemetry for Docker/API environment
-    from crawl4ai.telemetry import enable as enable_telemetry
-    from crawl4ai.telemetry import capture_exception
-    
-    # Enable telemetry automatically in Docker mode
-    enable_telemetry(always=True)
-    
-    import logging
-    telemetry_logger = logging.getLogger("telemetry")
-    telemetry_logger.info("✅ Telemetry enabled for Docker/API server")
-else:
-    # Define no-op for capture_exception if telemetry is disabled
-    def capture_exception(exc, context=None):
-        pass
-    
-    import logging
-    telemetry_logger = logging.getLogger("telemetry")
-    telemetry_logger.info("❌ Telemetry disabled via CRAWL4AI_TELEMETRY=0")
-
 # ── global page semaphore (hard cap) ─────────────────────────
 MAX_PAGES = config["crawler"]["pool"].get("max_pages", 30)
 GLOBAL_SEM = asyncio.Semaphore(MAX_PAGES)
@@ -267,7 +241,8 @@ async def get_markdown(
         raise HTTPException(
             400, "Invalid URL format. Must start with http://, https://, or for raw HTML (raw:, raw://)")
     markdown = await handle_markdown_request(
-        body.url, body.f, body.q, body.c, config, body.provider
+        body.url, body.f, body.q, body.c, config, body.provider,
+        body.temperature, body.base_url
     )
     return JSONResponse({
         "url": body.url,
@@ -292,12 +267,26 @@ async def generate_html(
     Use when you need sanitized HTML structures for building schemas or further processing.
     """
     cfg = CrawlerRunConfig()
-    async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-        results = await crawler.arun(url=body.url, config=cfg)
-    raw_html = results[0].html
-    from crawl4ai.utils import preprocess_html_for_schema
-    processed_html = preprocess_html_for_schema(raw_html)
-    return JSONResponse({"html": processed_html, "url": body.url, "success": True})
+    try:
+        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
+            results = await crawler.arun(url=body.url, config=cfg)
+        # Check if the crawl was successful
+        if not results[0].success:
+            raise HTTPException(
+                status_code=500,
+                detail=results[0].error_message or "Crawl failed"
+            )
+        
+        raw_html = results[0].html
+        from crawl4ai.utils import preprocess_html_for_schema
+        processed_html = preprocess_html_for_schema(raw_html)
+        return JSONResponse({"html": processed_html, "url": body.url, "success": True})
+    except Exception as e:
+        # Log and raise as HTTP 500 for other exceptions
+        raise HTTPException(
+            status_code=500,
+            detail=str(e)
+        )
 
 # Screenshot endpoint
 
@@ -315,18 +304,29 @@ async def generate_screenshot(
     Use when you need an image snapshot of the rendered page. Its recommened to provide an output path to save the screenshot.
     Then in result instead of the screenshot you will get a path to the saved file.
     """
-    cfg = CrawlerRunConfig(
-        screenshot=True, screenshot_wait_for=body.screenshot_wait_for)
-    async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-        results = await crawler.arun(url=body.url, config=cfg)
-    screenshot_data = results[0].screenshot
-    if body.output_path:
-        abs_path = os.path.abspath(body.output_path)
-        os.makedirs(os.path.dirname(abs_path), exist_ok=True)
-        with open(abs_path, "wb") as f:
-            f.write(base64.b64decode(screenshot_data))
-        return {"success": True, "path": abs_path}
-    return {"success": True, "screenshot": screenshot_data}
+    try:
+        cfg = CrawlerRunConfig(
+            screenshot=True, screenshot_wait_for=body.screenshot_wait_for)
+        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
+            results = await crawler.arun(url=body.url, config=cfg)
+        if not results[0].success:
+            raise HTTPException(
+                status_code=500,
+                detail=results[0].error_message or "Crawl failed"
+            )
+        screenshot_data = results[0].screenshot
+        if body.output_path:
+            abs_path = os.path.abspath(body.output_path)
+            os.makedirs(os.path.dirname(abs_path), exist_ok=True)
+            with open(abs_path, "wb") as f:
+                f.write(base64.b64decode(screenshot_data))
+            return {"success": True, "path": abs_path}
+        return {"success": True, "screenshot": screenshot_data}
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=str(e)
+        )
 
 # PDF endpoint
 
@@ -344,17 +344,28 @@ async def generate_pdf(
     Use when you need a printable or archivable snapshot of the page. It is recommended to provide an output path to save the PDF.
     Then in result instead of the PDF you will get a path to the saved file.
     """
-    cfg = CrawlerRunConfig(pdf=True)
-    async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-        results = await crawler.arun(url=body.url, config=cfg)
-    pdf_data = results[0].pdf
-    if body.output_path:
-        abs_path = os.path.abspath(body.output_path)
-        os.makedirs(os.path.dirname(abs_path), exist_ok=True)
-        with open(abs_path, "wb") as f:
-            f.write(pdf_data)
-        return {"success": True, "path": abs_path}
-    return {"success": True, "pdf": base64.b64encode(pdf_data).decode()}
+    try:
+        cfg = CrawlerRunConfig(pdf=True)
+        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
+            results = await crawler.arun(url=body.url, config=cfg)
+        if not results[0].success:
+            raise HTTPException(
+                status_code=500,
+                detail=results[0].error_message or "Crawl failed"
+            )
+        pdf_data = results[0].pdf
+        if body.output_path:
+            abs_path = os.path.abspath(body.output_path)
+            os.makedirs(os.path.dirname(abs_path), exist_ok=True)
+            with open(abs_path, "wb") as f:
+                f.write(pdf_data)
+            return {"success": True, "path": abs_path}
+        return {"success": True, "pdf": base64.b64encode(pdf_data).decode()}
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=str(e)
+        )
 
 
 @app.post("/execute_js")
@@ -410,12 +421,23 @@ async def execute_js(
         ```
 
     """
-    cfg = CrawlerRunConfig(js_code=body.scripts)
-    async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
-        results = await crawler.arun(url=body.url, config=cfg)
-    # Return JSON-serializable dict of the first CrawlResult
-    data = results[0].model_dump()
-    return JSONResponse(data)
+    try:
+        cfg = CrawlerRunConfig(js_code=body.scripts)
+        async with AsyncWebCrawler(config=BrowserConfig()) as crawler:
+            results = await crawler.arun(url=body.url, config=cfg)
+        if not results[0].success:
+            raise HTTPException(
+                status_code=500,
+                detail=results[0].error_message or "Crawl failed"
+            )
+        # Return JSON-serializable dict of the first CrawlResult
+        data = results[0].model_dump()
+        return JSONResponse(data)
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=str(e)
+        )
 
 
 @app.get("/llm/{url:path}")
@@ -460,16 +482,24 @@ async def crawl(
 ):
     """
     Crawl a list of URLs and return the results as JSON.
+    For streaming responses, use /crawl/stream endpoint.
     """
     if not crawl_request.urls:
         raise HTTPException(400, "At least one URL required")
-    res = await handle_crawl_request(
+    # Check whether it is a redirection for a streaming request
+    crawler_config = CrawlerRunConfig.load(crawl_request.crawler_config)
+    if crawler_config.stream:
+        return await stream_process(crawl_request=crawl_request)
+    results = await handle_crawl_request(
         urls=crawl_request.urls,
         browser_config=crawl_request.browser_config,
         crawler_config=crawl_request.crawler_config,
         config=config,
     )
-    return JSONResponse(res)
+    # check if all of the results are not successful
+    if all(not result["success"] for result in results["results"]):
+        raise HTTPException(500, f"Crawl request failed: {results['results'][0]['error_message']}")
+    return JSONResponse(results)
 
 
 @app.post("/crawl/stream")
@@ -481,12 +511,16 @@ async def crawl_stream(
 ):
     if not crawl_request.urls:
         raise HTTPException(400, "At least one URL required")
+
+    return await stream_process(crawl_request=crawl_request)
+
+async def stream_process(crawl_request: CrawlRequest):
     crawler, gen = await handle_stream_crawl_request(
         urls=crawl_request.urls,
         browser_config=crawl_request.browser_config,
         crawler_config=crawl_request.crawler_config,
         config=config,
-    )
+)
     return StreamingResponse(
         stream_results(crawler, gen),
         media_type="application/x-ndjson",

deploy/docker/static/playground/index.html

@@ -371,7 +371,7 @@
 
                 <div class="flex items-center">
                     <input id="st-stream" type="checkbox" class="mr-2">
-                    <label for="st-stream" class="text-sm">Use /crawl/stream</label>
+                    <label for="st-stream" class="text-sm">Enable streaming mode</label>
                     <button id="st-run"
                         class="ml-auto bg-accent text-dark px-4 py-2 rounded hover:bg-opacity-90 font-medium">
                         Run Stress Test
@@ -596,6 +596,14 @@
             forceHighlightElement(curlCodeEl);
         }
 
+        // Detect if stream is requested inside payload
+        function shouldUseStream(payload) {
+            const toBool = (v) => v === true || (typeof v === 'string' && v.toLowerCase() === 'true');
+            const fromCrawler = payload && payload.crawler_config && payload.crawler_config.params && payload.crawler_config.params.stream;
+            const direct = payload && payload.stream;
+            return toBool(fromCrawler) || toBool(direct);
+        }
+
         // Main run function
         async function runCrawl() {
             const endpoint = document.getElementById('endpoint').value;
@@ -611,16 +619,24 @@
                         : { browser_config: cfgJson };
                 }
             } catch (err) {
-                updateStatus('error');
-                document.querySelector('#response-content code').textContent =
-                    JSON.stringify({ error: err.message }, null, 2);
-                forceHighlightElement(document.querySelector('#response-content code'));
-                return; // stop run
+                const codeText = cm.getValue();
+                const streamFlag = /stream\s*=\s*True/i.test(codeText);
+                const isCrawlEndpoint = document.getElementById('endpoint').value === 'crawl';
+                if (isCrawlEndpoint && streamFlag) {
+                    // Fallback: proceed with minimal config only for stream
+                    advConfig = { crawler_config: { stream: true } };
+                } else {
+                    updateStatus('error');
+                    document.querySelector('#response-content code').textContent =
+                        JSON.stringify({ error: err.message }, null, 2);
+                    forceHighlightElement(document.querySelector('#response-content code'));
+                    return; // stop run
+                }
             }
 
             const endpointMap = {
                 crawl: '/crawl',
-                // crawl_stream: '/crawl/stream',
+                crawl_stream: '/crawl/stream', // Keep for backward compatibility
                 md: '/md',
                 llm: '/llm'
             };
@@ -647,7 +663,7 @@
                 // This will be handled directly in the fetch below
                 payload = null;
             } else {
-                // Default payload for /crawl and /crawl/stream
+                // Default payload for /crawl (supports both streaming and batch modes)
                 payload = {
                     urls,
                     ...advConfig
@@ -659,6 +675,7 @@
             try {
                 const startTime = performance.now();
                 let response, responseData;
+                const useStreamOverride = (endpoint === 'crawl') && shouldUseStream(payload);
 
                 if (endpoint === 'llm') {
                     // Special handling for LLM endpoint which uses URL pattern: /llm/{encoded_url}?q={query}
@@ -681,8 +698,8 @@
                     document.querySelector('#response-content code').textContent = JSON.stringify(responseData, null, 2);
                     document.querySelector('#response-content code').className = 'json hljs';
                     forceHighlightElement(document.querySelector('#response-content code'));
-                } else if (endpoint === 'crawl_stream') {
-                    // Stream processing
+                } else if (endpoint === 'crawl_stream' || useStreamOverride) {
+                    // Stream processing - now handled directly by /crawl endpoint
                     response = await fetch(api, {
                         method: 'POST',
                         headers: { 'Content-Type': 'application/json' },
@@ -757,6 +774,7 @@
                     const question = document.getElementById('llm-question').value.trim() || "What is this page about?";
                     generateSnippets(`${api}/${encodedUrl}?q=${encodeURIComponent(question)}`, null, 'GET');
                 } else {
+                    // Use the same API endpoint for both streaming and non-streaming
                     generateSnippets(api, payload);
                 }
             } catch (error) {
@@ -786,7 +804,7 @@
             document.getElementById('stress-avg-time').textContent = '0';
             document.getElementById('stress-peak-mem').textContent = '0';
 
-            const api = useStream ? '/crawl/stream' : '/crawl';
+            const api = '/crawl'; // Always use /crawl - backend handles streaming internally
             const urls = Array.from({ length: total }, (_, i) => `https://httpbin.org/anything/stress-${i}-${Date.now()}`);
             const chunks = [];
 

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) -> str:
+def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> Optional[str]:
     """Get the appropriate API key based on the LLM provider.
     
     Args:
@@ -79,19 +79,14 @@ def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> str:
         provider: Optional provider override (e.g., "openai/gpt-4")
     
     Returns:
-        The API key for the provider, or empty string if not found
+        The API key if directly configured, otherwise None to let litellm handle it
     """
-        
-    # Use provided provider or fall back to config
-    if not provider:
-        provider = config["llm"]["provider"]
-    
-    # Check if direct API key is configured
+    # Check if direct API key is configured (for backward compatibility)
     if "api_key" in config["llm"]:
         return config["llm"]["api_key"]
     
-    # Fall back to the configured api_key_env if no match
-    return os.environ.get(config["llm"].get("api_key_env", ""), "")
+    # Return None - litellm will automatically find the right environment variable
+    return None
 
 
 def validate_llm_provider(config: Dict, provider: Optional[str] = None) -> tuple[bool, str]:
@@ -104,19 +99,78 @@ def validate_llm_provider(config: Dict, provider: Optional[str] = None) -> tuple
     Returns:
         Tuple of (is_valid, error_message)
     """
-    # 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."
+    # If a direct API key is configured, validation passes
+    if "api_key" in config["llm"]:
+        return True, ""
     
+    # Otherwise, trust that litellm will find the appropriate environment variable
+    # We can't easily validate this without reimplementing litellm's logic
     return True, ""
 
 
+def get_llm_temperature(config: Dict, provider: Optional[str] = None) -> Optional[float]:
+    """Get temperature setting based on the LLM provider.
+    
+    Priority order:
+    1. Provider-specific environment variable (e.g., OPENAI_TEMPERATURE)
+    2. Global LLM_TEMPERATURE environment variable
+    3. None (to use litellm/provider defaults)
+    
+    Args:
+        config: The application configuration dictionary
+        provider: Optional provider override (e.g., "openai/gpt-4")
+    
+    Returns:
+        The temperature setting if configured, otherwise None
+    """
+    # Check provider-specific temperature first
+    if provider:
+        provider_name = provider.split('/')[0].upper()
+        provider_temp = os.environ.get(f"{provider_name}_TEMPERATURE")
+        if provider_temp:
+            try:
+                return float(provider_temp)
+            except ValueError:
+                logging.warning(f"Invalid temperature value for {provider_name}: {provider_temp}")
+    
+    # Check global LLM_TEMPERATURE
+    global_temp = os.environ.get("LLM_TEMPERATURE")
+    if global_temp:
+        try:
+            return float(global_temp)
+        except ValueError:
+            logging.warning(f"Invalid global temperature value: {global_temp}")
+    
+    # Return None to use litellm/provider defaults
+    return None
+
+
+def get_llm_base_url(config: Dict, provider: Optional[str] = None) -> Optional[str]:
+    """Get base URL setting based on the LLM provider.
+    
+    Priority order:
+    1. Provider-specific environment variable (e.g., OPENAI_BASE_URL)
+    2. Global LLM_BASE_URL environment variable
+    3. None (to use default endpoints)
+    
+    Args:
+        config: The application configuration dictionary
+        provider: Optional provider override (e.g., "openai/gpt-4")
+    
+    Returns:
+        The base URL if configured, otherwise None
+    """
+    # Check provider-specific base URL first
+    if provider:
+        provider_name = provider.split('/')[0].upper()
+        provider_url = os.environ.get(f"{provider_name}_BASE_URL")
+        if provider_url:
+            return provider_url
+    
+    # Check global LLM_BASE_URL
+    return os.environ.get("LLM_BASE_URL")
+
+
 def verify_email_domain(email: str) -> bool:
     try:
         domain = email.split('@')[1]

docs/examples/adaptive_crawling/llm_config_example.py

@@ -0,0 +1,154 @@
+import asyncio
+import os
+from crawl4ai import AsyncWebCrawler, AdaptiveCrawler, AdaptiveConfig, LLMConfig
+
+
+async def test_configuration(name: str, config: AdaptiveConfig, url: str, query: str):
+    """Test a specific configuration"""
+    print(f"\n{'='*60}")
+    print(f"Configuration: {name}")
+    print(f"{'='*60}")
+    
+    async with AsyncWebCrawler(verbose=False) as crawler:
+        adaptive = AdaptiveCrawler(crawler, config)
+        result = await adaptive.digest(start_url=url, query=query)
+        
+        print("\n" + "="*50)
+        print("CRAWL STATISTICS")
+        print("="*50)
+        adaptive.print_stats(detailed=False)
+        
+        # Get the most relevant content found
+        print("\n" + "="*50)
+        print("MOST RELEVANT PAGES")
+        print("="*50)
+        
+        relevant_pages = adaptive.get_relevant_content(top_k=5)
+        for i, page in enumerate(relevant_pages, 1):
+            print(f"\n{i}. {page['url']}")
+            print(f"   Relevance Score: {page['score']:.2%}")
+            
+            # Show a snippet of the content
+            content = page['content'] or ""
+            if content:
+                snippet = content[:200].replace('\n', ' ')
+                if len(content) > 200:
+                    snippet += "..."
+                print(f"   Preview: {snippet}")
+        
+        print(f"\n{'='*50}")
+        print(f"Pages crawled: {len(result.crawled_urls)}")
+        print(f"Final confidence: {adaptive.confidence:.1%}")
+        print(f"Stopped reason: {result.metrics.get('stopped_reason', 'max_pages')}")
+        
+        if result.metrics.get('is_irrelevant', False):
+            print("⚠️  Query detected as irrelevant!")
+        
+        return result
+
+
+async def llm_embedding():
+    """Demonstrate various embedding configurations"""
+    
+    print("EMBEDDING STRATEGY CONFIGURATION EXAMPLES")
+    print("=" * 60)
+    
+    # Base URL and query for testing
+    test_url = "https://docs.python.org/3/library/asyncio.html"
+    
+    openai_llm_config = LLMConfig(
+        provider='openai/text-embedding-3-small',
+        api_token=os.getenv('OPENAI_API_KEY'),
+        temperature=0.7,
+        max_tokens=2000
+    )
+    config_openai = AdaptiveConfig(
+        strategy="embedding",
+        max_pages=10,
+        
+        # Use OpenAI embeddings
+        embedding_llm_config=openai_llm_config,
+        # embedding_llm_config={
+        #     'provider': 'openai/text-embedding-3-small',
+        #     'api_token': os.getenv('OPENAI_API_KEY')
+        # },
+        
+        # OpenAI embeddings are high quality, can be stricter
+        embedding_k_exp=4.0,
+        n_query_variations=12
+    )
+    
+    await test_configuration(
+        "OpenAI Embeddings",
+        config_openai,
+        test_url,
+        # "event-driven architecture patterns"
+        "async await context managers coroutines"
+    )
+    return
+    
+    
+
+async def basic_adaptive_crawling():
+    """Basic adaptive crawling example"""
+    
+    # Initialize the crawler
+    async with AsyncWebCrawler(verbose=True) as crawler:
+        # Create an adaptive crawler with default settings (statistical strategy)
+        adaptive = AdaptiveCrawler(crawler)
+        
+        # Note: You can also use embedding strategy for semantic understanding:
+        # from crawl4ai import AdaptiveConfig
+        # config = AdaptiveConfig(strategy="embedding")
+        # adaptive = AdaptiveCrawler(crawler, config)
+        
+        # Start adaptive crawling
+        print("Starting adaptive crawl for Python async programming information...")
+        result = await adaptive.digest(
+            start_url="https://docs.python.org/3/library/asyncio.html",
+            query="async await context managers coroutines"
+        )
+        
+        # Display crawl statistics
+        print("\n" + "="*50)
+        print("CRAWL STATISTICS")
+        print("="*50)
+        adaptive.print_stats(detailed=False)
+        
+        # Get the most relevant content found
+        print("\n" + "="*50)
+        print("MOST RELEVANT PAGES")
+        print("="*50)
+        
+        relevant_pages = adaptive.get_relevant_content(top_k=5)
+        for i, page in enumerate(relevant_pages, 1):
+            print(f"\n{i}. {page['url']}")
+            print(f"   Relevance Score: {page['score']:.2%}")
+            
+            # Show a snippet of the content
+            content = page['content'] or ""
+            if content:
+                snippet = content[:200].replace('\n', ' ')
+                if len(content) > 200:
+                    snippet += "..."
+                print(f"   Preview: {snippet}")
+        
+        # Show final confidence
+        print(f"\n{'='*50}")
+        print(f"Final Confidence: {adaptive.confidence:.2%}")
+        print(f"Total Pages Crawled: {len(result.crawled_urls)}")
+        print(f"Knowledge Base Size: {len(adaptive.state.knowledge_base)} documents")
+        
+        
+        if adaptive.confidence >= 0.8:
+            print("✓ High confidence - can answer detailed questions about async Python")
+        elif adaptive.confidence >= 0.6:
+            print("~ Moderate confidence - can answer basic questions") 
+        else:
+            print("✗ Low confidence - need more information")
+
+
+
+if __name__ == "__main__":
+    asyncio.run(llm_embedding())
+    # asyncio.run(basic_adaptive_crawling())

docs/examples/website-to-api/.gitignore

@@ -0,0 +1,221 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py.cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+#pdm.lock
+#pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+#pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# Redis 
+*.rdb
+*.aof
+*.pid
+
+# RabbitMQ
+mnesia/
+rabbitmq/
+rabbitmq-data/
+
+# ActiveMQ
+activemq-data/
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+# Streamlit
+.streamlit/secrets.toml
+
+#directories
+models
+schemas
+saved_requests

docs/examples/website-to-api/README.md

@@ -0,0 +1,252 @@
+# Web Scraper API with Custom Model Support
+
+A powerful web scraping API that converts any website into structured data using AI. Features a beautiful minimalist frontend interface and support for custom LLM models!
+
+## Features
+
+- **AI-Powered Scraping**: Provide a URL and plain English query to extract structured data
+- **Beautiful Frontend**: Modern minimalist black-and-white interface with smooth UX
+- **Custom Model Support**: Use any LLM provider (OpenAI, Gemini, Anthropic, etc.) with your own API keys
+- **Model Management**: Save, list, and manage multiple model configurations via web interface
+- **Dual Scraping Approaches**: Choose between Schema-based (faster) or LLM-based (more flexible) extraction
+- **API Request History**: Automatic saving and display of all API requests with cURL commands
+- **Schema Caching**: Intelligent caching of generated schemas for faster subsequent requests
+- **Duplicate Prevention**: Avoids saving duplicate requests (same URL + query)
+- **RESTful API**: Easy-to-use HTTP endpoints for all operations
+
+## Quick Start
+
+### 1. Install Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### 2. Start the API Server
+
+```bash
+python app.py
+```
+
+The server will start on `http://localhost:8000` with a beautiful web interface!
+
+### 3. Using the Web Interface
+
+Once the server is running, open your browser and go to `http://localhost:8000` to access the modern web interface!
+
+#### Pages:
+- **Scrape Data**: Enter URLs and queries to extract structured data
+- **Models**: Manage your AI model configurations (add, list, delete)
+- **API Requests**: View history of all scraping requests with cURL commands
+
+#### Features:
+- **Minimalist Design**: Clean black-and-white theme inspired by modern web apps
+- **Real-time Results**: See extracted data in formatted JSON
+- **Copy to Clipboard**: Easy copying of results
+- **Toast Notifications**: User-friendly feedback
+- **Dual Scraping Modes**: Choose between Schema-based and LLM-based approaches
+
+## Model Management
+
+### Adding Models via Web Interface
+
+1. Go to the **Models** page
+2. Enter your model details:
+   - **Provider**: LLM provider (e.g., `gemini/gemini-2.5-flash`, `openai/gpt-4o`)
+   - **API Token**: Your API key for the provider
+3. Click "Add Model"
+
+### API Usage for Model Management
+
+#### Save a Model Configuration
+
+```bash
+curl -X POST "http://localhost:8000/models" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "provider": "gemini/gemini-2.5-flash",
+    "api_token": "your-api-key-here"
+  }'
+```
+
+#### List Saved Models
+
+```bash
+curl -X GET "http://localhost:8000/models"
+```
+
+#### Delete a Model Configuration
+
+```bash
+curl -X DELETE "http://localhost:8000/models/my-gemini"
+```
+
+## Scraping Approaches
+
+### 1. Schema-based Scraping (Faster)
+- Generates CSS selectors for targeted extraction
+- Caches schemas for repeated requests
+- Faster execution for structured websites
+
+### 2. LLM-based Scraping (More Flexible)
+- Direct LLM extraction without schema generation
+- More flexible for complex or dynamic content
+- Better for unstructured data extraction
+
+## Supported LLM Providers
+
+The API supports any LLM provider that crawl4ai supports, including:
+
+- **Google Gemini**: `gemini/gemini-2.5-flash`, `gemini/gemini-pro`
+- **OpenAI**: `openai/gpt-4`, `openai/gpt-3.5-turbo`
+- **Anthropic**: `anthropic/claude-3-opus`, `anthropic/claude-3-sonnet`
+- **And more...**
+
+## API Endpoints
+
+### Core Endpoints
+
+- `POST /scrape` - Schema-based scraping
+- `POST /scrape-with-llm` - LLM-based scraping
+- `GET /schemas` - List cached schemas
+- `POST /clear-cache` - Clear schema cache
+- `GET /health` - Health check
+
+### Model Management Endpoints
+
+- `GET /models` - List saved model configurations
+- `POST /models` - Save a new model configuration
+- `DELETE /models/{model_name}` - Delete a model configuration
+
+### API Request History
+
+- `GET /saved-requests` - List all saved API requests
+- `DELETE /saved-requests/{request_id}` - Delete a saved request
+
+## Request/Response Examples
+
+### Scrape Request
+
+```json
+{
+  "url": "https://example.com",
+  "query": "Extract the product name, price, and description",
+  "model_name": "my-custom-model"
+}
+```
+
+### Scrape Response
+
+```json
+{
+  "success": true,
+  "url": "https://example.com",
+  "query": "Extract the product name, price, and description",
+  "extracted_data": {
+    "product_name": "Example Product",
+    "price": "$99.99",
+    "description": "This is an example product description"
+  },
+  "schema_used": { ... },
+  "timestamp": "2024-01-01T12:00:00Z"
+}
+```
+
+### Model Configuration Request
+
+```json
+{
+  "provider": "gemini/gemini-2.5-flash",
+  "api_token": "your-api-key-here"
+}
+```
+
+## Testing
+
+Run the test script to verify the model management functionality:
+
+```bash
+python test_models.py
+```
+
+## File Structure
+
+```
+parse_example/
+├── api_server.py          # FastAPI server with all endpoints
+├── web_scraper_lib.py     # Core scraping library
+├── test_models.py         # Test script for model management
+├── requirements.txt       # Dependencies
+├── static/               # Frontend files
+│   ├── index.html        # Main HTML interface
+│   ├── styles.css        # CSS styles (minimalist theme)
+│   └── script.js         # JavaScript functionality
+├── schemas/              # Cached schemas
+├── models/               # Saved model configurations
+├── saved_requests/       # API request history
+└── README.md            # This file
+```
+
+## Advanced Usage
+
+### Using the Library Directly
+
+```python
+from web_scraper_lib import WebScraperAgent
+
+# Initialize agent
+agent = WebScraperAgent()
+
+# Save a model configuration
+agent.save_model_config(
+    model_name="my-model",
+    provider="openai/gpt-4",
+    api_token="your-api-key"
+)
+
+# Schema-based scraping
+result = await agent.scrape_data(
+    url="https://example.com",
+    query="Extract product information",
+    model_name="my-model"
+)
+
+# LLM-based scraping
+result = await agent.scrape_data_with_llm(
+    url="https://example.com",
+    query="Extract product information",
+    model_name="my-model"
+)
+```
+
+### Schema Caching
+
+The system automatically caches generated schemas based on URL and query combinations:
+
+- **First request**: Generates schema using AI
+- **Subsequent requests**: Uses cached schema for faster extraction
+
+### API Request History
+
+All API requests are automatically saved with:
+- Request details (URL, query, model used)
+- Response data
+- Timestamp
+- cURL command for re-execution
+
+### Duplicate Prevention
+
+The system prevents saving duplicate requests:
+- Same URL + query combinations are not saved multiple times
+- Returns existing request ID for duplicates
+- Keeps the API request history clean
+
+## Error Handling
+
+The API provides detailed error messages for common issues:
+
+- Invalid URLs
+- Missing model configurations
+- API key errors
+- Network timeouts
+- Parsing errors

docs/examples/website-to-api/api_server.py

@@ -0,0 +1,363 @@
+from fastapi import FastAPI, HTTPException
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from pydantic import BaseModel, HttpUrl
+from typing import Dict, Any, Optional, Union, List
+import uvicorn
+import asyncio
+import os
+import json
+from datetime import datetime
+from web_scraper_lib import WebScraperAgent, scrape_website
+
+app = FastAPI(
+    title="Web Scraper API",
+    description="Convert any website into a structured data API. Provide a URL and tell AI what data you need in plain English.",
+    version="1.0.0"
+)
+
+# Mount static files
+if os.path.exists("static"):
+    app.mount("/static", StaticFiles(directory="static"), name="static")
+
+# Mount assets directory
+if os.path.exists("assets"):
+    app.mount("/assets", StaticFiles(directory="assets"), name="assets")
+
+# Initialize the scraper agent
+scraper_agent = WebScraperAgent()
+
+# Create directory for saved API requests
+os.makedirs("saved_requests", exist_ok=True)
+
+class ScrapeRequest(BaseModel):
+    url: HttpUrl
+    query: str
+    model_name: Optional[str] = None
+
+class ModelConfigRequest(BaseModel):
+    model_name: str
+    provider: str
+    api_token: str
+
+class ScrapeResponse(BaseModel):
+    success: bool
+    url: str
+    query: str
+    extracted_data: Union[Dict[str, Any], list]
+    schema_used: Optional[Dict[str, Any]] = None
+    timestamp: Optional[str] = None
+    error: Optional[str] = None
+
+class SavedApiRequest(BaseModel):
+    id: str
+    endpoint: str
+    method: str
+    headers: Dict[str, str]
+    body: Dict[str, Any]
+    timestamp: str
+    response: Optional[Dict[str, Any]] = None
+
+def save_api_request(endpoint: str, method: str, headers: Dict[str, str], body: Dict[str, Any], response: Optional[Dict[str, Any]] = None) -> str:
+    """Save an API request to a JSON file."""
+    
+    # Check for duplicate requests (same URL and query)
+    if endpoint in ["/scrape", "/scrape-with-llm"] and "url" in body and "query" in body:
+        existing_requests = get_saved_requests()
+        for existing_request in existing_requests:
+            if (existing_request.endpoint == endpoint and 
+                existing_request.body.get("url") == body["url"] and 
+                existing_request.body.get("query") == body["query"]):
+                print(f"Duplicate request found for URL: {body['url']} and query: {body['query']}")
+                return existing_request.id  # Return existing request ID instead of creating new one
+    
+    request_id = datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3]
+    
+    saved_request = SavedApiRequest(
+        id=request_id,
+        endpoint=endpoint,
+        method=method,
+        headers=headers,
+        body=body,
+        timestamp=datetime.now().isoformat(),
+        response=response
+    )
+    
+    file_path = os.path.join("saved_requests", f"{request_id}.json")
+    with open(file_path, "w") as f:
+        json.dump(saved_request.dict(), f, indent=2)
+    
+    return request_id
+
+def get_saved_requests() -> List[SavedApiRequest]:
+    """Get all saved API requests."""
+    requests = []
+    if os.path.exists("saved_requests"):
+        for filename in os.listdir("saved_requests"):
+            if filename.endswith('.json'):
+                file_path = os.path.join("saved_requests", filename)
+                try:
+                    with open(file_path, "r") as f:
+                        data = json.load(f)
+                        requests.append(SavedApiRequest(**data))
+                except Exception as e:
+                    print(f"Error loading saved request {filename}: {e}")
+    
+    # Sort by timestamp (newest first)
+    requests.sort(key=lambda x: x.timestamp, reverse=True)
+    return requests
+
+@app.get("/")
+async def root():
+    """Serve the frontend interface."""
+    if os.path.exists("static/index.html"):
+        return FileResponse("static/index.html")
+    else:
+        return {
+            "message": "Web Scraper API",
+            "description": "Convert any website into structured data with AI",
+            "endpoints": {
+                "/scrape": "POST - Scrape data from a website",
+                "/schemas": "GET - List cached schemas",
+                "/clear-cache": "POST - Clear schema cache",
+                "/models": "GET - List saved model configurations",
+                "/models": "POST - Save a new model configuration",
+                "/models/{model_name}": "DELETE - Delete a model configuration",
+                "/saved-requests": "GET - List saved API requests"
+            }
+        }
+
+@app.post("/scrape", response_model=ScrapeResponse)
+async def scrape_website_endpoint(request: ScrapeRequest):
+    """
+    Scrape structured data from any website.
+    
+    This endpoint:
+    1. Takes a URL and plain English query
+    2. Generates a custom scraper using AI
+    3. Returns structured data
+    """
+    try:
+        # Save the API request
+        headers = {"Content-Type": "application/json"}
+        body = {
+            "url": str(request.url),
+            "query": request.query,
+            "model_name": request.model_name
+        }
+        
+        result = await scraper_agent.scrape_data(
+            url=str(request.url),
+            query=request.query,
+            model_name=request.model_name
+        )
+        
+        response_data = ScrapeResponse(
+            success=True,
+            url=result["url"],
+            query=result["query"],
+            extracted_data=result["extracted_data"],
+            schema_used=result["schema_used"],
+            timestamp=result["timestamp"]
+        )
+        
+        # Save the request with response
+        save_api_request(
+            endpoint="/scrape",
+            method="POST",
+            headers=headers,
+            body=body,
+            response=response_data.dict()
+        )
+        
+        return response_data
+    
+    except Exception as e:
+        # Save the failed request
+        headers = {"Content-Type": "application/json"}
+        body = {
+            "url": str(request.url),
+            "query": request.query,
+            "model_name": request.model_name
+        }
+        
+        save_api_request(
+            endpoint="/scrape",
+            method="POST",
+            headers=headers,
+            body=body,
+            response={"error": str(e)}
+        )
+        
+        raise HTTPException(status_code=500, detail=f"Scraping failed: {str(e)}")
+
+@app.post("/scrape-with-llm", response_model=ScrapeResponse)
+async def scrape_website_endpoint_with_llm(request: ScrapeRequest):
+    """
+    Scrape structured data from any website using a custom LLM model.
+    """
+    try:
+        # Save the API request
+        headers = {"Content-Type": "application/json"}
+        body = {
+            "url": str(request.url),
+            "query": request.query,
+            "model_name": request.model_name
+        }
+        
+        result = await scraper_agent.scrape_data_with_llm(
+            url=str(request.url),
+            query=request.query,
+            model_name=request.model_name
+        )
+        
+        response_data = ScrapeResponse(
+            success=True,
+            url=result["url"],
+            query=result["query"],
+            extracted_data=result["extracted_data"],
+            timestamp=result["timestamp"]
+        )
+        
+        # Save the request with response
+        save_api_request(
+            endpoint="/scrape-with-llm",
+            method="POST",
+            headers=headers,
+            body=body,
+            response=response_data.dict()
+        )
+        
+        return response_data
+    
+    except Exception as e:
+        # Save the failed request
+        headers = {"Content-Type": "application/json"}
+        body = {
+            "url": str(request.url),
+            "query": request.query,
+            "model_name": request.model_name
+        }
+        
+        save_api_request(
+            endpoint="/scrape-with-llm",
+            method="POST",
+            headers=headers,
+            body=body,
+            response={"error": str(e)}
+        )
+        
+        raise HTTPException(status_code=500, detail=f"Scraping failed: {str(e)}")
+
+@app.get("/saved-requests")
+async def list_saved_requests():
+    """List all saved API requests."""
+    try:
+        requests = get_saved_requests()
+        return {
+            "success": True,
+            "requests": [req.dict() for req in requests],
+            "count": len(requests)
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to list saved requests: {str(e)}")
+
+@app.delete("/saved-requests/{request_id}")
+async def delete_saved_request(request_id: str):
+    """Delete a saved API request."""
+    try:
+        file_path = os.path.join("saved_requests", f"{request_id}.json")
+        if os.path.exists(file_path):
+            os.remove(file_path)
+            return {
+                "success": True,
+                "message": f"Saved request '{request_id}' deleted successfully"
+            }
+        else:
+            raise HTTPException(status_code=404, detail=f"Saved request '{request_id}' not found")
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to delete saved request: {str(e)}")
+
+@app.get("/schemas")
+async def list_cached_schemas():
+    """List all cached schemas."""
+    try:
+        schemas = await scraper_agent.get_cached_schemas()
+        return {
+            "success": True,
+            "cached_schemas": schemas,
+            "count": len(schemas)
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to list schemas: {str(e)}")
+
+@app.post("/clear-cache")
+async def clear_schema_cache():
+    """Clear all cached schemas."""
+    try:
+        scraper_agent.clear_cache()
+        return {
+            "success": True,
+            "message": "Schema cache cleared successfully"
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to clear cache: {str(e)}")
+
+@app.get("/models")
+async def list_models():
+    """List all saved model configurations."""
+    try:
+        models = scraper_agent.list_saved_models()
+        return {
+            "success": True,
+            "models": models,
+            "count": len(models)
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to list models: {str(e)}")
+
+@app.post("/models")
+async def save_model_config(request: ModelConfigRequest):
+    """Save a new model configuration."""
+    try:
+        success = scraper_agent.save_model_config(
+            model_name=request.model_name,
+            provider=request.provider,
+            api_token=request.api_token
+        )
+        
+        if success:
+            return {
+                "success": True,
+                "message": f"Model configuration '{request.model_name}' saved successfully"
+            }
+        else:
+            raise HTTPException(status_code=500, detail="Failed to save model configuration")
+    
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to save model: {str(e)}")
+
+@app.delete("/models/{model_name}")
+async def delete_model_config(model_name: str):
+    """Delete a model configuration."""
+    try:
+        success = scraper_agent.delete_model_config(model_name)
+        
+        if success:
+            return {
+                "success": True,
+                "message": f"Model configuration '{model_name}' deleted successfully"
+            }
+        else:
+            raise HTTPException(status_code=404, detail=f"Model configuration '{model_name}' not found")
+    
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to delete model: {str(e)}")
+
+@app.get("/health")
+async def health_check():
+    """Health check endpoint."""
+    return {"status": "healthy", "service": "web-scraper-api"}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)

docs/examples/website-to-api/app.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+"""
+Startup script for the Web Scraper API with frontend interface.
+"""
+
+import os
+import sys
+import uvicorn
+from pathlib import Path
+
+def main():
+    # Check if static directory exists
+    static_dir = Path("static")
+    if not static_dir.exists():
+        print("❌ Static directory not found!")
+        print("Please make sure the 'static' directory exists with the frontend files.")
+        sys.exit(1)
+    
+    # Check if required frontend files exist
+    required_files = ["index.html", "styles.css", "script.js"]
+    missing_files = []
+    
+    for file in required_files:
+        if not (static_dir / file).exists():
+            missing_files.append(file)
+    
+    if missing_files:
+        print(f"❌ Missing frontend files: {', '.join(missing_files)}")
+        print("Please make sure all frontend files are present in the static directory.")
+        sys.exit(1)
+    
+    print("🚀 Starting Web Scraper API with Frontend Interface")
+    print("=" * 50)
+    print("📁 Static files found and ready to serve")
+    print("🌐 Frontend will be available at: http://localhost:8000")
+    print("🔌 API endpoints available at: http://localhost:8000/docs")
+    print("=" * 50)
+    
+    # Start the server
+    uvicorn.run(
+        "api_server:app",
+        host="0.0.0.0",
+        port=8000,
+        reload=True,
+        log_level="info"
+    )
+
+if __name__ == "__main__":
+    main() 

docs/examples/website-to-api/requirements.txt

@@ -0,0 +1,5 @@
+crawl4ai
+fastapi
+uvicorn
+pydantic
+litellm

docs/examples/website-to-api/static/index.html

@@ -0,0 +1,201 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Web2API Example</title>
+    <link rel="stylesheet" href="/static/styles.css">
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
+</head>
+<body>
+    <!-- Header -->
+    <header class="header">
+        <div class="header-content">
+            <div class="logo">
+                <img src="/assets/crawl4ai_logo.jpg" alt="Crawl4AI Logo" class="logo-image">
+                <span>Web2API Example</span>
+            </div>
+            <nav class="nav-links">
+                <a href="#" class="nav-link active" data-page="scrape">Scrape</a>
+                <a href="#" class="nav-link" data-page="models">Models</a>
+                <a href="#" class="nav-link" data-page="requests">API Requests</a>
+            </nav>
+        </div>
+    </header>
+
+    <!-- Main Content -->
+    <main class="main-content">
+        <!-- Scrape Page -->
+        <div id="scrape-page" class="page active">
+            <div class="hero-section">
+                <h1 class="hero-title">Turn Any Website Into An API</h1>
+                <p class="hero-subtitle">This example shows how to turn any website into an API using Crawl4AI.</p>
+            </div>
+
+            <!-- Workflow Demonstration -->
+            <div class="workflow-demo">
+                <div class="workflow-step">
+                    <h3 class="step-title">1. Your Request</h3>
+                    <div class="request-box">
+                        <div class="input-group">
+                            <label>URL:</label>
+                            <input type="url" id="url" name="url" placeholder="https://example-bookstore.com/new-releases" required>
+                        </div>
+                        <div class="input-group">
+                            <label>QUERY:</label>
+                            <textarea id="query" name="query" placeholder="Extract all the book titles, their authors, and the biography of the author" required></textarea>
+                        </div>
+                        <div class="form-options">
+                            <div class="option-group">
+                                <label for="scraping-approach">Approach:</label>
+                                <select id="scraping-approach" name="scraping_approach">
+                                    <option value="llm">LLM-based (More Flexible)</option>
+                                    <option value="schema">Schema-based (Uses LLM once!)</option>
+                                </select>
+                            </div>
+                            <div class="option-group">
+                                <label for="model-select">Model:</label>
+                                <select id="model-select" name="model_name" required>
+                                    <option value="">Select a Model</option>
+                                </select>
+                            </div>
+                        </div>
+                        <button type="submit" id="extract-btn" class="extract-btn">
+                            <i class="fas fa-magic"></i>
+                            Extract Data
+                        </button>
+                    </div>
+                </div>
+
+                <div class="workflow-arrow">→</div>
+
+                <div class="workflow-step">
+                    <h3 class="step-title">2. Your Instant API & Data</h3>
+                    <div class="response-container">
+                        <div class="api-request-box">
+                            <label>API Request (cURL):</label>
+                            <pre id="curl-example">curl -X POST http://localhost:8000/scrape -H "Content-Type: application/json" -d '{"url": "...", "query": "..."}'
+
+# Or for LLM-based approach:
+curl -X POST http://localhost:8000/scrape-with-llm -H "Content-Type: application/json" -d '{"url": "...", "query": "..."}'</pre>
+                        </div>
+                        <div class="json-response-box">
+                            <label>JSON Response:</label>
+                            <pre id="json-output">{
+  "success": true,
+  "extracted_data": [
+    {
+      "title": "Example Book",
+      "author": "John Doe",
+      "description": "A great book..."
+    }
+  ]
+}</pre>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <!-- Results Section -->
+            <div id="results-section" class="results-section" style="display: none;">
+                <div class="results-header">
+                    <h2>Extracted Data</h2>
+                    <button id="copy-json" class="copy-btn">
+                        <i class="fas fa-copy"></i>
+                        Copy JSON
+                    </button>
+                </div>
+                <div class="results-content">
+                    <div class="result-info">
+                        <div class="info-item">
+                            <span class="label">URL:</span>
+                            <span id="result-url" class="value"></span>
+                        </div>
+                        <div class="info-item">
+                            <span class="label">Query:</span>
+                            <span id="result-query" class="value"></span>
+                        </div>
+                        <div class="info-item">
+                            <span class="label">Model Used:</span>
+                            <span id="result-model" class="value"></span>
+                        </div>
+                    </div>
+                    <div class="json-display">
+                        <pre id="actual-json-output"></pre>
+                    </div>
+                </div>
+            </div>
+
+            <!-- Loading State -->
+            <div id="loading" class="loading" style="display: none;">
+                <div class="spinner"></div>
+                <p>AI is analyzing the website and extracting data...</p>
+            </div>
+        </div>
+
+        <!-- Models Page -->
+        <div id="models-page" class="page">
+            <div class="models-header">
+                <h1>Model Configuration</h1>
+                <p>Configure and manage your AI model configurations</p>
+            </div>
+
+            <div class="models-container">
+                <!-- Add New Model Form -->
+                <div class="model-form-section">
+                    <h3>Add New Model</h3>
+                    <form id="model-form" class="model-form">
+                        <div class="form-row">
+                            <div class="input-group">
+                                <label for="model-name">Model Name:</label>
+                                <input type="text" id="model-name" name="model_name" placeholder="my-gemini" required>
+                            </div>
+                            <div class="input-group">
+                                <label for="provider">Provider:</label>
+                                <input type="text" id="provider" name="provider" placeholder="gemini/gemini-2.5-flash" required>
+                            </div>
+                        </div>
+                        
+                        <div class="input-group">
+                            <label for="api-token">API Token:</label>
+                            <input type="password" id="api-token" name="api_token" placeholder="Enter your API token" required>
+                        </div>
+
+                        <button type="submit" class="save-btn">
+                            <i class="fas fa-save"></i>
+                            Save Model
+                        </button>
+                    </form>
+                </div>
+
+                <!-- Saved Models List -->
+                <div class="saved-models-section">
+                    <h3>Saved Models</h3>
+                    <div id="models-list" class="models-list">
+                        <!-- Models will be loaded here -->
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- API Requests Page -->
+        <div id="requests-page" class="page">
+            <div class="requests-header">
+                <h1>Saved API Requests</h1>
+                <p>View and manage your previous API requests</p>
+            </div>
+
+            <div class="requests-container">
+                <div class="requests-list" id="requests-list">
+                    <!-- Saved requests will be loaded here -->
+                </div>
+            </div>
+        </div>
+    </main>
+
+    <!-- Toast Notifications -->
+    <div id="toast-container" class="toast-container"></div>
+
+    <script src="/static/script.js"></script>
+</body>
+</html> 

docs/examples/website-to-api/static/script.js

@@ -0,0 +1,401 @@
+// API Configuration
+const API_BASE_URL = 'http://localhost:8000';
+
+// DOM Elements
+const navLinks = document.querySelectorAll('.nav-link');
+const pages = document.querySelectorAll('.page');
+const scrapeForm = document.getElementById('scrape-form');
+const modelForm = document.getElementById('model-form');
+const modelSelect = document.getElementById('model-select');
+const modelsList = document.getElementById('models-list');
+const resultsSection = document.getElementById('results-section');
+const loadingSection = document.getElementById('loading');
+const copyJsonBtn = document.getElementById('copy-json');
+
+// Navigation
+navLinks.forEach(link => {
+    link.addEventListener('click', (e) => {
+        e.preventDefault();
+        const targetPage = link.dataset.page;
+        
+        // Update active nav link
+        navLinks.forEach(l => l.classList.remove('active'));
+        link.classList.add('active');
+        
+        // Show target page
+        pages.forEach(page => page.classList.remove('active'));
+        document.getElementById(`${targetPage}-page`).classList.add('active');
+        
+        // Load data for the page
+        if (targetPage === 'models') {
+            loadModels();
+        } else if (targetPage === 'requests') {
+            loadSavedRequests();
+        }
+    });
+});
+
+// Scrape Form Handler
+document.getElementById('extract-btn').addEventListener('click', async (e) => {
+    e.preventDefault();
+    
+    // Scroll to results section immediately when button is clicked
+    document.getElementById('results-section').scrollIntoView({ 
+        behavior: 'smooth', 
+        block: 'start' 
+    });
+    
+    const url = document.getElementById('url').value;
+    const query = document.getElementById('query').value;
+    const headless = true; // Always use headless mode
+    const model_name = document.getElementById('model-select').value || null;
+    const scraping_approach = document.getElementById('scraping-approach').value;
+    
+    if (!url || !query) {
+        showToast('Please fill in both URL and query fields', 'error');
+        return;
+    }
+    
+    if (!model_name) {
+        showToast('Please select a model from the dropdown or add one from the Models page', 'error');
+        return;
+    }
+    
+    const data = {
+        url: url,
+        query: query,
+        headless: headless,
+        model_name: model_name
+    };
+    
+    // Show loading state
+    showLoading(true);
+    hideResults();
+    
+    try {
+        // Choose endpoint based on scraping approach
+        const endpoint = scraping_approach === 'llm' ? '/scrape-with-llm' : '/scrape';
+        
+        const response = await fetch(`${API_BASE_URL}${endpoint}`, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify(data)
+        });
+        
+        const result = await response.json();
+        
+        if (response.ok) {
+            displayResults(result);
+            showToast(`Data extracted successfully using ${scraping_approach === 'llm' ? 'LLM-based' : 'Schema-based'} approach!`, 'success');
+        } else {
+            throw new Error(result.detail || 'Failed to extract data');
+        }
+    } catch (error) {
+        console.error('Scraping error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    } finally {
+        showLoading(false);
+    }
+});
+
+// Model Form Handler
+modelForm.addEventListener('submit', async (e) => {
+    e.preventDefault();
+    
+    const formData = new FormData(modelForm);
+    const data = {
+        model_name: formData.get('model_name'),
+        provider: formData.get('provider'),
+        api_token: formData.get('api_token')
+    };
+    
+    try {
+        const response = await fetch(`${API_BASE_URL}/models`, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify(data)
+        });
+        
+        const result = await response.json();
+        
+        if (response.ok) {
+            showToast('Model saved successfully!', 'success');
+            modelForm.reset();
+            loadModels();
+            loadModelSelect();
+        } else {
+            throw new Error(result.detail || 'Failed to save model');
+        }
+    } catch (error) {
+        console.error('Model save error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    }
+});
+
+// Copy JSON Button
+copyJsonBtn.addEventListener('click', () => {
+    const actualJsonOutput = document.getElementById('actual-json-output');
+    const textToCopy = actualJsonOutput.textContent;
+    
+    navigator.clipboard.writeText(textToCopy).then(() => {
+        showToast('JSON copied to clipboard!', 'success');
+    }).catch(() => {
+        showToast('Failed to copy JSON', 'error');
+    });
+});
+
+// Load Models
+async function loadModels() {
+    try {
+        const response = await fetch(`${API_BASE_URL}/models`);
+        const result = await response.json();
+        
+        if (response.ok) {
+            displayModels(result.models);
+        } else {
+            throw new Error(result.detail || 'Failed to load models');
+        }
+    } catch (error) {
+        console.error('Load models error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    }
+}
+
+// Display Models
+function displayModels(models) {
+    if (models.length === 0) {
+        modelsList.innerHTML = '<p style="text-align: center; color: #7f8c8d; padding: 2rem;">No models saved yet. Add your first model above!</p>';
+        return;
+    }
+    
+    modelsList.innerHTML = models.map(model => `
+        <div class="model-card">
+            <div class="model-info">
+                <div class="model-name">${model}</div>
+                <div class="model-provider">Model Configuration</div>
+            </div>
+            <div class="model-actions">
+                <button class="btn btn-danger" onclick="deleteModel('${model}')">
+                    <i class="fas fa-trash"></i>
+                    Delete
+                </button>
+            </div>
+        </div>
+    `).join('');
+}
+
+// Delete Model
+async function deleteModel(modelName) {
+    if (!confirm(`Are you sure you want to delete the model "${modelName}"?`)) {
+        return;
+    }
+    
+    try {
+        const response = await fetch(`${API_BASE_URL}/models/${modelName}`, {
+            method: 'DELETE'
+        });
+        
+        const result = await response.json();
+        
+        if (response.ok) {
+            showToast('Model deleted successfully!', 'success');
+            loadModels();
+            loadModelSelect();
+        } else {
+            throw new Error(result.detail || 'Failed to delete model');
+        }
+    } catch (error) {
+        console.error('Delete model error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    }
+}
+
+// Load Model Select Options
+async function loadModelSelect() {
+    try {
+        const response = await fetch(`${API_BASE_URL}/models`);
+        const result = await response.json();
+        
+        if (response.ok) {
+            // Clear existing options
+            modelSelect.innerHTML = '<option value="">Select a Model</option>';
+            
+            // Add model options
+            result.models.forEach(model => {
+                const option = document.createElement('option');
+                option.value = model;
+                option.textContent = model;
+                modelSelect.appendChild(option);
+            });
+        }
+    } catch (error) {
+        console.error('Load model select error:', error);
+    }
+}
+
+// Display Results
+function displayResults(result) {
+    // Update result info
+    document.getElementById('result-url').textContent = result.url;
+    document.getElementById('result-query').textContent = result.query;
+    document.getElementById('result-model').textContent = result.model_name || 'Default Model';
+    
+    // Display JSON in the actual results section
+    const actualJsonOutput = document.getElementById('actual-json-output');
+    actualJsonOutput.textContent = JSON.stringify(result.extracted_data, null, 2);
+    
+    // Don't update the sample JSON in the workflow demo - keep it as example
+    
+    // Update the cURL example based on the approach used
+    const scraping_approach = document.getElementById('scraping-approach').value;
+    const endpoint = scraping_approach === 'llm' ? '/scrape-with-llm' : '/scrape';
+    const curlExample = document.getElementById('curl-example');
+    curlExample.textContent = `curl -X POST http://localhost:8000${endpoint} -H "Content-Type: application/json" -d '{"url": "${result.url}", "query": "${result.query}"}'`;
+    
+    // Show results section
+    resultsSection.style.display = 'block';
+    resultsSection.scrollIntoView({ behavior: 'smooth' });
+}
+
+// Show/Hide Loading
+function showLoading(show) {
+    loadingSection.style.display = show ? 'block' : 'none';
+}
+
+// Hide Results
+function hideResults() {
+    resultsSection.style.display = 'none';
+}
+
+// Toast Notifications
+function showToast(message, type = 'info') {
+    const toastContainer = document.getElementById('toast-container');
+    const toast = document.createElement('div');
+    toast.className = `toast ${type}`;
+    
+    const icon = type === 'success' ? 'fas fa-check-circle' : 
+                 type === 'error' ? 'fas fa-exclamation-circle' : 
+                 'fas fa-info-circle';
+    
+    toast.innerHTML = `
+        <i class="${icon}"></i>
+        <span>${message}</span>
+    `;
+    
+    toastContainer.appendChild(toast);
+    
+    // Auto remove after 5 seconds
+    setTimeout(() => {
+        toast.remove();
+    }, 5000);
+}
+
+// Load Saved Requests
+async function loadSavedRequests() {
+    try {
+        const response = await fetch(`${API_BASE_URL}/saved-requests`);
+        const result = await response.json();
+        
+        if (response.ok) {
+            displaySavedRequests(result.requests);
+        } else {
+            throw new Error(result.detail || 'Failed to load saved requests');
+        }
+    } catch (error) {
+        console.error('Load saved requests error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    }
+}
+
+// Display Saved Requests
+function displaySavedRequests(requests) {
+    const requestsList = document.getElementById('requests-list');
+    
+    if (requests.length === 0) {
+        requestsList.innerHTML = '<p style="text-align: center; color: #CCCCCC; padding: 2rem;">No saved API requests yet. Make your first request from the Scrape page!</p>';
+        return;
+    }
+    
+    requestsList.innerHTML = requests.map(request => {
+        const url = request.body.url;
+        const query = request.body.query;
+        const model = request.body.model_name || 'Default Model';
+        const endpoint = request.endpoint;
+        
+        // Create curl command
+        const curlCommand = `curl -X POST http://localhost:8000${endpoint} \\
+  -H "Content-Type: application/json" \\
+  -d '{
+    "url": "${url}",
+    "query": "${query}",
+    "model_name": "${model}"
+  }'`;
+        
+        return `
+            <div class="request-card">
+                <div class="request-header">
+                    <div class="request-info">
+                        <div class="request-url">${url}</div>
+                        <div class="request-query">${query}</div>
+                    </div>
+                    <div class="request-actions">
+                        <button class="btn-danger" onclick="deleteSavedRequest('${request.id}')">
+                            <i class="fas fa-trash"></i>
+                            Delete
+                        </button>
+                    </div>
+                </div>
+                
+                <div class="request-curl">
+                    <h4>cURL Command:</h4>
+                    <pre>${curlCommand}</pre>
+                </div>
+            </div>
+        `;
+    }).join('');
+}
+
+// Delete Saved Request
+async function deleteSavedRequest(requestId) {
+    if (!confirm('Are you sure you want to delete this saved request?')) {
+        return;
+    }
+    
+    try {
+        const response = await fetch(`${API_BASE_URL}/saved-requests/${requestId}`, {
+            method: 'DELETE'
+        });
+        
+        const result = await response.json();
+        
+        if (response.ok) {
+            showToast('Saved request deleted successfully!', 'success');
+            loadSavedRequests();
+        } else {
+            throw new Error(result.detail || 'Failed to delete saved request');
+        }
+    } catch (error) {
+        console.error('Delete saved request error:', error);
+        showToast(`Error: ${error.message}`, 'error');
+    }
+}
+
+// Initialize
+document.addEventListener('DOMContentLoaded', () => {
+    loadModelSelect();
+    
+    // Check if API is available
+    fetch(`${API_BASE_URL}/health`)
+        .then(response => {
+            if (!response.ok) {
+                showToast('Warning: API server might not be running', 'error');
+            }
+        })
+        .catch(() => {
+            showToast('Warning: Cannot connect to API server. Make sure it\'s running on localhost:8000', 'error');
+        });
+}); 

docs/examples/website-to-api/static/styles.css

@@ -0,0 +1,765 @@
+/* Reset and Base Styles */
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+body {
+    font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+    background: #000000;
+    color: #FFFFFF;
+    line-height: 1.6;
+    font-size: 16px;
+}
+
+/* Header */
+.header {
+    border-bottom: 1px solid #333;
+    padding: 1rem 0;
+    background: #000000;
+    position: sticky;
+    top: 0;
+    z-index: 100;
+}
+
+.header-content {
+    max-width: 1200px;
+    margin: 0 auto;
+    padding: 0 2rem;
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+}
+
+.logo {
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    font-size: 1.5rem;
+    font-weight: 600;
+    color: #FFFFFF;
+}
+
+.logo-image {
+    width: 40px;
+    height: 40px;
+    border-radius: 4px;
+    object-fit: contain;
+}
+
+.nav-links {
+    display: flex;
+    gap: 2rem;
+}
+
+.nav-link {
+    color: #CCCCCC;
+    text-decoration: none;
+    font-weight: 500;
+    transition: color 0.2s ease;
+}
+
+.nav-link:hover,
+.nav-link.active {
+    color: #FFFFFF;
+}
+
+/* Main Content */
+.main-content {
+    max-width: 1200px;
+    margin: 0 auto;
+    padding: 2rem;
+}
+
+.page {
+    display: none;
+}
+
+.page.active {
+    display: block;
+}
+
+/* Hero Section */
+.hero-section {
+    text-align: center;
+    margin-bottom: 4rem;
+    padding: 2rem 0;
+}
+
+.hero-title {
+    font-size: 3rem;
+    font-weight: 700;
+    color: #FFFFFF;
+    margin-bottom: 1rem;
+    line-height: 1.2;
+}
+
+.hero-subtitle {
+    font-size: 1.25rem;
+    color: #CCCCCC;
+    max-width: 600px;
+    margin: 0 auto;
+}
+
+/* Workflow Demo */
+.workflow-demo {
+    display: grid;
+    grid-template-columns: 1fr auto 1fr;
+    gap: 2rem;
+    align-items: start;
+    margin-bottom: 4rem;
+}
+
+.workflow-step {
+    display: flex;
+    flex-direction: column;
+    gap: 1rem;
+}
+
+.step-title {
+    font-size: 1.25rem;
+    font-weight: 600;
+    color: #FFFFFF;
+    text-align: center;
+    margin-bottom: 1rem;
+}
+
+.workflow-arrow {
+    font-size: 2rem;
+    font-weight: 700;
+    color: #09b5a5;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    margin-top: 20rem;
+}
+
+/* Request Box */
+.request-box {
+    border: 2px solid #333;
+    border-radius: 8px;
+    padding: 2rem;
+    background: #111111;
+}
+
+.input-group {
+    margin-bottom: 1.5rem;
+}
+
+.input-group label {
+    display: block;
+    font-family: 'Courier New', monospace;
+    font-weight: 600;
+    color: #FFFFFF;
+    margin-bottom: 0.5rem;
+    font-size: 0.9rem;
+}
+
+.input-group input,
+.input-group textarea,
+.input-group select {
+    width: 100%;
+    padding: 0.75rem;
+    border: 1px solid #333;
+    border-radius: 4px;
+    font-family: 'Courier New', monospace;
+    font-size: 0.9rem;
+    background: #1A1A1A;
+    color: #FFFFFF;
+    transition: border-color 0.2s ease;
+}
+
+.input-group input:focus,
+.input-group textarea:focus,
+.input-group select:focus {
+    outline: none;
+    border-color: #09b5a5;
+}
+
+.input-group textarea {
+    min-height: 80px;
+    resize: vertical;
+}
+
+.form-options {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    gap: 1rem;
+    margin-bottom: 1.5rem;
+}
+
+.option-group {
+    display: flex;
+    flex-direction: column;
+    gap: 0.5rem;
+}
+
+.option-group label {
+    font-family: 'Courier New', monospace;
+    font-weight: 600;
+    color: #FFFFFF;
+    font-size: 0.9rem;
+}
+
+.option-group input[type="checkbox"] {
+    width: auto;
+    margin-right: 0.5rem;
+}
+
+.extract-btn {
+    width: 100%;
+    padding: 1rem;
+    background: #09b5a5;
+    color: #000000;
+    border: none;
+    border-radius: 4px;
+    font-size: 1rem;
+    font-weight: 600;
+    cursor: pointer;
+    transition: background-color 0.2s ease;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: 0.5rem;
+}
+
+.extract-btn:hover {
+    background: #09b5a5;
+}
+
+/* Dropdown specific styling */
+select,
+.input-group select,
+.option-group select {
+    cursor: pointer !important;
+    appearance: none !important;
+    -webkit-appearance: none !important;
+    -moz-appearance: none !important;
+    -ms-appearance: none !important;
+    background-image: url("data:image/svg+xml;charset=UTF-8,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='none' stroke='%23FFFFFF' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3e%3cpolyline points='6,9 12,15 18,9'%3e%3c/polyline%3e%3c/svg%3e") !important;
+    background-repeat: no-repeat !important;
+    background-position: right 0.75rem center !important;
+    background-size: 1rem !important;
+    padding-right: 2.5rem !important;
+    border: 1px solid #333 !important;
+    border-radius: 4px !important;
+    font-family: 'Courier New', monospace !important;
+    font-size: 0.9rem !important;
+    background-color: #1A1A1A !important;
+    color: #FFFFFF !important;
+}
+
+select:hover,
+.input-group select:hover,
+.option-group select:hover {
+    border-color: #09b5a5 !important;
+}
+
+select:focus,
+.input-group select:focus,
+.option-group select:focus {
+    outline: none !important;
+    border-color: #09b5a5 !important;
+}
+
+select option,
+.input-group select option,
+.option-group select option {
+    background: #1A1A1A !important;
+    color: #FFFFFF !important;
+    padding: 0.5rem !important;
+}
+
+/* Response Container */
+.response-container {
+    display: flex;
+    flex-direction: column;
+    gap: 1rem;
+}
+
+.api-request-box,
+.json-response-box {
+    border: 2px solid #333;
+    border-radius: 8px;
+    padding: 1.5rem;
+    background: #111111;
+}
+
+.api-request-box label,
+.json-response-box label {
+    display: block;
+    font-family: 'Courier New', monospace;
+    font-weight: 600;
+    color: #FFFFFF;
+    margin-bottom: 0.5rem;
+    font-size: 0.9rem;
+}
+
+.api-request-box pre,
+.json-response-box pre {
+    font-family: 'Courier New', monospace;
+    font-size: 0.85rem;
+    line-height: 1.5;
+    color: #FFFFFF;
+    background: #1A1A1A;
+    padding: 1rem;
+    border-radius: 4px;
+    overflow-x: auto;
+    white-space: pre-wrap;
+    word-break: break-all;
+}
+
+/* Results Section */
+.results-section {
+    border: 2px solid #333;
+    border-radius: 8px;
+    overflow: hidden;
+    margin-top: 2rem;
+    background: #111111;
+}
+
+.results-header {
+    background: #1A1A1A;
+    color: #FFFFFF;
+    padding: 1rem 1.5rem;
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    border-bottom: 1px solid #333;
+}
+
+.results-header h2 {
+    font-size: 1.25rem;
+    font-weight: 600;
+    color: #FFFFFF;
+}
+
+.copy-btn {
+    background: #09b5a5;
+    color: #000000;
+    border: none;
+    padding: 0.5rem 1rem;
+    border-radius: 4px;
+    font-size: 0.9rem;
+    font-weight: 600;
+    cursor: pointer;
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    transition: background-color 0.2s ease;
+}
+
+.copy-btn:hover {
+    background: #09b5a5;
+}
+
+.results-content {
+    padding: 1.5rem;
+}
+
+.result-info {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
+    gap: 1rem;
+    margin-bottom: 1.5rem;
+    padding: 1rem;
+    background: #1A1A1A;
+    border-radius: 4px;
+    border: 1px solid #333;
+}
+
+.info-item {
+    display: flex;
+    flex-direction: column;
+    gap: 0.25rem;
+}
+
+.info-item .label {
+    font-weight: 600;
+    color: #FFFFFF;
+    font-size: 0.9rem;
+}
+
+.info-item .value {
+    color: #CCCCCC;
+    word-break: break-all;
+}
+
+.json-display {
+    background: #1A1A1A;
+    border-radius: 4px;
+    overflow: hidden;
+    border: 1px solid #333;
+}
+
+.json-display pre {
+    color: #FFFFFF;
+    padding: 1.5rem;
+    margin: 0;
+    overflow-x: auto;
+    font-family: 'Courier New', monospace;
+    font-size: 0.9rem;
+    line-height: 1.5;
+}
+
+/* Loading State */
+.loading {
+    text-align: center;
+    padding: 3rem;
+}
+
+.spinner {
+    width: 40px;
+    height: 40px;
+    border: 3px solid #333;
+    border-top: 3px solid #09b5a5;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
+    margin: 0 auto 1rem;
+}
+
+@keyframes spin {
+    0% { transform: rotate(0deg); }
+    100% { transform: rotate(360deg); }
+}
+
+/* Models Page */
+.models-header {
+    text-align: center;
+    margin-bottom: 3rem;
+}
+
+.models-header h1 {
+    font-size: 2.5rem;
+    font-weight: 700;
+    color: #FFFFFF;
+    margin-bottom: 1rem;
+}
+
+.models-header p {
+    font-size: 1.1rem;
+    color: #CCCCCC;
+}
+
+/* API Requests Page */
+.requests-header {
+    text-align: center;
+    margin-bottom: 3rem;
+}
+
+.requests-header h1 {
+    font-size: 2.5rem;
+    font-weight: 700;
+    color: #FFFFFF;
+    margin-bottom: 1rem;
+}
+
+.requests-header p {
+    font-size: 1.1rem;
+    color: #CCCCCC;
+}
+
+.requests-container {
+    max-width: 1200px;
+    margin: 0 auto;
+}
+
+.requests-list {
+    display: grid;
+    gap: 1.5rem;
+}
+
+.request-card {
+    border: 2px solid #333;
+    border-radius: 8px;
+    padding: 1.5rem;
+    background: #111111;
+    transition: border-color 0.2s ease;
+}
+
+.request-card:hover {
+    border-color: #09b5a5;
+}
+
+.request-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    margin-bottom: 1rem;
+    padding-bottom: 1rem;
+    border-bottom: 1px solid #333;
+}
+
+.request-info {
+    display: flex;
+    flex-direction: column;
+    gap: 0.5rem;
+}
+
+.request-url {
+    font-family: 'Courier New', monospace;
+    font-weight: 600;
+    color: #09b5a5;
+    font-size: 1.1rem;
+    word-break: break-all;
+}
+
+.request-query {
+    color: #CCCCCC;
+    font-size: 0.9rem;
+    margin-top: 0.5rem;
+    word-break: break-all;
+}
+
+.request-actions {
+    display: flex;
+    gap: 0.5rem;
+}
+
+.request-curl {
+    background: #1A1A1A;
+    border: 1px solid #333;
+    border-radius: 4px;
+    padding: 1rem;
+    margin-top: 1rem;
+}
+
+.request-curl h4 {
+    color: #FFFFFF;
+    font-size: 0.9rem;
+    font-weight: 600;
+    margin-bottom: 0.5rem;
+    font-family: 'Courier New', monospace;
+}
+
+.request-curl pre {
+    color: #CCCCCC;
+    font-size: 0.8rem;
+    line-height: 1.4;
+    overflow-x: auto;
+    white-space: pre-wrap;
+    word-break: break-all;
+    background: #111111;
+    padding: 0.75rem;
+    border-radius: 4px;
+    border: 1px solid #333;
+}
+
+.models-container {
+    max-width: 800px;
+    margin: 0 auto;
+}
+
+.model-form-section {
+    border: 2px solid #333;
+    border-radius: 8px;
+    padding: 2rem;
+    margin-bottom: 2rem;
+    background: #111111;
+}
+
+.model-form-section h3 {
+    font-size: 1.25rem;
+    font-weight: 600;
+    color: #FFFFFF;
+    margin-bottom: 1.5rem;
+}
+
+.model-form {
+    display: flex;
+    flex-direction: column;
+    gap: 1.5rem;
+}
+
+.form-row {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    gap: 1rem;
+}
+
+.save-btn {
+    padding: 1rem;
+    background: #09b5a5;
+    color: #000000;
+    border: none;
+    border-radius: 4px;
+    font-size: 1rem;
+    font-weight: 600;
+    cursor: pointer;
+    transition: background-color 0.2s ease;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: 0.5rem;
+}
+
+.save-btn:hover {
+    background: #09b5a5;
+}
+
+.saved-models-section h3 {
+    font-size: 1.25rem;
+    font-weight: 600;
+    color: #FFFFFF;
+    margin-bottom: 1.5rem;
+}
+
+.models-list {
+    display: grid;
+    gap: 1rem;
+}
+
+.model-card {
+    border: 2px solid #333;
+    border-radius: 8px;
+    padding: 1.5rem;
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    transition: border-color 0.2s ease;
+    background: #111111;
+}
+
+.model-card:hover {
+    border-color: #09b5a5;
+}
+
+.model-info {
+    flex: 1;
+}
+
+.model-name {
+    font-weight: 600;
+    color: #FFFFFF;
+    font-size: 1.1rem;
+    margin-bottom: 0.5rem;
+}
+
+.model-provider {
+    color: #CCCCCC;
+    font-size: 0.9rem;
+}
+
+.model-actions {
+    display: flex;
+    gap: 0.5rem;
+}
+
+.btn-danger {
+    background: #FF4444;
+    color: #FFFFFF;
+    border: none;
+    padding: 0.5rem 1rem;
+    border-radius: 4px;
+    font-size: 0.9rem;
+    font-weight: 600;
+    cursor: pointer;
+    transition: background-color 0.2s ease;
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+}
+
+.btn-danger:hover {
+    background: #CC3333;
+}
+
+
+
+/* Toast Notifications */
+.toast-container {
+    position: fixed;
+    top: 20px;
+    right: 20px;
+    z-index: 1000;
+}
+
+.toast {
+    background: #111111;
+    border: 2px solid #333;
+    border-radius: 4px;
+    padding: 1rem 1.5rem;
+    margin-bottom: 0.5rem;
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    animation: slideIn 0.3s ease;
+    max-width: 400px;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
+    color: #FFFFFF;
+}
+
+.toast.success {
+    border-color: #09b5a5;
+    background: #0A1A1A;
+}
+
+.toast.error {
+    border-color: #FF4444;
+    background: #1A0A0A;
+}
+
+.toast.info {
+    border-color: #09b5a5;
+    background: #0A1A1A;
+}
+
+@keyframes slideIn {
+    from {
+        transform: translateX(100%);
+        opacity: 0;
+    }
+    to {
+        transform: translateX(0);
+        opacity: 1;
+    }
+}
+
+/* Responsive Design */
+@media (max-width: 768px) {
+    .header-content {
+        padding: 0 1rem;
+    }
+    
+    .main-content {
+        padding: 1rem;
+    }
+    
+    .hero-title {
+        font-size: 2rem;
+    }
+    
+    .workflow-demo {
+        grid-template-columns: 1fr;
+        gap: 1rem;
+    }
+    
+    .workflow-arrow {
+        transform: rotate(90deg);
+        margin: 1rem 0;
+    }
+    
+    .form-options {
+        grid-template-columns: 1fr;
+    }
+    
+    .form-row {
+        grid-template-columns: 1fr;
+    }
+    
+    .result-info {
+        grid-template-columns: 1fr;
+    }
+    
+    .model-card {
+        flex-direction: column;
+        gap: 1rem;
+        text-align: center;
+    }
+    
+    .model-actions {
+        width: 100%;
+        justify-content: center;
+    }
+}

docs/examples/website-to-api/test_api.py

@@ -0,0 +1,28 @@
+import asyncio
+from web_scraper_lib import scrape_website
+import os
+
+async def test_library():
+    """Test the mini library directly."""
+    print("=== Testing Mini Library ===")
+    
+    # Test 1: Scrape with a custom model
+    url = "https://marketplace.mainstreet.co.in/collections/adidas-yeezy/products/adidas-yeezy-boost-350-v2-yecheil-non-reflective"
+    query = "Extract the following data: Product name, Product price, Product description, Product size. DO NOT EXTRACT ANYTHING ELSE."
+    if os.path.exists("models"):
+        model_name = os.listdir("models")[0].split(".")[0]
+    else:
+        raise Exception("No models found in models directory")
+
+    print(f"Scraping: {url}")
+    print(f"Query: {query}")
+    
+    try:
+        result = await scrape_website(url, query, model_name)
+        print("✅ Library test successful!")
+        print(f"Extracted data: {result['extracted_data']}")
+    except Exception as e:
+        print(f"❌ Library test failed: {e}")
+
+if __name__ == "__main__":
+    asyncio.run(test_library())

docs/examples/website-to-api/test_models.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""
+Test script for the new model management functionality.
+This script demonstrates how to save and use custom model configurations.
+"""
+
+import asyncio
+import requests
+import json
+
+# API base URL
+BASE_URL = "http://localhost:8000"
+
+def test_model_management():
+    """Test the model management endpoints."""
+    
+    print("=== Testing Model Management ===")
+    
+    # 1. List current models
+    print("\n1. Listing current models:")
+    response = requests.get(f"{BASE_URL}/models")
+    print(f"Status: {response.status_code}")
+    print(f"Response: {json.dumps(response.json(), indent=2)}")
+    
+    
+    # 2. Save another model configuration (OpenAI example)
+    print("\n2. Saving OpenAI model configuration:")
+    openai_config = {
+        "model_name": "my-openai",
+        "provider": "openai",
+        "api_token": "your-openai-api-key-here"
+    }
+    
+    response = requests.post(f"{BASE_URL}/models", json=openai_config)
+    print(f"Status: {response.status_code}")
+    print(f"Response: {json.dumps(response.json(), indent=2)}")
+    
+    # 3. List models again to see the new ones
+    print("\n3. Listing models after adding new ones:")
+    response = requests.get(f"{BASE_URL}/models")
+    print(f"Status: {response.status_code}")
+    print(f"Response: {json.dumps(response.json(), indent=2)}")
+
+    # 4. Delete a model configuration
+    print("\n4. Deleting a model configuration:")
+    response = requests.delete(f"{BASE_URL}/models/my-openai")
+    print(f"Status: {response.status_code}")
+    print(f"Response: {json.dumps(response.json(), indent=2)}")
+    
+    # 5. Final list of models
+    print("\n5. Final list of models:")
+    response = requests.get(f"{BASE_URL}/models")
+    print(f"Status: {response.status_code}")
+    print(f"Response: {json.dumps(response.json(), indent=2)}")
+
+if __name__ == "__main__":
+    print("Model Management Test Script")
+    print("Make sure the API server is running on http://localhost:8000")
+    print("=" * 50)
+    
+    try:
+        test_model_management()
+    except requests.exceptions.ConnectionError:
+        print("Error: Could not connect to the API server.")
+        print("Make sure the server is running with: python api_server.py")
+    except Exception as e:
+        print(f"Error: {e}") 

docs/examples/website-to-api/web_scraper_lib.py

@@ -0,0 +1,397 @@
+from crawl4ai import (
+    AsyncWebCrawler,
+    BrowserConfig,
+    CacheMode,
+    CrawlerRunConfig,
+    LLMConfig,
+    JsonCssExtractionStrategy,
+    LLMExtractionStrategy
+)
+import os
+import json
+import hashlib
+from typing import Dict, Any, Optional, List
+from litellm import completion
+
+class ModelConfig:
+    """Configuration for LLM models."""
+    
+    def __init__(self, provider: str, api_token: str):
+        self.provider = provider
+        self.api_token = api_token
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "provider": self.provider,
+            "api_token": self.api_token
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> 'ModelConfig':
+        return cls(
+            provider=data["provider"],
+            api_token=data["api_token"]
+        )
+
+class WebScraperAgent:
+    """
+    A mini library that converts any website into a structured data API.
+    
+    Features:
+    1. Provide a URL and tell AI what data you need in plain English
+    2. Generate: Agent reverse-engineers the site and deploys custom scraper
+    3. Integrate: Use private API endpoint to get structured data
+    4. Support for custom LLM models and API keys
+    """
+    
+    def __init__(self, schemas_dir: str = "schemas", models_dir: str = "models"):
+        self.schemas_dir = schemas_dir
+        self.models_dir = models_dir
+        os.makedirs(self.schemas_dir, exist_ok=True)
+        os.makedirs(self.models_dir, exist_ok=True)
+    
+    def _generate_schema_key(self, url: str, query: str) -> str:
+        """Generate a unique key for schema caching based on URL and query."""
+        content = f"{url}:{query}"
+        return hashlib.md5(content.encode()).hexdigest()
+    
+    def save_model_config(self, model_name: str, provider: str, api_token: str) -> bool:
+        """
+        Save a model configuration for later use.
+        
+        Args:
+            model_name: User-friendly name for the model
+            provider: LLM provider (e.g., 'gemini', 'openai', 'anthropic')
+            api_token: API token for the provider
+            
+        Returns:
+            True if saved successfully
+        """
+        try:
+            model_config = ModelConfig(provider, api_token)
+            config_path = os.path.join(self.models_dir, f"{model_name}.json")
+            
+            with open(config_path, "w") as f:
+                json.dump(model_config.to_dict(), f, indent=2)
+            
+            print(f"Model configuration saved: {model_name}")
+            return True
+        except Exception as e:
+            print(f"Failed to save model configuration: {e}")
+            return False
+    
+    def load_model_config(self, model_name: str) -> Optional[ModelConfig]:
+        """
+        Load a saved model configuration.
+        
+        Args:
+            model_name: Name of the saved model configuration
+            
+        Returns:
+            ModelConfig object or None if not found
+        """
+        try:
+            config_path = os.path.join(self.models_dir, f"{model_name}.json")
+            if not os.path.exists(config_path):
+                return None
+            
+            with open(config_path, "r") as f:
+                data = json.load(f)
+            
+            return ModelConfig.from_dict(data)
+        except Exception as e:
+            print(f"Failed to load model configuration: {e}")
+            return None
+    
+    def list_saved_models(self) -> List[str]:
+        """List all saved model configurations."""
+        models = []
+        for filename in os.listdir(self.models_dir):
+            if filename.endswith('.json'):
+                models.append(filename[:-5])  # Remove .json extension
+        return models
+    
+    def delete_model_config(self, model_name: str) -> bool:
+        """
+        Delete a saved model configuration.
+        
+        Args:
+            model_name: Name of the model configuration to delete
+            
+        Returns:
+            True if deleted successfully
+        """
+        try:
+            config_path = os.path.join(self.models_dir, f"{model_name}.json")
+            if os.path.exists(config_path):
+                os.remove(config_path)
+                print(f"Model configuration deleted: {model_name}")
+                return True
+            return False
+        except Exception as e:
+            print(f"Failed to delete model configuration: {e}")
+            return False
+    
+    async def _load_or_generate_schema(self, url: str, query: str, session_id: str = "schema_generator", model_name: Optional[str] = None) -> Dict[str, Any]:
+        """
+        Loads schema from cache if exists, otherwise generates using AI.
+        This is the "Generate" step - our agent reverse-engineers the site.
+        
+        Args:
+            url: URL to scrape
+            query: Query for data extraction
+            session_id: Session identifier
+            model_name: Name of saved model configuration to use
+        """
+        schema_key = self._generate_schema_key(url, query)
+        schema_path = os.path.join(self.schemas_dir, f"{schema_key}.json")
+        
+        if os.path.exists(schema_path):
+            print(f"Schema found in cache for {url}")
+            with open(schema_path, "r") as f:
+                return json.load(f)
+        
+        print(f"Generating new schema for {url}")
+        print(f"Query: {query}")
+        query += """
+        IMPORTANT:
+        GENERATE THE SCHEMA WITH ONLY THE FIELDS MENTIONED IN THE QUERY. MAKE SURE THE NUMBER OF FIELDS IN THE SCHEME MATCH THE NUMBER OF FIELDS IN THE QUERY.
+        """
+        
+        # Step 1: Fetch the page HTML
+        async with AsyncWebCrawler(config=BrowserConfig(headless=True)) as crawler:
+            result = await crawler.arun(
+                url=url,
+                config=CrawlerRunConfig(
+                    cache_mode=CacheMode.BYPASS,
+                    session_id=session_id,
+                    simulate_user=True,
+                    remove_overlay_elements=True,
+                    delay_before_return_html=5,
+                )
+            )
+            html = result.fit_html
+        
+        # Step 2: Generate schema using AI with custom model if specified
+        print("AI is analyzing the page structure...")
+        
+        # Use custom model configuration if provided
+        if model_name:
+            model_config = self.load_model_config(model_name)
+            if model_config:
+                llm_config = LLMConfig(
+                    provider=model_config.provider,
+                    api_token=model_config.api_token
+                )
+                print(f"Using custom model: {model_name}")
+            else:
+                raise ValueError(f"Model configuration '{model_name}' not found. Please add it from the Models page.")
+        else:
+            # Require a model to be specified
+            raise ValueError("No model specified. Please select a model from the dropdown or add one from the Models page.")
+        
+        schema = JsonCssExtractionStrategy.generate_schema(
+            html=html,
+            llm_config=llm_config,
+            query=query
+        )
+        
+        # Step 3: Cache the generated schema
+        print(f"Schema generated and cached: {json.dumps(schema, indent=2)}")
+        with open(schema_path, "w") as f:
+            json.dump(schema, f, indent=2)
+        
+        return schema
+    
+    def _generate_llm_schema(self, query: str, llm_config: LLMConfig) -> Dict[str, Any]:
+        """
+        Generate a schema for a given query using a custom LLM model.
+        
+        Args:
+            query: Plain English description of what data to extract
+            model_config: Model configuration to use
+        """
+        # ask the model to generate a schema for the given query in the form of a json.
+        prompt = f"""
+        IDENTIFY THE FIELDS FOR EXTRACTION MENTIONED IN THE QUERY and GENERATE A JSON SCHEMA FOR THE FIELDS.
+        eg.
+        {{
+            "name": "str",  
+            "age": "str",
+            "email": "str",
+            "product_name": "str",
+            "product_price": "str",
+            "product_description": "str",
+            "product_image": "str",
+            "product_url": "str",
+            "product_rating": "str",
+            "product_reviews": "str",
+        }}
+        Here is the query:
+        {query}
+        IMPORTANT:
+        THE RESULT SHOULD BE A JSON OBJECT.
+        MAKE SURE THE NUMBER OF FIELDS IN THE RESULT MATCH THE NUMBER OF FIELDS IN THE QUERY.
+        THE RESULT SHOULD BE A JSON OBJECT.
+        """
+        response = completion(
+            model=llm_config.provider,
+            messages=[{"role": "user", "content": prompt}],
+            api_key=llm_config.api_token,
+            result_type="json"
+        )
+
+        return response.json()["choices"][0]["message"]["content"]
+    async def scrape_data_with_llm(self, url: str, query: str, model_name: Optional[str] = None) -> Dict[str, Any]:
+        """
+        Scrape structured data from any website using a custom LLM model.
+        
+        Args:
+            url: The website URL to scrape
+            query: Plain English description of what data to extract
+            model_name: Name of saved model configuration to use
+        """
+
+        if model_name:
+            model_config = self.load_model_config(model_name)
+            if model_config:
+                llm_config = LLMConfig(
+                    provider=model_config.provider,
+                    api_token=model_config.api_token
+                )
+                print(f"Using custom model: {model_name}")
+            else:
+                raise ValueError(f"Model configuration '{model_name}' not found. Please add it from the Models page.")
+        else:
+            # Require a model to be specified
+            raise ValueError("No model specified. Please select a model from the dropdown or add one from the Models page.")
+
+        query += """\n  
+        IMPORTANT:
+        THE RESULT SHOULD BE A JSON OBJECT WITH THE ONLY THE FIELDS MENTIONED IN THE QUERY.
+        MAKE SURE THE NUMBER OF FIELDS IN THE RESULT MATCH THE NUMBER OF FIELDS IN THE QUERY.
+        THE RESULT SHOULD BE A JSON OBJECT.
+        """
+
+        schema = self._generate_llm_schema(query, llm_config)
+
+        print(f"Schema: {schema}")
+
+        llm_extraction_strategy = LLMExtractionStrategy(
+            llm_config=llm_config,
+            instruction=query,
+            result_type="json",
+            schema=schema
+        )
+
+        async with AsyncWebCrawler() as crawler:
+            result = await crawler.arun(
+                url=url,
+                config=CrawlerRunConfig(
+                    cache_mode=CacheMode.BYPASS,
+                    simulate_user=True,
+                    extraction_strategy=llm_extraction_strategy,
+                )
+            )
+        extracted_data = result.extracted_content
+        if isinstance(extracted_data, str):
+                try:
+                    extracted_data = json.loads(extracted_data)
+                except json.JSONDecodeError:
+                    # If it's not valid JSON, keep it as string
+                    pass
+            
+        return {
+                "url": url,
+                "query": query,
+                "extracted_data": extracted_data,
+                "timestamp": result.timestamp if hasattr(result, 'timestamp') else None
+            }
+        
+    async def scrape_data(self, url: str, query: str, model_name: Optional[str] = None) -> Dict[str, Any]:
+        """
+        Main method to scrape structured data from any website.
+        
+        Args:
+            url: The website URL to scrape
+            query: Plain English description of what data to extract
+            model_name: Name of saved model configuration to use
+            
+        Returns:
+            Structured data extracted from the website
+        """
+        # Step 1: Generate or load schema (reverse-engineer the site)
+        schema = await self._load_or_generate_schema(url=url, query=query, model_name=model_name)
+        
+        # Step 2: Deploy custom high-speed scraper
+        print(f"Deploying custom scraper for {url}")
+        browser_config = BrowserConfig(headless=True)
+        
+        async with AsyncWebCrawler(config=browser_config) as crawler:
+            run_config = CrawlerRunConfig(
+                extraction_strategy=JsonCssExtractionStrategy(schema=schema),
+            )
+            result = await crawler.arun(url=url, config=run_config)
+            
+            # Step 3: Return structured data
+            # Parse extracted_content if it's a JSON string
+            extracted_data = result.extracted_content
+            if isinstance(extracted_data, str):
+                try:
+                    extracted_data = json.loads(extracted_data)
+                except json.JSONDecodeError:
+                    # If it's not valid JSON, keep it as string
+                    pass
+            
+            return {
+                "url": url,
+                "query": query,
+                "extracted_data": extracted_data,
+                "schema_used": schema,
+                "timestamp": result.timestamp if hasattr(result, 'timestamp') else None
+            }
+    
+    async def get_cached_schemas(self) -> Dict[str, str]:
+        """Get list of cached schemas."""
+        schemas = {}
+        for filename in os.listdir(self.schemas_dir):
+            if filename.endswith('.json'):
+                schema_key = filename[:-5]  # Remove .json extension
+                schemas[schema_key] = filename
+        return schemas
+    
+    def clear_cache(self):
+        """Clear all cached schemas."""
+        import shutil
+        if os.path.exists(self.schemas_dir):
+            shutil.rmtree(self.schemas_dir)
+        os.makedirs(self.schemas_dir, exist_ok=True)
+        print("Schema cache cleared")
+
+# Convenience function for simple usage
+async def scrape_website(url: str, query: str, model_name: Optional[str] = None) -> Dict[str, Any]:
+    """
+    Simple function to scrape any website with plain English instructions.
+    
+    Args:
+        url: Website URL
+        query: Plain English description of what data to extract
+        model_name: Name of saved model configuration to use
+        
+    Returns:
+        Extracted structured data
+    """
+    agent = WebScraperAgent()
+    return await agent.scrape_data(url, query, model_name)
+
+async def scrape_website_with_llm(url: str, query: str, model_name: Optional[str] = None):
+    """
+    Scrape structured data from any website using a custom LLM model.
+    
+    Args:
+        url: The website URL to scrape
+        query: Plain English description of what data to extract
+        model_name: Name of saved model configuration to use
+    """
+    agent = WebScraperAgent()
+    return await agent.scrape_data_with_llm(url, query, model_name)

docs/md_v2/advanced/adaptive-strategies.md

@@ -126,30 +126,6 @@ Factors:
 - URL depth (fewer slashes = higher authority)
 - Clean URL structure
 
-### Custom Link Scoring
-
-```python
-class CustomLinkScorer:
-    def score(self, link: Link, query: str, state: CrawlState) -> float:
-        # Prioritize specific URL patterns
-        if "/api/reference/" in link.href:
-            return 2.0  # Double the score
-        
-        # Deprioritize certain sections
-        if "/archive/" in link.href:
-            return 0.1  # Reduce score by 90%
-        
-        # Default scoring
-        return 1.0
-
-# Use with adaptive crawler
-adaptive = AdaptiveCrawler(
-    crawler,
-    config=config,
-    link_scorer=CustomLinkScorer()
-)
-```
-
 ## Domain-Specific Configurations
 
 ### Technical Documentation
@@ -230,8 +206,12 @@ config = AdaptiveConfig(
 
 # Periodically clean state
 if len(state.knowledge_base) > 1000:
-    # Keep only most relevant
-    state.knowledge_base = get_top_relevant(state.knowledge_base, 500)
+    # Keep only the top 500 most relevant docs
+    top_content = adaptive.get_relevant_content(top_k=500)
+    keep_indices = {d["index"] for d in top_content}
+    state.knowledge_base = [
+        doc for i, doc in enumerate(state.knowledge_base) if i in keep_indices
+    ]
 ```
 
 ### Parallel Processing
@@ -252,18 +232,6 @@ tasks = [
 results = await asyncio.gather(*tasks)
 ```
 
-### Caching Strategy
-
-```python
-# Enable caching for repeated crawls
-async with AsyncWebCrawler(
-    config=BrowserConfig(
-        cache_mode=CacheMode.ENABLED
-    )
-) as crawler:
-    adaptive = AdaptiveCrawler(crawler, config)
-```
-
 ## Debugging & Analysis
 
 ### Enable Verbose Logging
@@ -322,9 +290,9 @@ with open("crawl_analysis.json", "w") as f:
 ### Implementing a Custom Strategy
 
 ```python
-from crawl4ai.adaptive_crawler import BaseStrategy
+from crawl4ai.adaptive_crawler import CrawlStrategy
 
-class DomainSpecificStrategy(BaseStrategy):
+class DomainSpecificStrategy(CrawlStrategy):
     def calculate_coverage(self, state: CrawlState) -> float:
         # Custom coverage calculation
         # e.g., weight certain terms more heavily
@@ -351,7 +319,7 @@ adaptive = AdaptiveCrawler(
 ### Combining Strategies
 
 ```python
-class HybridStrategy(BaseStrategy):
+class HybridStrategy(CrawlStrategy):
     def __init__(self):
         self.strategies = [
             TechnicalDocStrategy(),

docs/md_v2/advanced/proxy-security.md

@@ -7,13 +7,13 @@ Simple proxy configuration with `BrowserConfig`:
 ```python
 from crawl4ai.async_configs import BrowserConfig
 
-# Using proxy URL
-browser_config = BrowserConfig(proxy="http://proxy.example.com:8080")
+# Using HTTP proxy
+browser_config = BrowserConfig(proxy_config={"server": "http://proxy.example.com:8080"})
 async with AsyncWebCrawler(config=browser_config) as crawler:
     result = await crawler.arun(url="https://example.com")
 
 # Using SOCKS proxy
-browser_config = BrowserConfig(proxy="socks5://proxy.example.com:1080")
+browser_config = BrowserConfig(proxy_config={"server": "socks5://proxy.example.com:1080"})
 async with AsyncWebCrawler(config=browser_config) as crawler:
     result = await crawler.arun(url="https://example.com")
 ```
@@ -25,7 +25,11 @@ Use an authenticated proxy with `BrowserConfig`:
 ```python
 from crawl4ai.async_configs import BrowserConfig
 
-browser_config = BrowserConfig(proxy="http://[username]:[password]@[host]:[port]")
+browser_config = BrowserConfig(proxy_config={
+    "server": "http://[host]:[port]",
+    "username": "[username]",
+    "password": "[password]",
+})
 async with AsyncWebCrawler(config=browser_config) as crawler:
     result = await crawler.arun(url="https://example.com")
 ```

docs/md_v2/api/parameters.md

@@ -23,7 +23,7 @@ browser_cfg = BrowserConfig(
 | **`headless`**        | `bool` (default: `True`)               | Headless means no visible UI. `False` is handy for debugging.                                                                         |
 | **`viewport_width`**  | `int` (default: `1080`)                | Initial page width (in px). Useful for testing responsive layouts.                                                                    |
 | **`viewport_height`** | `int` (default: `600`)                 | Initial page height (in px).                                                                                                          |
-| **`proxy`**           | `str` (default: `None`)                | Single-proxy URL if you want all traffic to go through it, e.g. `"http://user:pass@proxy:8080"`.                                      |
+| **`proxy`**           | `str` (deprecated)                      | Deprecated. Use `proxy_config` instead. If set, it will be auto-converted internally. |
 | **`proxy_config`**    | `dict` (default: `None`)               | For advanced or multi-proxy needs, specify details like `{"server": "...", "username": "...", ...}`.                                  |
 | **`use_persistent_context`** | `bool` (default: `False`)       | If `True`, uses a **persistent** browser context (keep cookies, sessions across runs). Also sets `use_managed_browser=True`.          |
 | **`user_data_dir`**   | `str or None` (default: `None`)        | Directory to store user data (profiles, cookies). Must be set if you want permanent sessions.                                         |
@@ -155,6 +155,7 @@ If your page is a single-page app with repeated JS updates, set `js_only=True` i
 | **`exclude_external_links`** | `bool` (False)          | Removes all links pointing outside the current domain.                                                                      |
 | **`exclude_social_media_links`** | `bool` (False)      | Strips links specifically to social sites (like Facebook or Twitter).                                                      |
 | **`exclude_domains`**        | `list` ([])             | Provide a custom list of domains to exclude (like `["ads.com", "trackers.io"]`).                                            |
+| **`preserve_https_for_internal_links`** | `bool` (False) | If `True`, preserves HTTPS scheme for internal links even when the server redirects to HTTP. Useful for security-conscious crawling. |
 
 Use these for link-level content filtering (often to keep crawls “internal” or to remove spammy domains).
 

docs/md_v2/core/adaptive-crawling.md

@@ -108,7 +108,19 @@ config = AdaptiveConfig(
     embedding_min_confidence_threshold=0.1  # Stop if completely irrelevant
 )
 
-# With custom embedding provider (e.g., OpenAI)
+# With custom LLM provider for query expansion (recommended)
+from crawl4ai import LLMConfig
+
+config = AdaptiveConfig(
+    strategy="embedding",
+    embedding_llm_config=LLMConfig(
+        provider='openai/text-embedding-3-small',
+        api_token='your-api-key',
+        temperature=0.7
+    )
+)
+
+# Alternative: Dictionary format (backward compatible)
 config = AdaptiveConfig(
     strategy="embedding",
     embedding_llm_config={

docs/md_v2/core/deep-crawling.md

@@ -472,6 +472,17 @@ Note that for BestFirstCrawlingStrategy, score_threshold is not needed since pag
 
 5.**Balance breadth vs. depth.** Choose your strategy wisely - BFS for comprehensive coverage, DFS for deep exploration, BestFirst for focused relevance-based crawling.
 
+6.**Preserve HTTPS for security.** If crawling HTTPS sites that redirect to HTTP, use `preserve_https_for_internal_links=True` to maintain secure connections:
+
+```python
+config = CrawlerRunConfig(
+    deep_crawl_strategy=BFSDeepCrawlStrategy(max_depth=2),
+    preserve_https_for_internal_links=True  # Keep HTTPS even if server redirects to HTTP
+)
+```
+
+This is especially useful for security-conscious crawling or when dealing with sites that support both protocols.
+
 ---
 
 ## 10. Summary & Next Steps

docs/md_v2/core/docker-deployment.md

@@ -89,6 +89,16 @@ ANTHROPIC_API_KEY=your-anthropic-key
 # TOGETHER_API_KEY=your-together-key
 # MISTRAL_API_KEY=your-mistral-key
 # GEMINI_API_TOKEN=your-gemini-token
+
+# Optional: Global LLM settings
+# LLM_PROVIDER=openai/gpt-4o-mini
+# LLM_TEMPERATURE=0.7
+# LLM_BASE_URL=https://api.custom.com/v1
+
+# Optional: Provider-specific overrides
+# OPENAI_TEMPERATURE=0.5
+# OPENAI_BASE_URL=https://custom-openai.com/v1
+# ANTHROPIC_TEMPERATURE=0.3
 EOL
 ```
 > 🔑 **Note**: Keep your API keys secure! Never commit `.llm.env` to version control.
@@ -156,27 +166,43 @@ cp deploy/docker/.llm.env.example .llm.env
 
 **Flexible LLM Provider Configuration:**
 
-The Docker setup now supports flexible LLM provider configuration through three methods:
+The Docker setup now supports flexible LLM provider configuration through a hierarchical system:
 
-1. **Environment Variable** (Highest Priority): Set `LLM_PROVIDER` to override the default
-   ```bash
-   export LLM_PROVIDER="anthropic/claude-3-opus"
-   # Or in your .llm.env file:
-   # LLM_PROVIDER=anthropic/claude-3-opus
-   ```
-
-2. **API Request Parameter**: Specify provider per request
+1. **API Request Parameters** (Highest Priority): Specify per request
    ```json
    {
      "url": "https://example.com",
      "f": "llm",
-     "provider": "groq/mixtral-8x7b"
+     "provider": "groq/mixtral-8x7b",
+     "temperature": 0.7,
+     "base_url": "https://api.custom.com/v1"
    }
    ```
 
-3. **Config File Default**: Falls back to `config.yml` (default: `openai/gpt-4o-mini`)
+2. **Provider-Specific Environment Variables**: Override for specific providers
+   ```bash
+   # In your .llm.env file:
+   OPENAI_TEMPERATURE=0.5
+   OPENAI_BASE_URL=https://custom-openai.com/v1
+   ANTHROPIC_TEMPERATURE=0.3
+   ```
 
-The system automatically selects the appropriate API key based on the configured `api_key_env` in the config file.
+3. **Global Environment Variables**: Set defaults for all providers
+   ```bash
+   # In your .llm.env file:
+   LLM_PROVIDER=anthropic/claude-3-opus
+   LLM_TEMPERATURE=0.7
+   LLM_BASE_URL=https://api.proxy.com/v1
+   ```
+
+4. **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.).
+
+**Supported LLM Parameters:**
+- `provider`: LLM provider and model (e.g., "openai/gpt-4", "anthropic/claude-3-opus")
+- `temperature`: Controls randomness (0.0-2.0, lower = more focused, higher = more creative)
+- `base_url`: Custom API endpoint for proxy servers or alternative endpoints
 
 #### 3. Build and Run with Compose
 
@@ -555,6 +581,101 @@ Crucially, when sending configurations directly via JSON, they **must** follow t
 **LLM Extraction Strategy** *(Keep example, ensure schema uses type/value wrapper)*
 *(Keep Deep Crawler Example)*
 
+### LLM Configuration Examples
+
+The Docker API supports dynamic LLM configuration through multiple levels:
+
+#### Temperature Control
+
+Temperature affects the randomness of LLM responses (0.0 = deterministic, 2.0 = very creative):
+
+```python
+import requests
+
+# Low temperature for factual extraction
+response = requests.post(
+    "http://localhost:11235/md",
+    json={
+        "url": "https://example.com",
+        "f": "llm",
+        "q": "Extract all dates and numbers from this page",
+        "temperature": 0.2  # Very focused, deterministic
+    }
+)
+
+# High temperature for creative tasks
+response = requests.post(
+    "http://localhost:11235/md",
+    json={
+        "url": "https://example.com", 
+        "f": "llm",
+        "q": "Write a creative summary of this content",
+        "temperature": 1.2  # More creative, varied responses
+    }
+)
+```
+
+#### Custom API Endpoints
+
+Use custom base URLs for proxy servers or alternative API endpoints:
+
+```python
+
+# Using a local LLM server
+response = requests.post(
+    "http://localhost:11235/md",
+    json={
+        "url": "https://example.com",
+        "f": "llm",
+        "q": "Extract key information",
+        "provider": "ollama/llama2",
+        "base_url": "http://localhost:11434/v1"
+    }
+)
+```
+
+#### Dynamic Provider Selection
+
+Switch between providers based on task requirements:
+
+```python
+async def smart_extraction(url: str, content_type: str):
+    """Select provider and temperature based on content type"""
+    
+    configs = {
+        "technical": {
+            "provider": "openai/gpt-4",
+            "temperature": 0.3,
+            "query": "Extract technical specifications and code examples"
+        },
+        "creative": {
+            "provider": "anthropic/claude-3-opus",
+            "temperature": 0.9,
+            "query": "Create an engaging narrative summary"
+        },
+        "quick": {
+            "provider": "groq/mixtral-8x7b",
+            "temperature": 0.5,
+            "query": "Quick summary in bullet points"
+        }
+    }
+    
+    config = configs.get(content_type, configs["quick"])
+    
+    response = await httpx.post(
+        "http://localhost:11235/md",
+        json={
+            "url": url,
+            "f": "llm",
+            "q": config["query"],
+            "provider": config["provider"],
+            "temperature": config["temperature"]
+        }
+    )
+    
+    return response.json()
+```
+
 ### REST API Examples
 
 Update URLs to use port `11235`.
@@ -693,8 +814,8 @@ app:
 # Default LLM Configuration
 llm:
   provider: "openai/gpt-4o-mini"  # Can be overridden by LLM_PROVIDER env var
-  api_key_env: "OPENAI_API_KEY"
-  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored
+  # api_key: sk-...  # If you pass the API key directly (not recommended)
+  # temperature and base_url are controlled via environment variables or request parameters
 
 # Redis Configuration (Used by internal Redis server managed by supervisord)
 redis:

docs/md_v2/core/quickstart.md

@@ -79,7 +79,7 @@ if __name__ == "__main__":
     asyncio.run(main())
 ```
 
-> IMPORTANT: By default cache mode is set to `CacheMode.ENABLED`. So to have fresh content, you need to set it to `CacheMode.BYPASS`
+> IMPORTANT: By default cache mode is set to `CacheMode.BYPASS` to have fresh content. Set `CacheMode.ENABLED` to enable caching.
 
 We’ll explore more advanced config in later tutorials (like enabling proxies, PDF output, multi-tab sessions, etc.). For now, just note how you pass these objects to manage crawling.
 

docs/md_v2/core/telemetry.md

@@ -1,242 +0,0 @@
-# Telemetry
-
-Crawl4AI includes **opt-in telemetry** to help improve stability by capturing anonymous crash reports. No personal data or crawled content is ever collected.
-
-!!! info "Privacy First"
-    Telemetry is completely optional and respects your privacy. Only exception information is collected - no URLs, no personal data, no crawled content.
-
-## Overview
-
-- **Privacy-first**: Only exceptions and crashes are reported
-- **Opt-in by default**: You control when telemetry is enabled (except in Docker where it's on by default)
-- **No PII**: No URLs, request data, or personal information is collected
-- **Provider-agnostic**: Currently uses Sentry, but designed to support multiple backends
-
-## Installation
-
-Telemetry requires the optional Sentry SDK:
-
-```bash
-# Install with telemetry support
-pip install crawl4ai[telemetry]
-
-# Or install Sentry SDK separately
-pip install sentry-sdk>=2.0.0
-```
-
-## Environments
-
-### 1. Python Library & CLI
-
-On first exception, you'll see an interactive prompt:
-
-```
-🚨 Crawl4AI Error Detection
-==============================================================
-We noticed an error occurred. Help improve Crawl4AI by
-sending anonymous crash reports?
-
-[1] Yes, send this error only
-[2] Yes, always send errors
-[3] No, don't send
-
-Your choice (1/2/3): 
-```
-
-Control via CLI:
-```bash
-# Enable telemetry
-crwl telemetry enable
-crwl telemetry enable --email you@example.com
-
-# Disable telemetry
-crwl telemetry disable
-
-# Check status
-crwl telemetry status
-```
-
-### 2. Docker / API Server
-
-!!! warning "Default Enabled in Docker"
-    Telemetry is **enabled by default** in Docker environments to help identify container-specific issues. This is different from the CLI where it's opt-in.
-
-To disable:
-```bash
-# Via environment variable
-docker run -e CRAWL4AI_TELEMETRY=0 ...
-
-# In docker-compose.yml
-environment:
-  - CRAWL4AI_TELEMETRY=0
-```
-
-### 3. Jupyter / Google Colab
-
-In notebooks, you'll see an interactive widget (if available) or a code snippet:
-
-```python
-import crawl4ai
-
-# Enable telemetry
-crawl4ai.telemetry.enable(email="you@example.com", always=True)
-
-# Send only next error
-crawl4ai.telemetry.enable(once=True)
-
-# Disable telemetry
-crawl4ai.telemetry.disable()
-
-# Check status
-crawl4ai.telemetry.status()
-```
-
-## Python API
-
-### Basic Usage
-
-```python
-from crawl4ai import telemetry
-
-# Enable/disable telemetry
-telemetry.enable(email="optional@email.com", always=True)
-telemetry.disable()
-
-# Check current status
-status = telemetry.status()
-print(f"Telemetry enabled: {status['enabled']}")
-print(f"Consent: {status['consent']}")
-```
-
-### Manual Exception Capture
-
-```python
-from crawl4ai.telemetry import capture_exception
-
-try:
-    # Your code here
-    risky_operation()
-except Exception as e:
-    # Manually capture exception with context
-    capture_exception(e, {
-        'operation': 'custom_crawler',
-        'url': 'https://example.com'  # Will be sanitized
-    })
-    raise
-```
-
-### Decorator Pattern
-
-```python
-from crawl4ai.telemetry import telemetry_decorator
-
-@telemetry_decorator
-def my_crawler_function():
-    # Exceptions will be automatically captured
-    pass
-```
-
-### Context Manager
-
-```python
-from crawl4ai.telemetry import telemetry_context
-
-with telemetry_context("data_extraction"):
-    # Any exceptions in this block will be captured
-    result = extract_data(html)
-```
-
-## Configuration
-
-Settings are stored in `~/.crawl4ai/config.json`:
-
-```json
-{
-  "telemetry": {
-    "consent": "always",
-    "email": "user@example.com"
-  }
-}
-```
-
-Consent levels:
-- `"not_set"` - No decision made yet
-- `"denied"` - Telemetry disabled
-- `"once"` - Send current error only
-- `"always"` - Always send errors
-
-## Environment Variables
-
-- `CRAWL4AI_TELEMETRY=0` - Disable telemetry (overrides config)
-- `CRAWL4AI_TELEMETRY_EMAIL=email@example.com` - Set email for follow-up
-- `CRAWL4AI_SENTRY_DSN=https://...` - Override default DSN (for maintainers)
-
-## What's Collected
-
-### Collected ✅
-- Exception type and traceback
-- Crawl4AI version
-- Python version
-- Operating system
-- Environment type (CLI, Docker, Jupyter)
-- Optional email (if provided)
-
-### NOT Collected ❌
-- URLs being crawled
-- HTML content
-- Request/response data
-- Cookies or authentication tokens
-- IP addresses
-- Any personally identifiable information
-
-## Provider Architecture
-
-Telemetry is designed to be provider-agnostic:
-
-```python
-from crawl4ai.telemetry.base import TelemetryProvider
-
-class CustomProvider(TelemetryProvider):
-    def send_exception(self, exc, context=None):
-        # Your implementation
-        pass
-```
-
-## FAQ
-
-### Q: Can I completely disable telemetry?
-A: Yes! Use `crwl telemetry disable` or set `CRAWL4AI_TELEMETRY=0`
-
-### Q: Is telemetry required?
-A: No, it's completely optional (except enabled by default in Docker)
-
-### Q: What if I don't install sentry-sdk?
-A: Telemetry will gracefully degrade to a no-op state
-
-### Q: Can I see what's being sent?
-A: Yes, check the source code in `crawl4ai/telemetry/`
-
-### Q: How do I remove my email?
-A: Delete `~/.crawl4ai/config.json` or edit it to remove the email field
-
-## Privacy Commitment
-
-1. **Transparency**: All telemetry code is open source
-2. **Control**: You can enable/disable at any time
-3. **Minimal**: Only crash data, no user content
-4. **Secure**: Data transmitted over HTTPS to Sentry
-5. **Anonymous**: No tracking or user identification
-
-## Contributing
-
-Help improve telemetry:
-- Report issues with telemetry itself
-- Suggest privacy improvements
-- Add new provider backends
-
-## Support
-
-If you have concerns about telemetry:
-- Open an issue on GitHub
-- Email the maintainers
-- Review the code in `crawl4ai/telemetry/`

docs/md_v2/core/url-seeding.md

@@ -102,16 +102,16 @@ async def smart_blog_crawler():
     
     # Step 2: Configure discovery - let's find all blog posts
     config = SeedingConfig(
-        source="sitemap",           # Use the website's sitemap
-        pattern="*/blog/*.html",    # Only blog posts
+        source="sitemap+cc",      # Use the website's sitemap+cc
+        pattern="*/courses/*",    # Only courses related posts
         extract_head=True,          # Get page metadata
         max_urls=100               # Limit for this example
     )
     
     # Step 3: Discover URLs from the Python blog
-    print("🔍 Discovering blog posts...")
+    print("🔍 Discovering course posts...")
     urls = await seeder.urls("realpython.com", config)
-    print(f"✅ Found {len(urls)} blog posts")
+    print(f"✅ Found {len(urls)} course posts")
     
     # Step 4: Filter for Python tutorials (using metadata!)
     tutorials = [
@@ -134,7 +134,8 @@ async def smart_blog_crawler():
     async with AsyncWebCrawler() as crawler:
         config = CrawlerRunConfig(
             only_text=True,
-            word_count_threshold=300  # Only substantial articles
+            word_count_threshold=300,  # Only substantial articles
+            stream=True
         )
         
         # Extract URLs and crawl them
@@ -155,7 +156,7 @@ asyncio.run(smart_blog_crawler())
 
 **What just happened?**
 
-1. We discovered all blog URLs from the sitemap
+1. We discovered all blog URLs from the sitemap+cc
 2. We filtered using metadata (no crawling needed!)
 3. We crawled only the relevant tutorials
 4. We saved tons of time and bandwidth
@@ -282,8 +283,8 @@ config = SeedingConfig(
     live_check=True,  # Verify each URL is accessible
     concurrency=20    # Check 20 URLs in parallel
 )
-
-urls = await seeder.urls("example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("example.com", config)
 
 # Now you can filter by status
 live_urls = [u for u in urls if u["status"] == "valid"]
@@ -311,8 +312,8 @@ This is where URL seeding gets really powerful. Instead of crawling entire pages
 config = SeedingConfig(
     extract_head=True  # Extract metadata from <head> section
 )
-
-urls = await seeder.urls("example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("example.com", config)
 
 # Now each URL has rich metadata
 for url in urls[:3]:
@@ -387,8 +388,8 @@ config = SeedingConfig(
     scoring_method="bm25",
     score_threshold=0.3
 )
-
-urls = await seeder.urls("example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("example.com", config)
 
 # URLs are scored based on:
 # 1. Domain parts matching (e.g., 'python' in python.example.com)
@@ -429,8 +430,8 @@ config = SeedingConfig(
     extract_head=True,
     live_check=True
 )
-
-urls = await seeder.urls("blog.example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("blog.example.com", config)
 
 # Analyze the results
 for url in urls[:5]:
@@ -488,8 +489,8 @@ config = SeedingConfig(
     scoring_method="bm25",       # Use BM25 algorithm
     score_threshold=0.3          # Minimum relevance score
 )
-
-urls = await seeder.urls("realpython.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("realpython.com", config)
 
 # Results are automatically sorted by relevance!
 for url in urls[:5]:
@@ -511,8 +512,8 @@ config = SeedingConfig(
     score_threshold=0.5,
     max_urls=20
 )
-
-urls = await seeder.urls("docs.example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("docs.example.com", config)
 
 # The highest scoring URLs will be API docs!
 ```
@@ -529,8 +530,8 @@ config = SeedingConfig(
     score_threshold=0.4,
     pattern="*/product/*"  # Combine with pattern matching
 )
-
-urls = await seeder.urls("shop.example.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("shop.example.com", config)
 
 # Filter further by price (from metadata)
 affordable = [
@@ -550,8 +551,8 @@ config = SeedingConfig(
     scoring_method="bm25",
     score_threshold=0.35
 )
-
-urls = await seeder.urls("technews.com", config)
+async with AsyncUrlSeeder() as seeder:
+    urls = await seeder.urls("technews.com", config)
 
 # Filter by date
 from datetime import datetime, timedelta
@@ -591,8 +592,8 @@ for query in queries:
         score_threshold=0.4,
         max_urls=10  # Top 10 per topic
     )
-    
-    urls = await seeder.urls("learning-platform.com", config)
+    async with AsyncUrlSeeder() as seeder:
+        urls = await seeder.urls("learning-platform.com", config)
     all_tutorials.extend(urls)
 
 # Remove duplicates while preserving order
@@ -625,7 +626,8 @@ config = SeedingConfig(
 )
 
 # Returns a dictionary: {domain: [urls]}
-results = await seeder.many_urls(domains, config)
+async with AsyncUrlSeeder() as seeder:
+    results = await seeder.many_urls(domains, config)
 
 # Process results
 for domain, urls in results.items():
@@ -654,8 +656,8 @@ config = SeedingConfig(
     pattern="*/blog/*",
     max_urls=100
 )
-
-results = await seeder.many_urls(competitors, config)
+async with AsyncUrlSeeder() as seeder:
+    results = await seeder.many_urls(competitors, config)
 
 # Analyze content types
 for domain, urls in results.items():
@@ -690,8 +692,8 @@ config = SeedingConfig(
     score_threshold=0.3,
     max_urls=20  # Per site
 )
-
-results = await seeder.many_urls(educational_sites, config)
+async with AsyncUrlSeeder() as seeder:
+    results = await seeder.many_urls(educational_sites, config)
 
 # Find the best beginner tutorials
 all_tutorials = []
@@ -731,8 +733,8 @@ config = SeedingConfig(
     score_threshold=0.5,  # High threshold for relevance
     max_urls=10
 )
-
-results = await seeder.many_urls(news_sites, config)
+async with AsyncUrlSeeder() as seeder:
+    results = await seeder.many_urls(news_sites, config)
 
 # Collect all mentions
 mentions = []

mkdocs.yml

@@ -35,7 +35,6 @@ nav:
     - "Page Interaction": "core/page-interaction.md"
     - "Content Selection": "core/content-selection.md"
     - "Cache Modes": "core/cache-modes.md"
-    - "Telemetry": "core/telemetry.md"
     - "Local Files & Raw HTML": "core/local-files.md"
     - "Link & Media": "core/link-media.md"
   - Advanced:

pyproject.toml

@@ -7,7 +7,7 @@ name = "Crawl4AI"
 dynamic = ["version"]
 description = "🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & scraper"
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license = "Apache-2.0"
 authors = [
     {name = "Unclecode", email = "unclecode@kidocode.com"}
@@ -36,6 +36,7 @@ dependencies = [
     "PyYAML>=6.0",
     "nltk>=3.9.1",
     "rich>=13.9.4",
+    "cssselect>=1.2.0",
     "httpx>=0.27.2",
     "httpx[http2]>=0.27.2",
     "fake-useragent>=2.0.3",
@@ -51,7 +52,6 @@ classifiers = [
     "Development Status :: 4 - Beta",
     "Intended Audience :: Developers",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -64,7 +64,6 @@ torch = ["torch", "nltk", "scikit-learn"]
 transformer = ["transformers", "tokenizers", "sentence-transformers"]
 cosine = ["torch", "transformers", "nltk", "sentence-transformers"]
 sync = ["selenium"]
-telemetry = ["sentry-sdk>=2.0.0", "ipywidgets>=8.0.0"]
 all = [
     "PyPDF2",
     "torch",
@@ -73,9 +72,7 @@ all = [
     "transformers",
     "tokenizers",
     "sentence-transformers",
-    "selenium",
-    "sentry-sdk>=2.0.0",
-    "ipywidgets>=8.0.0"
+    "selenium"
 ]
 
 [project.scripts]

pytest.ini

@@ -1,16 +0,0 @@
-[pytest]
-testpaths = tests
-python_paths = .
-addopts = --maxfail=1 --disable-warnings -q --tb=short -v
-asyncio_mode = auto
-markers =
-    slow: marks tests as slow (deselect with '-m "not slow"')
-    integration: marks tests as integration tests
-    unit: marks tests as unit tests
-    privacy: marks tests related to privacy compliance
-    performance: marks tests related to performance
-filterwarnings =
-    ignore::DeprecationWarning
-    ignore::PendingDeprecationWarning
-env =
-    CRAWL4AI_TEST_MODE=1

requirements.txt

@@ -24,6 +24,7 @@ psutil>=6.1.1
 PyYAML>=6.0
 nltk>=3.9.1
 rich>=13.9.4
+cssselect>=1.2.0
 chardet>=5.2.0
 brotli>=1.1.0
 httpx[http2]>=0.27.2

setup.py

@@ -56,11 +56,10 @@ setup(
         "Development Status :: 3 - Alpha",
         "Intended Audience :: Developers",
         "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
         "Programming Language :: Python :: 3.11",
         "Programming Language :: Python :: 3.12",
         "Programming Language :: Python :: 3.13",
     ],
-    python_requires=">=3.9",
+    python_requires=">=3.10",
 )

tests/adaptive/test_llm_embedding.py

@@ -0,0 +1,154 @@
+import asyncio
+import os
+from crawl4ai import AsyncWebCrawler, AdaptiveCrawler, AdaptiveConfig, LLMConfig
+
+
+async def test_configuration(name: str, config: AdaptiveConfig, url: str, query: str):
+    """Test a specific configuration"""
+    print(f"\n{'='*60}")
+    print(f"Configuration: {name}")
+    print(f"{'='*60}")
+    
+    async with AsyncWebCrawler(verbose=False) as crawler:
+        adaptive = AdaptiveCrawler(crawler, config)
+        result = await adaptive.digest(start_url=url, query=query)
+        
+        print("\n" + "="*50)
+        print("CRAWL STATISTICS")
+        print("="*50)
+        adaptive.print_stats(detailed=False)
+        
+        # Get the most relevant content found
+        print("\n" + "="*50)
+        print("MOST RELEVANT PAGES")
+        print("="*50)
+        
+        relevant_pages = adaptive.get_relevant_content(top_k=5)
+        for i, page in enumerate(relevant_pages, 1):
+            print(f"\n{i}. {page['url']}")
+            print(f"   Relevance Score: {page['score']:.2%}")
+            
+            # Show a snippet of the content
+            content = page['content'] or ""
+            if content:
+                snippet = content[:200].replace('\n', ' ')
+                if len(content) > 200:
+                    snippet += "..."
+                print(f"   Preview: {snippet}")
+        
+        print(f"\n{'='*50}")
+        print(f"Pages crawled: {len(result.crawled_urls)}")
+        print(f"Final confidence: {adaptive.confidence:.1%}")
+        print(f"Stopped reason: {result.metrics.get('stopped_reason', 'max_pages')}")
+        
+        if result.metrics.get('is_irrelevant', False):
+            print("⚠️  Query detected as irrelevant!")
+        
+        return result
+
+
+async def llm_embedding():
+    """Demonstrate various embedding configurations"""
+    
+    print("EMBEDDING STRATEGY CONFIGURATION EXAMPLES")
+    print("=" * 60)
+    
+    # Base URL and query for testing
+    test_url = "https://docs.python.org/3/library/asyncio.html"
+    
+    openai_llm_config = LLMConfig(
+        provider='openai/text-embedding-3-small',
+        api_token=os.getenv('OPENAI_API_KEY'),
+        temperature=0.7,
+        max_tokens=2000
+    )
+    config_openai = AdaptiveConfig(
+        strategy="embedding",
+        max_pages=10,
+        
+        # Use OpenAI embeddings
+        embedding_llm_config=openai_llm_config,
+        # embedding_llm_config={
+        #     'provider': 'openai/text-embedding-3-small',
+        #     'api_token': os.getenv('OPENAI_API_KEY')
+        # },
+        
+        # OpenAI embeddings are high quality, can be stricter
+        embedding_k_exp=4.0,
+        n_query_variations=12
+    )
+    
+    await test_configuration(
+        "OpenAI Embeddings",
+        config_openai,
+        test_url,
+        # "event-driven architecture patterns"
+        "async await context managers coroutines"
+    )
+    return
+    
+    
+
+async def basic_adaptive_crawling():
+    """Basic adaptive crawling example"""
+    
+    # Initialize the crawler
+    async with AsyncWebCrawler(verbose=True) as crawler:
+        # Create an adaptive crawler with default settings (statistical strategy)
+        adaptive = AdaptiveCrawler(crawler)
+        
+        # Note: You can also use embedding strategy for semantic understanding:
+        # from crawl4ai import AdaptiveConfig
+        # config = AdaptiveConfig(strategy="embedding")
+        # adaptive = AdaptiveCrawler(crawler, config)
+        
+        # Start adaptive crawling
+        print("Starting adaptive crawl for Python async programming information...")
+        result = await adaptive.digest(
+            start_url="https://docs.python.org/3/library/asyncio.html",
+            query="async await context managers coroutines"
+        )
+        
+        # Display crawl statistics
+        print("\n" + "="*50)
+        print("CRAWL STATISTICS")
+        print("="*50)
+        adaptive.print_stats(detailed=False)
+        
+        # Get the most relevant content found
+        print("\n" + "="*50)
+        print("MOST RELEVANT PAGES")
+        print("="*50)
+        
+        relevant_pages = adaptive.get_relevant_content(top_k=5)
+        for i, page in enumerate(relevant_pages, 1):
+            print(f"\n{i}. {page['url']}")
+            print(f"   Relevance Score: {page['score']:.2%}")
+            
+            # Show a snippet of the content
+            content = page['content'] or ""
+            if content:
+                snippet = content[:200].replace('\n', ' ')
+                if len(content) > 200:
+                    snippet += "..."
+                print(f"   Preview: {snippet}")
+        
+        # Show final confidence
+        print(f"\n{'='*50}")
+        print(f"Final Confidence: {adaptive.confidence:.2%}")
+        print(f"Total Pages Crawled: {len(result.crawled_urls)}")
+        print(f"Knowledge Base Size: {len(adaptive.state.knowledge_base)} documents")
+        
+        
+        if adaptive.confidence >= 0.8:
+            print("✓ High confidence - can answer detailed questions about async Python")
+        elif adaptive.confidence >= 0.6:
+            print("~ Moderate confidence - can answer basic questions") 
+        else:
+            print("✗ Low confidence - need more information")
+
+
+
+if __name__ == "__main__":
+    asyncio.run(llm_embedding())
+    # asyncio.run(basic_adaptive_crawling())

tests/async/test_0.4.2_browser_manager.py

@@ -112,7 +112,7 @@ async def test_proxy_settings():
         headless=True,
         verbose=False,
         user_agent="Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36",
-        proxy="http://127.0.0.1:8080",  # Assuming local proxy server for test
+        proxy_config={"server": "http://127.0.0.1:8080"},  # Assuming local proxy server for test
         use_managed_browser=False,
         use_persistent_context=False,
     ) as crawler:

tests/conftest.py

@@ -1,151 +0,0 @@
-"""
-Shared pytest fixtures for Crawl4AI tests.
-"""
-
-import pytest
-import tempfile
-import os
-from pathlib import Path
-from unittest.mock import Mock, patch
-from crawl4ai.telemetry.config import TelemetryConfig, TelemetryConsent
-from crawl4ai.telemetry.environment import Environment
-
-
-@pytest.fixture
-def temp_config_dir():
-    """Provide a temporary directory for telemetry config testing."""
-    with tempfile.TemporaryDirectory() as tmpdir:
-        yield Path(tmpdir)
-
-
-@pytest.fixture
-def mock_telemetry_config(temp_config_dir):
-    """Provide a mocked telemetry config for testing."""
-    config = TelemetryConfig(config_dir=temp_config_dir)
-    yield config
-
-
-@pytest.fixture
-def clean_environment():
-    """Clean environment variables before and after test."""
-    # Store original environment
-    original_env = os.environ.copy()
-    
-    # Clean telemetry-related env vars
-    telemetry_vars = [
-        'CRAWL4AI_TELEMETRY',
-        'CRAWL4AI_DOCKER', 
-        'CRAWL4AI_API_SERVER',
-        'CRAWL4AI_TEST_MODE'
-    ]
-    
-    for var in telemetry_vars:
-        if var in os.environ:
-            del os.environ[var]
-    
-    # Set test mode
-    os.environ['CRAWL4AI_TEST_MODE'] = '1'
-    
-    yield
-    
-    # Restore original environment
-    os.environ.clear()
-    os.environ.update(original_env)
-
-
-@pytest.fixture
-def mock_sentry_provider():
-    """Provide a mocked Sentry provider for testing."""
-    with patch('crawl4ai.telemetry.providers.sentry.SentryProvider') as mock:
-        provider_instance = Mock()
-        provider_instance.initialize.return_value = True
-        provider_instance.send_exception.return_value = True
-        provider_instance.is_initialized = True
-        mock.return_value = provider_instance
-        yield provider_instance
-
-
-@pytest.fixture
-def enabled_telemetry_config(temp_config_dir):  # noqa: F811
-    """Provide a telemetry config with telemetry enabled."""
-    config = Mock()
-    config.get_consent.return_value = TelemetryConsent.ALWAYS
-    config.is_enabled.return_value = True
-    config.should_send_current.return_value = True
-    config.get_email.return_value = "test@example.com"
-    config.update_from_env.return_value = None
-    yield config
-
-
-@pytest.fixture
-def disabled_telemetry_config(temp_config_dir):  # noqa: F811
-    """Provide a telemetry config with telemetry disabled."""
-    config = Mock()
-    config.get_consent.return_value = TelemetryConsent.DENIED
-    config.is_enabled.return_value = False
-    config.should_send_current.return_value = False
-    config.update_from_env.return_value = None
-    yield config
-
-
-@pytest.fixture
-def docker_environment():
-    """Mock Docker environment detection."""
-    with patch('crawl4ai.telemetry.environment.EnvironmentDetector.detect', return_value=Environment.DOCKER):
-        yield
-
-
-@pytest.fixture
-def cli_environment():
-    """Mock CLI environment detection."""
-    with patch('crawl4ai.telemetry.environment.EnvironmentDetector.detect', return_value=Environment.CLI):
-        with patch('sys.stdin.isatty', return_value=True):
-            yield
-
-
-@pytest.fixture
-def jupyter_environment():
-    """Mock Jupyter environment detection."""
-    with patch('crawl4ai.telemetry.environment.EnvironmentDetector.detect', return_value=Environment.JUPYTER):
-        yield
-
-
-@pytest.fixture(autouse=True)
-def reset_telemetry_singleton():
-    """Reset telemetry singleton between tests."""
-    from crawl4ai.telemetry import TelemetryManager
-    # Reset the singleton instance
-    if hasattr(TelemetryManager, '_instance'):
-        TelemetryManager._instance = None  # noqa: SLF001
-    yield
-    # Clean up after test
-    if hasattr(TelemetryManager, '_instance'):
-        TelemetryManager._instance = None  # noqa: SLF001
-
-
-@pytest.fixture
-def sample_exception():
-    """Provide a sample exception for testing."""
-    try:
-        raise ValueError("Test exception for telemetry")
-    except ValueError as e:
-        return e
-
-
-@pytest.fixture
-def privacy_test_data():
-    """Provide test data that should NOT be captured by telemetry."""
-    return {
-        'url': 'https://example.com/private-page',
-        'content': 'This is private content that should not be sent',
-        'user_data': {
-            'email': 'user@private.com',
-            'password': 'secret123',
-            'api_key': 'sk-1234567890abcdef'
-        },
-        'pii': {
-            'ssn': '123-45-6789',
-            'phone': '+1-555-123-4567',
-            'address': '123 Main St, Anytown, USA'
-        }
-    }

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()))

tests/docker/test_llm_params.py

@@ -0,0 +1,349 @@
+#!/usr/bin/env python3
+"""
+Test script for LLM temperature and base_url parameters in Crawl4AI Docker API.
+This demonstrates the new hierarchical configuration system:
+1. Request-level parameters (highest priority)
+2. Provider-specific environment variables
+3. Global environment variables
+4. System defaults (lowest priority)
+"""
+
+import asyncio
+import httpx
+import json
+import os
+from rich.console import Console
+from rich.panel import Panel
+from rich.syntax import Syntax
+from rich.table import Table
+
+
+console = Console()
+
+# Configuration
+BASE_URL = "http://localhost:11235"  # Docker API endpoint
+TEST_URL = "https://httpbin.org/html"     # Simple test page
+
+# --- Helper Functions ---
+
+async def check_server_health(client: httpx.AsyncClient) -> bool:
+    """Check if the server is healthy."""
+    console.print("[bold cyan]Checking server health...[/]", end="")
+    try:
+        response = await client.get("/health", timeout=10.0)
+        response.raise_for_status()
+        console.print(" [bold green]✓ Server is healthy![/]")
+        return True
+    except Exception as e:
+        console.print(f"\n[bold red]✗ Server health check failed: {e}[/]")
+        console.print(f"Is the server running at {BASE_URL}?")
+        return False
+
+def print_request(endpoint: str, payload: dict, title: str = "Request"):
+    """Pretty print the request."""
+    syntax = Syntax(json.dumps(payload, indent=2), "json", theme="monokai")
+    console.print(Panel.fit(
+        f"[cyan]POST {endpoint}[/cyan]\n{syntax}",
+        title=f"[bold blue]{title}[/]",
+        border_style="blue"
+    ))
+
+def print_response(response: dict, title: str = "Response"):
+    """Pretty print relevant parts of the response."""
+    # Extract only the relevant parts
+    relevant = {}
+    if "markdown" in response:
+        relevant["markdown"] = response["markdown"][:200] + "..." if len(response.get("markdown", "")) > 200 else response.get("markdown", "")
+    if "success" in response:
+        relevant["success"] = response["success"]
+    if "url" in response:
+        relevant["url"] = response["url"]
+    if "filter" in response:
+        relevant["filter"] = response["filter"]
+    
+    console.print(Panel.fit(
+        Syntax(json.dumps(relevant, indent=2), "json", theme="monokai"),
+        title=f"[bold green]{title}[/]",
+        border_style="green"
+    ))
+
+# --- Test Functions ---
+
+async def test_default_no_params(client: httpx.AsyncClient):
+    """Test 1: No temperature or base_url specified - uses defaults"""
+    console.rule("[bold yellow]Test 1: Default Configuration (No Parameters)[/]")
+    
+    payload = {
+        "url": TEST_URL,
+        "f": "llm",
+        "q": "What is the main heading of this page? Answer in exactly 5 words."
+    }
+    
+    print_request("/md", payload, "Request without temperature/base_url")
+    
+    try:
+        response = await client.post("/md", json=payload, timeout=30.0)
+        response.raise_for_status()
+        data = response.json()
+        print_response(data, "Response (using system defaults)")
+        console.print("[dim]→ This used system defaults or environment variables if set[/]")
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/]")
+
+async def test_request_temperature(client: httpx.AsyncClient):
+    """Test 2: Request-level temperature (highest priority)"""
+    console.rule("[bold yellow]Test 2: Request-Level Temperature[/]")
+    
+    # Test with low temperature (more focused)
+    payload_low = {
+        "url": TEST_URL,
+        "f": "llm",
+        "q": "What is the main heading? Be creative and poetic.",
+        "temperature": 0.1  # Very low - should be less creative
+    }
+    
+    print_request("/md", payload_low, "Low Temperature (0.1)")
+    
+    try:
+        response = await client.post("/md", json=payload_low, timeout=30.0)
+        response.raise_for_status()
+        data_low = response.json()
+        print_response(data_low, "Response with Low Temperature")
+        console.print("[dim]→ Low temperature (0.1) should produce focused, less creative output[/]")
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/]")
+    
+    console.print()
+    
+    # Test with high temperature (more creative)
+    payload_high = {
+        "url": TEST_URL,
+        "f": "llm",
+        "q": "What is the main heading? Be creative and poetic.",
+        "temperature": 1.5  # High - should be more creative
+    }
+    
+    print_request("/md", payload_high, "High Temperature (1.5)")
+    
+    try:
+        response = await client.post("/md", json=payload_high, timeout=30.0)
+        response.raise_for_status()
+        data_high = response.json()
+        print_response(data_high, "Response with High Temperature")
+        console.print("[dim]→ High temperature (1.5) should produce more creative, varied output[/]")
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/]")
+
+async def test_provider_override(client: httpx.AsyncClient):
+    """Test 3: Provider override with temperature"""
+    console.rule("[bold yellow]Test 3: Provider Override with Temperature[/]")
+    
+    provider = "gemini/gemini-2.5-flash-lite"
+    payload = {
+        "url": TEST_URL,
+        "f": "llm",
+        "q": "Summarize this page in one sentence.",
+        "provider": provider,  # Explicitly set provider
+        "temperature": 0.7
+    }
+    
+    print_request("/md", payload, "Provider + Temperature Override")
+    
+    try:
+        response = await client.post("/md", json=payload, timeout=30.0)
+        response.raise_for_status()
+        data = response.json()
+        print_response(data, "Response with Provider Override")
+        console.print(f"[dim]→ This explicitly uses {provider} with temperature 0.7[/]")
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/]")
+
+async def test_base_url_custom(client: httpx.AsyncClient):
+    """Test 4: Custom base_url (will fail unless you have a custom endpoint)"""
+    console.rule("[bold yellow]Test 4: Custom Base URL (Demo Only)[/]")
+    
+    payload = {
+        "url": TEST_URL,
+        "f": "llm",
+        "q": "What is this page about?",
+        "base_url": "https://api.custom-endpoint.com/v1",  # Custom endpoint
+        "temperature": 0.5
+    }
+    
+    print_request("/md", payload, "Custom Base URL Request")
+    console.print("[yellow]Note: This will fail unless you have a custom endpoint set up[/]")
+    
+    try:
+        response = await client.post("/md", json=payload, timeout=10.0)
+        response.raise_for_status()
+        data = response.json()
+        print_response(data, "Response from Custom Endpoint")
+    except httpx.HTTPStatusError as e:
+        console.print(f"[yellow]Expected failure (no custom endpoint): Status {e.response.status_code}[/]")
+    except Exception as e:
+        console.print(f"[yellow]Expected error: {e}[/]")
+
+async def test_llm_job_endpoint(client: httpx.AsyncClient):
+    """Test 5: Test the /llm/job endpoint with temperature and base_url"""
+    console.rule("[bold yellow]Test 5: LLM Job Endpoint with Parameters[/]")
+    
+    payload = {
+        "url": TEST_URL,
+        "q": "Extract the main title and any key information",
+        "temperature": 0.3,
+        # "base_url": "https://api.openai.com/v1"  # Optional
+    }
+    
+    print_request("/llm/job", payload, "LLM Job with Temperature")
+    
+    try:
+        # Submit the job
+        response = await client.post("/llm/job", json=payload, timeout=30.0)
+        response.raise_for_status()
+        job_data = response.json()
+        
+        if "task_id" in job_data:
+            task_id = job_data["task_id"]
+            console.print(f"[green]Job created with task_id: {task_id}[/]")
+            
+            # Poll for result (simplified - in production use proper polling)
+            await asyncio.sleep(3)
+            
+            status_response = await client.get(f"/llm/job/{task_id}")
+            status_data = status_response.json()
+            
+            if status_data.get("status") == "completed":
+                console.print("[green]Job completed successfully![/]")
+                if "result" in status_data:
+                    console.print(Panel.fit(
+                        Syntax(json.dumps(status_data["result"], indent=2), "json", theme="monokai"),
+                        title="Extraction Result",
+                        border_style="green"
+                    ))
+            else:
+                console.print(f"[yellow]Job status: {status_data.get('status', 'unknown')}[/]")
+        else:
+            console.print(f"[red]Unexpected response: {job_data}[/]")
+            
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/]")
+
+
+async def test_llm_endpoint(client: httpx.AsyncClient):
+    """
+    Quick QA round-trip with /llm.
+    Asks a trivial question against SIMPLE_URL just to show wiring.
+    """
+    import time
+    import urllib.parse
+
+    page_url = "https://kidocode.com"
+    question = "What is the title of this page?"
+
+    enc = urllib.parse.quote_plus(page_url, safe="")
+    console.print(f"GET /llm/{enc}?q={question}")
+
+    try:
+        t0 = time.time()
+        resp = await client.get(f"/llm/{enc}", params={"q": question})
+        dt = time.time() - t0
+        console.print(
+            f"Response Status: [bold {'green' if resp.is_success else 'red'}]{resp.status_code}[/] (took {dt:.2f}s)")
+        resp.raise_for_status()
+        answer = resp.json().get("answer", "")
+        console.print(Panel(answer or "No answer returned",
+                      title="LLM answer", border_style="magenta", expand=False))
+    except Exception as e:
+        console.print(f"[bold red]Error hitting /llm:[/] {e}")
+
+
+async def show_environment_info():
+    """Display current environment configuration"""
+    console.rule("[bold cyan]Current Environment Configuration[/]")
+    
+    table = Table(title="LLM Environment Variables", show_header=True, header_style="bold magenta")
+    table.add_column("Variable", style="cyan", width=30)
+    table.add_column("Value", style="yellow")
+    table.add_column("Description", style="dim")
+    
+    env_vars = [
+        ("LLM_PROVIDER", "Global default provider"),
+        ("LLM_TEMPERATURE", "Global default temperature"),
+        ("LLM_BASE_URL", "Global custom API endpoint"),
+        ("OPENAI_API_KEY", "OpenAI API key"),
+        ("OPENAI_TEMPERATURE", "OpenAI-specific temperature"),
+        ("OPENAI_BASE_URL", "OpenAI-specific endpoint"),
+        ("ANTHROPIC_API_KEY", "Anthropic API key"),
+        ("ANTHROPIC_TEMPERATURE", "Anthropic-specific temperature"),
+        ("GROQ_API_KEY", "Groq API key"),
+        ("GROQ_TEMPERATURE", "Groq-specific temperature"),
+    ]
+    
+    for var, desc in env_vars:
+        value = os.environ.get(var, "[not set]")
+        if "API_KEY" in var and value != "[not set]":
+            # Mask API keys for security
+            value = value[:10] + "..." if len(value) > 10 else "***"
+        table.add_row(var, value, desc)
+    
+    console.print(table)
+    console.print()
+
+# --- Main Test Runner ---
+
+async def main():
+    """Run all tests"""
+    console.print(Panel.fit(
+        "[bold cyan]Crawl4AI LLM Parameters Test Suite[/]\n" +
+        "Testing temperature and base_url configuration hierarchy",
+        border_style="cyan"
+    ))
+    
+    # Show current environment
+    # await show_environment_info()
+    
+    # Create HTTP client
+    async with httpx.AsyncClient(base_url=BASE_URL, timeout=60.0) as client:
+        # Check server health
+        if not await check_server_health(client):
+            console.print("[red]Server is not available. Please ensure the Docker container is running.[/]")
+            return
+        
+        # Run tests
+        tests = [
+            ("Default Configuration", test_default_no_params),
+            ("Request Temperature", test_request_temperature),
+            ("Provider Override", test_provider_override),
+            ("Custom Base URL", test_base_url_custom),
+            ("LLM Job Endpoint", test_llm_job_endpoint),
+            ("LLM Endpoint", test_llm_endpoint),
+        ]
+        
+        for i, (name, test_func) in enumerate(tests, 1):
+            if i > 1:
+                console.print()  # Add spacing between tests
+            
+            try:
+                await test_func(client)
+            except Exception as e:
+                console.print(f"[red]Test '{name}' failed with error: {e}[/]")
+                console.print_exception(show_locals=False)
+        
+        console.rule("[bold green]All Tests Complete![/]", style="green")
+        
+        # Summary
+        console.print("\n[bold cyan]Configuration Hierarchy Summary:[/]")
+        console.print("1. [yellow]Request parameters[/] - Highest priority (temperature, base_url in API call)")
+        console.print("2. [yellow]Provider-specific env[/] - e.g., OPENAI_TEMPERATURE, GROQ_BASE_URL")
+        console.print("3. [yellow]Global env variables[/] - LLM_TEMPERATURE, LLM_BASE_URL")
+        console.print("4. [yellow]System defaults[/] - Lowest priority (provider/litellm defaults)")
+        console.print()
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        console.print("\n[yellow]Tests interrupted by user.[/]")
+    except Exception as e:
+        console.print(f"\n[bold red]An error occurred:[/]")
+        console.print_exception(show_locals=False)

tests/docker/test_server_requests.py

@@ -143,7 +143,40 @@ class TestCrawlEndpoints:
         assert "<h1>Herman Melville - Moby-Dick</h1>" in result["html"]
         # We don't specify a markdown generator in this test, so don't make assumptions about markdown field
         # It might be null, missing, or populated depending on the server's default behavior
+    async def test_crawl_with_stream_direct(self, async_client: httpx.AsyncClient):
+        """Test that /crawl endpoint handles stream=True directly without redirect."""
+        payload = {
+            "urls": [SIMPLE_HTML_URL],
+            "browser_config": {
+                "type": "BrowserConfig",
+                "params": {
+                    "headless": True,
+                }
+            },
+            "crawler_config": {
+                "type": "CrawlerRunConfig", 
+                "params": {
+                    "stream": True,  # Set stream to True for direct streaming
+                    "screenshot": False,
+                    "cache_mode": CacheMode.BYPASS.value
+                }
+            }
+        }
 
+        # Send a request to the /crawl endpoint - should handle streaming directly
+        async with async_client.stream("POST", "/crawl", json=payload) as response:
+            assert response.status_code == 200
+            assert response.headers["content-type"] == "application/x-ndjson"
+            assert response.headers.get("x-stream-status") == "active"
+
+            results = await process_streaming_response(response)
+
+            assert len(results) == 1
+            result = results[0]
+            await assert_crawl_result_structure(result)
+            assert result["success"] is True
+            assert result["url"] == SIMPLE_HTML_URL
+            assert "<h1>Herman Melville - Moby-Dick</h1>" in result["html"]
     async def test_simple_crawl_single_url_streaming(self, async_client: httpx.AsyncClient):
         """Test /crawl/stream with a single URL and simple config values."""
         payload = {
@@ -635,7 +668,209 @@ class TestCrawlEndpoints:
             pytest.fail(f"LLM extracted content parsing or validation failed: {e}\nContent: {result['extracted_content']}")
         except Exception as e: # Catch any other unexpected error
             pytest.fail(f"An unexpected error occurred during LLM result processing: {e}\nContent: {result['extracted_content']}")
-            
+
+
+    # 7. Error Handling Tests
+    async def test_invalid_url_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for invalid URLs."""
+        payload = {
+            "urls": ["invalid-url", "https://nonexistent-domain-12345.com"],
+            "browser_config": {"type": "BrowserConfig", "params": {"headless": True}},
+            "crawler_config": {"type": "CrawlerRunConfig", "params": {"cache_mode": CacheMode.BYPASS.value}}
+        }
+        
+        response = await async_client.post("/crawl", json=payload)
+        # Should return 200 with failed results, not 500
+        print(f"Status code: {response.status_code}")
+        print(f"Response: {response.text}")
+        assert response.status_code == 500
+        data = response.json()
+        assert data["detail"].startswith("Crawl request failed:")
+
+    async def test_mixed_success_failure_urls(self, async_client: httpx.AsyncClient):
+        """Test handling of mixed success/failure URLs."""
+        payload = {
+            "urls": [
+                SIMPLE_HTML_URL,  # Should succeed
+                "https://nonexistent-domain-12345.com",  # Should fail
+                "https://invalid-url-with-special-chars-!@#$%^&*()",  # Should fail
+            ],
+            "browser_config": {"type": "BrowserConfig", "params": {"headless": True}},
+            "crawler_config": {
+                "type": "CrawlerRunConfig", 
+                "params": {
+                    "cache_mode": CacheMode.BYPASS.value,
+                    "markdown_generator": {
+                        "type": "DefaultMarkdownGenerator",
+                        "params": {
+                            "content_filter": {
+                                "type": "PruningContentFilter",
+                                "params": {"threshold": 0.5}
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        
+        response = await async_client.post("/crawl", json=payload)
+        assert response.status_code == 200
+        data = response.json()
+        assert data["success"] is True
+        assert len(data["results"]) == 3
+        
+        success_count = 0
+        failure_count = 0
+        
+        for result in data["results"]:
+            if result["success"]:
+                success_count += 1
+            else:
+                failure_count += 1
+                assert "error_message" in result
+                assert len(result["error_message"]) > 0
+                
+        assert success_count >= 1  # At least one should succeed
+        assert failure_count >= 1  # At least one should fail
+
+    async def test_streaming_mixed_urls(self, async_client: httpx.AsyncClient):
+        """Test streaming with mixed success/failure URLs."""
+        payload = {
+            "urls": [
+                SIMPLE_HTML_URL,  # Should succeed
+                "https://nonexistent-domain-12345.com",  # Should fail
+            ],
+            "browser_config": {"type": "BrowserConfig", "params": {"headless": True}},
+            "crawler_config": {
+                "type": "CrawlerRunConfig", 
+                "params": {
+                    "stream": True,
+                    "cache_mode": CacheMode.BYPASS.value
+                }
+            }
+        }
+        
+        async with async_client.stream("POST", "/crawl/stream", json=payload) as response:
+            response.raise_for_status()
+            results = await process_streaming_response(response)
+        
+        assert len(results) == 2
+        
+        success_count = 0
+        failure_count = 0
+        
+        for result in results:
+            if result["success"]:
+                success_count += 1
+                assert result["url"] == SIMPLE_HTML_URL
+            else:
+                failure_count += 1
+                assert "error_message" in result
+                assert result["error_message"] is not None
+        
+        assert success_count == 1
+        assert failure_count == 1
+
+    async def test_markdown_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for markdown endpoint."""
+        # Test invalid URL
+        invalid_payload = {"url": "invalid-url", "f": "fit"}
+        response = await async_client.post("/md", json=invalid_payload)
+        # Should return 400 for invalid URL format
+        assert response.status_code == 400
+        
+        # Test non-existent URL
+        nonexistent_payload = {"url": "https://nonexistent-domain-12345.com", "f": "fit"}
+        response = await async_client.post("/md", json=nonexistent_payload)
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_html_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for HTML endpoint."""
+        # Test invalid URL
+        invalid_payload = {"url": "invalid-url"}
+        response = await async_client.post("/html", json=invalid_payload)
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_screenshot_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for screenshot endpoint."""
+        # Test invalid URL
+        invalid_payload = {"url": "invalid-url"}
+        response = await async_client.post("/screenshot", json=invalid_payload)
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_pdf_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for PDF endpoint."""
+        # Test invalid URL
+        invalid_payload = {"url": "invalid-url"}
+        response = await async_client.post("/pdf", json=invalid_payload)
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_execute_js_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for execute_js endpoint."""
+        # Test invalid URL
+        invalid_payload = {"url": "invalid-url", "scripts": ["return document.title;"]}
+        response = await async_client.post("/execute_js", json=invalid_payload)
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_llm_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for LLM endpoint."""
+        # Test missing query parameter
+        response = await async_client.get("/llm/https://example.com")
+        assert response.status_code == 422  # FastAPI validation error, not 400
+        
+        # Test invalid URL
+        response = await async_client.get("/llm/invalid-url?q=test")
+        # Should return 500 for crawl failure
+        assert response.status_code == 500
+
+    async def test_ask_endpoint_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for ask endpoint."""
+        # Test invalid context_type
+        response = await async_client.get("/ask?context_type=invalid")
+        assert response.status_code == 422  # Validation error
+        
+        # Test invalid score_ratio
+        response = await async_client.get("/ask?score_ratio=2.0")  # > 1.0
+        assert response.status_code == 422  # Validation error
+        
+        # Test invalid max_results
+        response = await async_client.get("/ask?max_results=0")  # < 1
+        assert response.status_code == 422  # Validation error
+
+    async def test_config_dump_error_handling(self, async_client: httpx.AsyncClient):
+        """Test error handling for config dump endpoint."""
+        # Test invalid code
+        invalid_payload = {"code": "invalid_code"}
+        response = await async_client.post("/config/dump", json=invalid_payload)
+        assert response.status_code == 400
+        
+        # Test nested function calls (not allowed)
+        nested_payload = {"code": "CrawlerRunConfig(BrowserConfig())"}
+        response = await async_client.post("/config/dump", json=nested_payload)
+        assert response.status_code == 400
+
+    async def test_malformed_request_handling(self, async_client: httpx.AsyncClient):
+        """Test handling of malformed requests."""
+        # Test missing required fields
+        malformed_payload = {"urls": []}  # Missing browser_config and crawler_config
+        response = await async_client.post("/crawl", json=malformed_payload)
+        print(f"Response: {response.text}")
+        assert response.status_code == 422  # Validation error
+        
+        # Test empty URLs list
+        empty_urls_payload = {
+            "urls": [],
+            "browser_config": {"type": "BrowserConfig", "params": {}},
+            "crawler_config": {"type": "CrawlerRunConfig", "params": {}}
+        }
+        response = await async_client.post("/crawl", json=empty_urls_payload)
+        assert response.status_code == 422  # "At least one URL required"
+
 if __name__ == "__main__":
     # Define arguments for pytest programmatically
     # -v: verbose output

tests/general/test_bff_scoring.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+"""
+Simple test to verify BestFirstCrawlingStrategy fixes.
+This test crawls a real website and shows that:
+1. Higher-scoring pages are crawled first (priority queue fix)
+2. Links are scored before truncation (link discovery fix)
+"""
+
+import asyncio
+from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
+from crawl4ai.deep_crawling import BestFirstCrawlingStrategy
+from crawl4ai.deep_crawling.scorers import KeywordRelevanceScorer
+
+async def test_best_first_strategy():
+    """Test BestFirstCrawlingStrategy with keyword scoring"""
+    
+    print("=" * 70)
+    print("Testing BestFirstCrawlingStrategy with Real URL")
+    print("=" * 70)
+    print("\nThis test will:")
+    print("1. Crawl Python.org documentation")
+    print("2. Score pages based on keywords: 'tutorial', 'guide', 'reference'")
+    print("3. Show that higher-scoring pages are crawled first")
+    print("-" * 70)
+    
+    # Create a keyword scorer that prioritizes tutorial/guide pages
+    scorer = KeywordRelevanceScorer(
+        keywords=["tutorial", "guide", "reference", "documentation"],
+        weight=1.0,
+        case_sensitive=False
+    )
+    
+    # Create the strategy with scoring
+    strategy = BestFirstCrawlingStrategy(
+        max_depth=2,          # Crawl 2 levels deep
+        max_pages=10,         # Limit to 10 pages total
+        url_scorer=scorer,    # Use keyword scoring
+        include_external=False  # Only internal links
+    )
+    
+    # Configure browser and crawler
+    browser_config = BrowserConfig(
+        headless=True,    # Run in background
+        verbose=False     # Reduce output noise
+    )
+    
+    crawler_config = CrawlerRunConfig(
+        deep_crawl_strategy=strategy,
+        verbose=False
+    )
+    
+    print("\nStarting crawl of https://docs.python.org/3/")
+    print("Looking for pages with keywords: tutorial, guide, reference, documentation")
+    print("-" * 70)
+    
+    crawled_urls = []
+    
+    async with AsyncWebCrawler(config=browser_config) as crawler:
+        # Crawl and collect results
+        results = await crawler.arun(
+            url="https://docs.python.org/3/",
+            config=crawler_config
+        )
+        
+        # Process results
+        if isinstance(results, list):
+            for result in results:
+                score = result.metadata.get('score', 0) if result.metadata else 0
+                depth = result.metadata.get('depth', 0) if result.metadata else 0
+                crawled_urls.append({
+                    'url': result.url,
+                    'score': score,
+                    'depth': depth,
+                    'success': result.success
+                })
+    
+    print("\n" + "=" * 70)
+    print("CRAWL RESULTS (in order of crawling)")
+    print("=" * 70)
+    
+    for i, item in enumerate(crawled_urls, 1):
+        status = "✓" if item['success'] else "✗"
+        # Highlight high-scoring pages
+        if item['score'] > 0.5:
+            print(f"{i:2}. [{status}] Score: {item['score']:.2f} | Depth: {item['depth']} | {item['url']}")
+            print(f"     ^ HIGH SCORE - Contains keywords!")
+        else:
+            print(f"{i:2}. [{status}] Score: {item['score']:.2f} | Depth: {item['depth']} | {item['url']}")
+    
+    print("\n" + "=" * 70)
+    print("ANALYSIS")
+    print("=" * 70)
+    
+    # Check if higher scores appear early in the crawl
+    scores = [item['score'] for item in crawled_urls[1:]]  # Skip initial URL
+    high_score_indices = [i for i, s in enumerate(scores) if s > 0.3]
+    
+    if high_score_indices and high_score_indices[0] < len(scores) / 2:
+        print("✅ SUCCESS: Higher-scoring pages (with keywords) were crawled early!")
+        print("   This confirms the priority queue fix is working.")
+    else:
+        print("⚠️  Check the crawl order above - higher scores should appear early")
+    
+    # Show score distribution
+    print(f"\nScore Statistics:")
+    print(f"  - Total pages crawled: {len(crawled_urls)}")
+    print(f"  - Average score: {sum(item['score'] for item in crawled_urls) / len(crawled_urls):.2f}")
+    print(f"  - Max score: {max(item['score'] for item in crawled_urls):.2f}")
+    print(f"  - Pages with keywords: {sum(1 for item in crawled_urls if item['score'] > 0.3)}")
+    
+    print("\n" + "=" * 70)
+    print("TEST COMPLETE")
+    print("=" * 70)
+
+if __name__ == "__main__":
+    print("\n🔍 BestFirstCrawlingStrategy Simple Test\n")
+    asyncio.run(test_best_first_strategy())

tests/memory/test_docker_config_gen.py

@@ -24,7 +24,7 @@ CASES = [
     # --- BrowserConfig variants ---
     "BrowserConfig()",
     "BrowserConfig(headless=False, extra_args=['--disable-gpu'])",
-    "BrowserConfig(browser_mode='builtin', proxy='http://1.2.3.4:8080')",
+    "BrowserConfig(browser_mode='builtin', proxy_config={'server': 'http://1.2.3.4:8080'})",
 ]
 
 for code in CASES:

tests/proxy/test_proxy_deprecation.py

@@ -0,0 +1,42 @@
+import warnings
+
+import pytest
+
+from crawl4ai.async_configs import BrowserConfig, ProxyConfig
+
+
+def test_browser_config_proxy_string_emits_deprecation_and_autoconverts():
+    warnings.simplefilter("always", DeprecationWarning)
+
+    proxy_str = "23.95.150.145:6114:username:password"
+    with warnings.catch_warnings(record=True) as caught:
+        cfg = BrowserConfig(proxy=proxy_str, headless=True)
+
+    dep_warnings = [w for w in caught if issubclass(w.category, DeprecationWarning)]
+    assert dep_warnings, "Expected DeprecationWarning when using BrowserConfig(proxy=...)"
+
+    assert cfg.proxy is None, "cfg.proxy should be None after auto-conversion"
+    assert isinstance(cfg.proxy_config, ProxyConfig), "cfg.proxy_config should be ProxyConfig instance"
+    assert cfg.proxy_config.username == "username"
+    assert cfg.proxy_config.password == "password"
+    assert cfg.proxy_config.server.startswith("http://")
+    assert cfg.proxy_config.server.endswith(":6114")
+
+
+def test_browser_config_with_proxy_config_emits_no_deprecation():
+    warnings.simplefilter("always", DeprecationWarning)
+
+    with warnings.catch_warnings(record=True) as caught:
+        cfg = BrowserConfig(
+            headless=True,
+            proxy_config={
+                "server": "http://127.0.0.1:8080",
+                "username": "u",
+                "password": "p",
+            },
+        )
+
+    dep_warnings = [w for w in caught if issubclass(w.category, DeprecationWarning)]
+    assert not dep_warnings, "Did not expect DeprecationWarning when using proxy_config"
+    assert cfg.proxy is None
+    assert isinstance(cfg.proxy_config, ProxyConfig)

tests/telemetry/conftest.py

@@ -1,64 +0,0 @@
-"""
-Test configuration and utilities for telemetry testing.
-"""
-
-import os
-import pytest
-
-
-def pytest_configure(config):  # noqa: ARG001
-    """Configure pytest for telemetry tests."""
-    # Add custom markers
-    config.addinivalue_line("markers", "unit: Unit tests")
-    config.addinivalue_line("markers", "integration: Integration tests") 
-    config.addinivalue_line("markers", "privacy: Privacy compliance tests")
-    config.addinivalue_line("markers", "performance: Performance tests")
-    config.addinivalue_line("markers", "slow: Slow running tests")
-
-
-def pytest_collection_modifyitems(config, items):  # noqa: ARG001
-    """Modify test collection to add markers automatically."""
-    for item in items:
-        # Add markers based on test location and name
-        if "telemetry" in str(item.fspath):
-            if "integration" in item.name or "test_integration" in str(item.fspath):
-                item.add_marker(pytest.mark.integration)
-            elif "privacy" in item.name or "performance" in item.name:
-                if "privacy" in item.name:
-                    item.add_marker(pytest.mark.privacy)
-                if "performance" in item.name:
-                    item.add_marker(pytest.mark.performance)
-            else:
-                item.add_marker(pytest.mark.unit)
-            
-            # Mark slow tests
-            if "slow" in item.name or any(mark.name == "slow" for mark in item.iter_markers()):
-                item.add_marker(pytest.mark.slow)
-
-
-@pytest.fixture(autouse=True)
-def setup_test_environment():
-    """Set up test environment variables."""
-    # Ensure we're in test mode
-    os.environ['CRAWL4AI_TEST_MODE'] = '1'
-    
-    # Disable actual telemetry during tests unless explicitly enabled
-    if 'CRAWL4AI_TELEMETRY_TEST_REAL' not in os.environ:
-        os.environ['CRAWL4AI_TELEMETRY'] = '0'
-    
-    yield
-    
-    # Clean up after tests
-    test_vars = ['CRAWL4AI_TEST_MODE', 'CRAWL4AI_TELEMETRY_TEST_REAL']
-    for var in test_vars:
-        if var in os.environ:
-            del os.environ[var]
-
-
-def pytest_report_header(config):  # noqa: ARG001
-    """Add information to pytest header."""
-    return [
-        "Crawl4AI Telemetry Tests",
-        f"Test mode: {'ENABLED' if os.environ.get('CRAWL4AI_TEST_MODE') else 'DISABLED'}",
-        f"Real telemetry: {'ENABLED' if os.environ.get('CRAWL4AI_TELEMETRY_TEST_REAL') else 'DISABLED'}"
-    ]

tests/telemetry/test_integration.py

@@ -1,216 +0,0 @@
-"""
-Integration tests for telemetry CLI commands.
-"""
-
-import pytest
-import subprocess
-import sys
-import os
-from unittest.mock import patch, Mock
-
-
-@pytest.mark.integration
-class TestTelemetryCLI:
-    """Test telemetry CLI commands integration."""
-    
-    def test_telemetry_status_command(self, clean_environment, temp_config_dir):
-        """Test the telemetry status CLI command."""
-        # Import with mocked config
-        with patch('crawl4ai.telemetry.TelemetryConfig') as MockConfig:
-            mock_config = Mock()
-            mock_config.get_consent.return_value = 'not_set'
-            mock_config.is_enabled.return_value = False
-            MockConfig.return_value = mock_config
-            
-            from crawl4ai.cli import main
-            
-            # Test status command
-            with patch('sys.argv', ['crawl4ai', 'telemetry', 'status']):
-                try:
-                    main()
-                except SystemExit:
-                    pass  # CLI commands often call sys.exit()
-    
-    def test_telemetry_enable_command(self, clean_environment, temp_config_dir):
-        """Test the telemetry enable CLI command."""
-        with patch('crawl4ai.telemetry.TelemetryConfig') as MockConfig:
-            mock_config = Mock()
-            MockConfig.return_value = mock_config
-            
-            from crawl4ai.cli import main
-            
-            # Test enable command
-            with patch('sys.argv', ['crawl4ai', 'telemetry', 'enable', '--email', 'test@example.com']):
-                try:
-                    main()
-                except SystemExit:
-                    pass
-    
-    def test_telemetry_disable_command(self, clean_environment, temp_config_dir):
-        """Test the telemetry disable CLI command."""
-        with patch('crawl4ai.telemetry.TelemetryConfig') as MockConfig:
-            mock_config = Mock()
-            MockConfig.return_value = mock_config
-            
-            from crawl4ai.cli import main
-            
-            # Test disable command
-            with patch('sys.argv', ['crawl4ai', 'telemetry', 'disable']):
-                try:
-                    main()
-                except SystemExit:
-                    pass
-    
-    @pytest.mark.slow
-    def test_cli_subprocess_integration(self, temp_config_dir):
-        """Test CLI commands as subprocess calls."""
-        env = os.environ.copy()
-        env['CRAWL4AI_CONFIG_DIR'] = str(temp_config_dir)
-        
-        # Test status command via subprocess
-        try:
-            result = subprocess.run(
-                [sys.executable, '-m', 'crawl4ai.cli', 'telemetry', 'status'],
-                env=env,
-                capture_output=True,
-                text=True,
-                timeout=10
-            )
-            # Should not crash, regardless of exit code
-            assert result.returncode in [0, 1]  # May return 1 if not configured
-        except subprocess.TimeoutExpired:
-            pytest.skip("CLI command timed out")
-        except FileNotFoundError:
-            pytest.skip("CLI module not found")
-
-
-@pytest.mark.integration
-class TestAsyncWebCrawlerIntegration:
-    """Test AsyncWebCrawler telemetry integration."""
-    
-    @pytest.mark.asyncio
-    async def test_crawler_telemetry_decorator(self, enabled_telemetry_config, mock_sentry_provider):
-        """Test that AsyncWebCrawler methods are decorated with telemetry."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            from crawl4ai import AsyncWebCrawler
-            
-            # Check if the arun method has telemetry decoration
-            crawler = AsyncWebCrawler()
-            assert hasattr(crawler.arun, '__wrapped__') or callable(crawler.arun)
-    
-    @pytest.mark.asyncio
-    async def test_crawler_exception_capture_integration(self, enabled_telemetry_config, mock_sentry_provider):
-        """Test that exceptions in AsyncWebCrawler are captured."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            with patch('crawl4ai.telemetry.capture_exception') as _mock_capture:
-                from crawl4ai import AsyncWebCrawler
-                
-                async with AsyncWebCrawler() as crawler:
-                    try:
-                        # This should cause an exception
-                        await crawler.arun(url="invalid://url")
-                    except Exception:
-                        pass  # We expect this to fail
-                
-                # The decorator should have attempted to capture the exception
-                # Note: This might not always be called depending on where the exception occurs
-    
-    @pytest.mark.asyncio
-    async def test_crawler_with_disabled_telemetry(self, disabled_telemetry_config):
-        """Test that AsyncWebCrawler works normally with disabled telemetry."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=disabled_telemetry_config):
-            from crawl4ai import AsyncWebCrawler
-            
-            # Should work normally even with telemetry disabled
-            async with AsyncWebCrawler() as crawler:
-                assert crawler is not None
-
-
-@pytest.mark.integration  
-class TestDockerIntegration:
-    """Test Docker environment telemetry integration."""
-    
-    def test_docker_environment_detection(self, docker_environment, temp_config_dir):
-        """Test that Docker environment is detected correctly."""
-        from crawl4ai.telemetry.environment import EnvironmentDetector
-        
-        env = EnvironmentDetector.detect()
-        from crawl4ai.telemetry.environment import Environment
-        assert env == Environment.DOCKER
-    
-    def test_docker_default_telemetry_enabled(self, temp_config_dir):
-        """Test that telemetry is enabled by default in Docker."""
-        from crawl4ai.telemetry.environment import Environment
-        
-        # Clear any existing environment variables that might interfere
-        with patch.dict(os.environ, {}, clear=True):
-            # Set only the Docker environment variable
-            os.environ['CRAWL4AI_DOCKER'] = 'true'
-            
-            with patch('crawl4ai.telemetry.environment.EnvironmentDetector.detect', return_value=Environment.DOCKER):
-                from crawl4ai.telemetry.consent import ConsentManager
-                from crawl4ai.telemetry.config import TelemetryConfig, TelemetryConsent
-                
-                config = TelemetryConfig(config_dir=temp_config_dir)
-                consent_manager = ConsentManager(config)
-                
-                # Should set consent to ALWAYS for Docker
-                consent_manager.check_and_prompt()
-                assert config.get_consent() == TelemetryConsent.ALWAYS
-    
-    def test_docker_telemetry_can_be_disabled(self, temp_config_dir):
-        """Test that Docker telemetry can be disabled via environment variable."""
-        from crawl4ai.telemetry.environment import Environment
-        
-        with patch.dict(os.environ, {'CRAWL4AI_TELEMETRY': '0', 'CRAWL4AI_DOCKER': 'true'}):
-            with patch('crawl4ai.telemetry.environment.EnvironmentDetector.detect', return_value=Environment.DOCKER):
-                from crawl4ai.telemetry.consent import ConsentManager
-                from crawl4ai.telemetry.config import TelemetryConfig, TelemetryConsent
-                
-                config = TelemetryConfig(config_dir=temp_config_dir)
-                consent_manager = ConsentManager(config)
-                
-                # Should set consent to DENIED when env var is 0
-                consent_manager.check_and_prompt()
-                assert config.get_consent() == TelemetryConsent.DENIED
-
-
-@pytest.mark.integration
-class TestTelemetryProviderIntegration:
-    """Test telemetry provider integration."""
-    
-    def test_sentry_provider_initialization(self, enabled_telemetry_config):
-        """Test that Sentry provider initializes correctly."""
-        try:
-            from crawl4ai.telemetry.providers.sentry import SentryProvider
-            
-            provider = SentryProvider()
-            # Should not crash during initialization
-            assert provider is not None
-            
-        except ImportError:
-            pytest.skip("Sentry provider not available")
-    
-    def test_null_provider_fallback(self, disabled_telemetry_config):
-        """Test that NullProvider is used when telemetry is disabled."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=disabled_telemetry_config):
-            from crawl4ai.telemetry import TelemetryManager
-            from crawl4ai.telemetry.base import NullProvider
-            
-            manager = TelemetryManager()
-            assert isinstance(manager._provider, NullProvider)  # noqa: SLF001
-    
-    def test_graceful_degradation_without_sentry(self, enabled_telemetry_config):
-        """Test graceful degradation when sentry-sdk is not available."""
-        with patch.dict('sys.modules', {'sentry_sdk': None}):
-            with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-                from crawl4ai.telemetry import TelemetryManager
-                from crawl4ai.telemetry.base import NullProvider
-                
-                # Should fall back to NullProvider when Sentry is not available
-                manager = TelemetryManager()
-                assert isinstance(manager._provider, NullProvider)  # noqa: SLF001
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v"])

tests/telemetry/test_privacy_performance.py

@@ -1,283 +0,0 @@
-"""
-Privacy and performance tests for telemetry system.
-"""
-
-import pytest
-import time
-import asyncio
-from unittest.mock import patch
-from crawl4ai.telemetry import telemetry_decorator, async_telemetry_decorator, TelemetryManager
-
-
-@pytest.mark.privacy
-class TestTelemetryPrivacy:
-    """Test privacy compliance of telemetry system."""
-    
-    def test_no_url_captured(self, enabled_telemetry_config, mock_sentry_provider, privacy_test_data):
-        """Test that URLs are not captured in telemetry data."""
-        # Ensure config is properly set for sending
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            # Mock the provider directly in the manager
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            # Create exception with URL in context
-            exception = ValueError("Test error")
-            context = {'url': privacy_test_data['url']}
-            
-            manager.capture_exception(exception, context)
-            
-            # Verify that the provider was called
-            mock_sentry_provider.send_exception.assert_called_once()
-            call_args = mock_sentry_provider.send_exception.call_args
-            
-            # Verify that context was passed to the provider (filtering happens in provider)
-            assert len(call_args) >= 2
-    
-    def test_no_content_captured(self, enabled_telemetry_config, mock_sentry_provider, privacy_test_data):
-        """Test that crawled content is not captured."""
-        # Ensure config is properly set
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            exception = ValueError("Test error")
-            context = {
-                'content': privacy_test_data['content'],
-                'html': '<html><body>Private content</body></html>',
-                'text': 'Extracted private text'
-            }
-            
-            manager.capture_exception(exception, context)
-            
-            mock_sentry_provider.send_exception.assert_called_once()
-            call_args = mock_sentry_provider.send_exception.call_args
-            
-            # Verify that the provider was called (actual filtering would happen in provider)
-            assert len(call_args) >= 2
-    
-    def test_no_pii_captured(self, enabled_telemetry_config, mock_sentry_provider, privacy_test_data):
-        """Test that PII is not captured in telemetry."""
-        # Ensure config is properly set
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            exception = ValueError("Test error")
-            context = privacy_test_data['user_data'].copy()
-            context.update(privacy_test_data['pii'])
-            
-            manager.capture_exception(exception, context)
-            
-            mock_sentry_provider.send_exception.assert_called_once()
-            call_args = mock_sentry_provider.send_exception.call_args
-            
-            # Verify that the provider was called (actual filtering would happen in provider)
-            assert len(call_args) >= 2
-    
-    def test_sanitized_context_captured(self, enabled_telemetry_config, mock_sentry_provider):
-        """Test that only safe context is captured."""
-        # Ensure config is properly set
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            exception = ValueError("Test error")
-            context = {
-                'operation': 'crawl',  # Safe to capture
-                'status_code': 404,    # Safe to capture
-                'retry_count': 3,      # Safe to capture
-                'user_email': 'secret@example.com',  # Should be in context (not filtered at this level)
-                'content': 'private content'         # Should be in context (not filtered at this level)
-            }
-            
-            manager.capture_exception(exception, context)
-            
-            mock_sentry_provider.send_exception.assert_called_once()
-            call_args = mock_sentry_provider.send_exception.call_args
-            
-            # Get the actual arguments passed to the mock
-            args, kwargs = call_args
-            assert len(args) >= 2, f"Expected at least 2 args, got {len(args)}"
-            
-            # The second argument should be the context
-            captured_context = args[1]
-            
-            # The basic context should be present (this tests the manager, not the provider filtering)
-            assert 'operation' in captured_context, f"operation not found in {captured_context}"
-            assert captured_context.get('operation') == 'crawl'
-            assert captured_context.get('status_code') == 404
-            assert captured_context.get('retry_count') == 3
-
-
-@pytest.mark.performance
-class TestTelemetryPerformance:
-    """Test performance impact of telemetry system."""
-    
-    def test_decorator_overhead_sync(self, enabled_telemetry_config, mock_sentry_provider):  # noqa: ARG002
-        """Test performance overhead of sync telemetry decorator."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            
-            @telemetry_decorator
-            def test_function():
-                """Test function with telemetry decorator."""
-                time.sleep(0.001)  # Simulate small amount of work
-                return "success"
-            
-            # Measure time with telemetry
-            start_time = time.time()
-            for _ in range(100):
-                test_function()
-            telemetry_time = time.time() - start_time
-            
-            # Telemetry should add minimal overhead
-            assert telemetry_time < 1.0  # Should complete 100 calls in under 1 second
-    
-    @pytest.mark.asyncio
-    async def test_decorator_overhead_async(self, enabled_telemetry_config, mock_sentry_provider):  # noqa: ARG002
-        """Test performance overhead of async telemetry decorator."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            
-            @async_telemetry_decorator
-            async def test_async_function():
-                """Test async function with telemetry decorator."""
-                await asyncio.sleep(0.001)  # Simulate small amount of async work
-                return "success"
-            
-            # Measure time with telemetry
-            start_time = time.time()
-            tasks = [test_async_function() for _ in range(100)]
-            await asyncio.gather(*tasks)
-            telemetry_time = time.time() - start_time
-            
-            # Telemetry should add minimal overhead to async operations
-            assert telemetry_time < 2.0  # Should complete 100 async calls in under 2 seconds
-    
-    def test_disabled_telemetry_performance(self, disabled_telemetry_config):
-        """Test that disabled telemetry has zero overhead."""
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=disabled_telemetry_config):
-            
-            @telemetry_decorator
-            def test_function():
-                """Test function with disabled telemetry."""
-                time.sleep(0.001)
-                return "success"
-            
-            # Measure time with disabled telemetry
-            start_time = time.time()
-            for _ in range(100):
-                test_function()
-            disabled_time = time.time() - start_time
-            
-            # Should be very fast when disabled
-            assert disabled_time < 0.5  # Should be faster than enabled telemetry
-    
-    def test_telemetry_manager_initialization_performance(self):
-        """Test that TelemetryManager initializes quickly."""
-        start_time = time.time()
-        
-        # Initialize multiple managers (should use singleton)
-        for _ in range(10):
-            TelemetryManager.get_instance()
-        
-        init_time = time.time() - start_time
-        
-        # Initialization should be fast
-        assert init_time < 0.1  # Should initialize in under 100ms
-    
-    def test_config_loading_performance(self, temp_config_dir):
-        """Test that config loading is fast."""
-        from crawl4ai.telemetry.config import TelemetryConfig
-        
-        # Create config with some data
-        config = TelemetryConfig(config_dir=temp_config_dir)
-        from crawl4ai.telemetry.config import TelemetryConsent
-        config.set_consent(TelemetryConsent.ALWAYS, email="test@example.com")
-        
-        start_time = time.time()
-        
-        # Load config multiple times
-        for _ in range(100):
-            new_config = TelemetryConfig(config_dir=temp_config_dir)
-            new_config.get_consent()
-        
-        load_time = time.time() - start_time
-        
-        # Config loading should be fast
-        assert load_time < 0.5  # Should load 100 times in under 500ms
-
-
-@pytest.mark.performance
-class TestTelemetryScalability:
-    """Test telemetry system scalability."""
-    
-    def test_multiple_exception_capture(self, enabled_telemetry_config, mock_sentry_provider):
-        """Test capturing multiple exceptions in sequence."""
-        # Ensure config is properly set
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            start_time = time.time()
-            
-            # Capture many exceptions
-            for i in range(50):
-                exception = ValueError(f"Test error {i}")
-                manager.capture_exception(exception, {'operation': f'test_{i}'})
-            
-            capture_time = time.time() - start_time
-            
-            # Should handle multiple exceptions efficiently
-            assert capture_time < 1.0  # Should capture 50 exceptions in under 1 second
-            assert mock_sentry_provider.send_exception.call_count <= 50  # May be less due to consent checks
-    
-    @pytest.mark.asyncio
-    async def test_concurrent_exception_capture(self, enabled_telemetry_config, mock_sentry_provider):  # noqa: ARG002
-        """Test concurrent exception capture performance."""
-        # Ensure config is properly set
-        enabled_telemetry_config.is_enabled.return_value = True
-        enabled_telemetry_config.should_send_current.return_value = True
-        
-        with patch('crawl4ai.telemetry.TelemetryConfig', return_value=enabled_telemetry_config):
-            manager = TelemetryManager()
-            manager._provider = mock_sentry_provider  # noqa: SLF001
-            manager._initialized = True  # noqa: SLF001
-            
-            async def capture_exception_async(i):
-                exception = ValueError(f"Concurrent error {i}")
-                return manager.capture_exception(exception, {'operation': f'concurrent_{i}'})
-            
-            start_time = time.time()
-            
-            # Capture exceptions concurrently
-            tasks = [capture_exception_async(i) for i in range(20)]
-            await asyncio.gather(*tasks)
-            
-            capture_time = time.time() - start_time
-            
-            # Should handle concurrent exceptions efficiently
-            assert capture_time < 1.0  # Should capture 20 concurrent exceptions in under 1 second
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v"])

tests/telemetry/test_telemetry.py

@@ -1,241 +0,0 @@
-"""
-Tests for Crawl4AI telemetry functionality.
-"""
-
-import pytest
-import os
-import tempfile
-from pathlib import Path
-import json
-from unittest.mock import Mock, patch, MagicMock
-
-from crawl4ai.telemetry import (
-    TelemetryManager,
-    capture_exception,
-    enable,
-    disable,
-    status
-)
-from crawl4ai.telemetry.config import TelemetryConfig, TelemetryConsent
-from crawl4ai.telemetry.environment import Environment, EnvironmentDetector
-from crawl4ai.telemetry.base import NullProvider
-from crawl4ai.telemetry.consent import ConsentManager
-
-
-class TestTelemetryConfig:
-    """Test telemetry configuration management."""
-    
-    def test_config_initialization(self):
-        """Test config initialization with custom directory."""
-        with tempfile.TemporaryDirectory() as tmpdir:
-            config = TelemetryConfig(config_dir=Path(tmpdir))
-            assert config.config_dir == Path(tmpdir)
-            assert config.get_consent() == TelemetryConsent.NOT_SET
-    
-    def test_consent_persistence(self):
-        """Test that consent is saved and loaded correctly."""
-        with tempfile.TemporaryDirectory() as tmpdir:
-            config = TelemetryConfig(config_dir=Path(tmpdir))
-            
-            # Set consent
-            config.set_consent(TelemetryConsent.ALWAYS, email="test@example.com")
-            
-            # Create new config instance to test persistence
-            config2 = TelemetryConfig(config_dir=Path(tmpdir))
-            assert config2.get_consent() == TelemetryConsent.ALWAYS
-            assert config2.get_email() == "test@example.com"
-    
-    def test_environment_variable_override(self):
-        """Test that environment variables override config."""
-        with tempfile.TemporaryDirectory() as tmpdir:
-            config = TelemetryConfig(config_dir=Path(tmpdir))
-            config.set_consent(TelemetryConsent.ALWAYS)
-            
-            # Set environment variable to disable
-            os.environ['CRAWL4AI_TELEMETRY'] = '0'
-            try:
-                config.update_from_env()
-                assert config.get_consent() == TelemetryConsent.DENIED
-            finally:
-                del os.environ['CRAWL4AI_TELEMETRY']
-
-
-class TestEnvironmentDetection:
-    """Test environment detection functionality."""
-    
-    def test_cli_detection(self):
-        """Test CLI environment detection."""
-        # Mock sys.stdin.isatty
-        with patch('sys.stdin.isatty', return_value=True):
-            env = EnvironmentDetector.detect()
-            # Should detect as CLI in most test environments
-            assert env in [Environment.CLI, Environment.UNKNOWN]
-    
-    def test_docker_detection(self):
-        """Test Docker environment detection."""
-        # Mock Docker environment
-        with patch.dict(os.environ, {'CRAWL4AI_DOCKER': 'true'}):
-            env = EnvironmentDetector.detect()
-            assert env == Environment.DOCKER
-    
-    def test_api_server_detection(self):
-        """Test API server detection."""
-        with patch.dict(os.environ, {'CRAWL4AI_API_SERVER': 'true', 'CRAWL4AI_DOCKER': 'true'}):
-            env = EnvironmentDetector.detect()
-            assert env == Environment.API_SERVER
-
-
-class TestTelemetryManager:
-    """Test the main telemetry manager."""
-    
-    def test_singleton_pattern(self):
-        """Test that TelemetryManager is a singleton."""
-        manager1 = TelemetryManager.get_instance()
-        manager2 = TelemetryManager.get_instance()
-        assert manager1 is manager2
-    
-    def test_exception_capture(self):
-        """Test exception capture functionality."""
-        with tempfile.TemporaryDirectory() as tmpdir:
-            # Create manager with custom config dir
-            with patch('crawl4ai.telemetry.TelemetryConfig') as MockConfig:
-                mock_config = Mock()
-                mock_config.get_consent.return_value = TelemetryConsent.ALWAYS
-                mock_config.is_enabled.return_value = True
-                mock_config.should_send_current.return_value = True
-                mock_config.get_email.return_value = "test@example.com"
-                mock_config.update_from_env.return_value = None
-                MockConfig.return_value = mock_config
-                
-                # Mock the provider setup
-                with patch('crawl4ai.telemetry.providers.sentry.SentryProvider') as MockSentryProvider:
-                    mock_provider = Mock()
-                    mock_provider.initialize.return_value = True
-                    mock_provider.send_exception.return_value = True
-                    MockSentryProvider.return_value = mock_provider
-                    
-                    manager = TelemetryManager()
-                    
-                    # Test exception capture
-                    test_exception = ValueError("Test error")
-                    result = manager.capture_exception(test_exception, {'test': 'context'})
-                    
-                    # Verify the exception was processed
-                    assert mock_config.should_send_current.called
-    
-    def test_null_provider_when_disabled(self):
-        """Test that NullProvider is used when telemetry is disabled."""
-        with tempfile.TemporaryDirectory() as tmpdir:
-            with patch('crawl4ai.telemetry.TelemetryConfig') as MockConfig:
-                mock_config = Mock()
-                mock_config.get_consent.return_value = TelemetryConsent.DENIED
-                mock_config.is_enabled.return_value = False
-                MockConfig.return_value = mock_config
-                
-                manager = TelemetryManager()
-                assert isinstance(manager._provider, NullProvider)
-
-
-class TestConsentManager:
-    """Test consent management functionality."""
-    
-    def test_docker_default_enabled(self):
-        """Test that Docker environment has telemetry enabled by default."""
-        with patch('crawl4ai.telemetry.consent.EnvironmentDetector.detect', return_value=Environment.DOCKER):
-            with patch('os.environ.get') as mock_env_get:
-                # Mock os.environ.get to return None for CRAWL4AI_TELEMETRY
-                mock_env_get.return_value = None
-                
-                config = Mock()
-                config.get_consent.return_value = TelemetryConsent.NOT_SET
-                
-                consent_manager = ConsentManager(config)
-                consent_manager.check_and_prompt()
-                
-                # Should be enabled by default in Docker
-                assert config.set_consent.called
-                assert config.set_consent.call_args[0][0] == TelemetryConsent.ALWAYS
-    
-    def test_docker_disabled_by_env(self):
-        """Test that Docker telemetry can be disabled via environment variable."""
-        with patch('crawl4ai.telemetry.consent.EnvironmentDetector.detect', return_value=Environment.DOCKER):
-            with patch.dict(os.environ, {'CRAWL4AI_TELEMETRY': '0'}):
-                config = Mock()
-                config.get_consent.return_value = TelemetryConsent.NOT_SET
-                
-                consent_manager = ConsentManager(config)
-                consent = consent_manager.check_and_prompt()
-                
-                # Should be disabled
-                assert config.set_consent.called
-                assert config.set_consent.call_args[0][0] == TelemetryConsent.DENIED
-
-
-class TestPublicAPI:
-    """Test the public API functions."""
-    
-    @patch('crawl4ai.telemetry.get_telemetry')
-    def test_enable_function(self, mock_get_telemetry):
-        """Test the enable() function."""
-        mock_manager = Mock()
-        mock_get_telemetry.return_value = mock_manager
-        
-        enable(email="test@example.com", always=True)
-        
-        mock_manager.enable.assert_called_once_with(
-            email="test@example.com",
-            always=True,
-            once=False
-        )
-    
-    @patch('crawl4ai.telemetry.get_telemetry')
-    def test_disable_function(self, mock_get_telemetry):
-        """Test the disable() function."""
-        mock_manager = Mock()
-        mock_get_telemetry.return_value = mock_manager
-        
-        disable()
-        
-        mock_manager.disable.assert_called_once()
-    
-    @patch('crawl4ai.telemetry.get_telemetry')
-    def test_status_function(self, mock_get_telemetry):
-        """Test the status() function."""
-        mock_manager = Mock()
-        mock_manager.status.return_value = {
-            'enabled': True,
-            'consent': 'always',
-            'email': 'test@example.com'
-        }
-        mock_get_telemetry.return_value = mock_manager
-        
-        result = status()
-        
-        assert result['enabled'] is True
-        assert result['consent'] == 'always'
-        assert result['email'] == 'test@example.com'
-
-
-class TestIntegration:
-    """Integration tests for telemetry with AsyncWebCrawler."""
-    
-    @pytest.mark.asyncio
-    async def test_crawler_exception_capture(self):
-        """Test that AsyncWebCrawler captures exceptions."""
-        from crawl4ai import AsyncWebCrawler
-        
-        with patch('crawl4ai.telemetry.capture_exception') as mock_capture:
-            # This should trigger an exception for invalid URL
-            async with AsyncWebCrawler() as crawler:
-                try:
-                    # Use an invalid URL that will cause an error
-                    result = await crawler.arun(url="not-a-valid-url")
-                except Exception:
-                    pass
-            
-            # Check if exception was captured (may not be called if error is handled)
-            # This is more of a smoke test to ensure the integration doesn't break
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v"])

tests/test_preserve_https_for_internal_links.py

@@ -0,0 +1,175 @@
+#!/usr/bin/env python3
+"""
+Final test and demo for HTTPS preservation feature (Issue #1410)
+
+This demonstrates how the preserve_https_for_internal_links flag
+prevents HTTPS downgrade when servers redirect to HTTP.
+"""
+
+import sys
+import os
+from urllib.parse import urljoin, urlparse
+
+def demonstrate_issue():
+    """Show the problem: HTTPS -> HTTP redirect causes HTTP links"""
+    
+    print("=" * 60)
+    print("DEMONSTRATING THE ISSUE")
+    print("=" * 60)
+    
+    # Simulate what happens during crawling
+    original_url = "https://quotes.toscrape.com/tag/deep-thoughts"
+    redirected_url = "http://quotes.toscrape.com/tag/deep-thoughts/"  # Server redirects to HTTP
+    
+    # Extract a relative link
+    relative_link = "/author/Albert-Einstein"
+    
+    # Standard URL joining uses the redirected (HTTP) base
+    resolved_url = urljoin(redirected_url, relative_link)
+    
+    print(f"Original URL:    {original_url}")
+    print(f"Redirected to:   {redirected_url}")
+    print(f"Relative link:   {relative_link}")
+    print(f"Resolved link:   {resolved_url}")
+    print(f"\n❌ Problem: Link is now HTTP instead of HTTPS!")
+    
+    return resolved_url
+
+def demonstrate_solution():
+    """Show the solution: preserve HTTPS for internal links"""
+    
+    print("\n" + "=" * 60)
+    print("DEMONSTRATING THE SOLUTION")
+    print("=" * 60)
+    
+    # Our normalize_url with HTTPS preservation
+    def normalize_url_with_preservation(href, base_url, preserve_https=False, original_scheme=None):
+        """Normalize URL with optional HTTPS preservation"""
+        
+        # Standard resolution
+        full_url = urljoin(base_url, href.strip())
+        
+        # Preserve HTTPS if requested
+        if preserve_https and original_scheme == 'https':
+            parsed_full = urlparse(full_url)
+            parsed_base = urlparse(base_url)
+            
+            # Only for same-domain links
+            if parsed_full.scheme == 'http' and parsed_full.netloc == parsed_base.netloc:
+                full_url = full_url.replace('http://', 'https://', 1)
+                print(f"  → Preserved HTTPS for {parsed_full.netloc}")
+        
+        return full_url
+    
+    # Same scenario as before
+    original_url = "https://quotes.toscrape.com/tag/deep-thoughts"
+    redirected_url = "http://quotes.toscrape.com/tag/deep-thoughts/"
+    relative_link = "/author/Albert-Einstein"
+    
+    # Without preservation (current behavior)
+    resolved_without = normalize_url_with_preservation(
+        relative_link, redirected_url,
+        preserve_https=False, original_scheme='https'
+    )
+    
+    print(f"\nWithout preservation:")
+    print(f"  Result: {resolved_without}")
+    
+    # With preservation (new feature)
+    resolved_with = normalize_url_with_preservation(
+        relative_link, redirected_url,
+        preserve_https=True, original_scheme='https'
+    )
+    
+    print(f"\nWith preservation (preserve_https_for_internal_links=True):")
+    print(f"  Result: {resolved_with}")
+    print(f"\n✅ Solution: Internal link stays HTTPS!")
+    
+    return resolved_with
+
+def test_edge_cases():
+    """Test important edge cases"""
+    
+    print("\n" + "=" * 60)
+    print("EDGE CASES")
+    print("=" * 60)
+    
+    from urllib.parse import urljoin, urlparse
+    
+    def preserve_https(href, base_url, original_scheme):
+        """Helper to test preservation logic"""
+        full_url = urljoin(base_url, href)
+        
+        if original_scheme == 'https':
+            parsed_full = urlparse(full_url)
+            parsed_base = urlparse(base_url)
+            # Fixed: check for protocol-relative URLs
+            if (parsed_full.scheme == 'http' and 
+                parsed_full.netloc == parsed_base.netloc and
+                not href.strip().startswith('//')):
+                full_url = full_url.replace('http://', 'https://', 1)
+        
+        return full_url
+    
+    test_cases = [
+        # (description, href, base_url, original_scheme, should_be_https)
+        ("External link", "http://other.com/page", "http://example.com", "https", False),
+        ("Already HTTPS", "/page", "https://example.com", "https", True),
+        ("No original HTTPS", "/page", "http://example.com", "http", False),
+        ("Subdomain", "/page", "http://sub.example.com", "https", True),
+        ("Protocol-relative", "//example.com/page", "http://example.com", "https", False),
+    ]
+    
+    for desc, href, base_url, orig_scheme, should_be_https in test_cases:
+        result = preserve_https(href, base_url, orig_scheme)
+        is_https = result.startswith('https://')
+        status = "✅" if is_https == should_be_https else "❌"
+        
+        print(f"\n{status} {desc}:")
+        print(f"  Input: {href} + {base_url}")
+        print(f"  Result: {result}")
+        print(f"  Expected HTTPS: {should_be_https}, Got: {is_https}")
+
+def usage_example():
+    """Show how to use the feature in crawl4ai"""
+    
+    print("\n" + "=" * 60)
+    print("USAGE IN CRAWL4AI")
+    print("=" * 60)
+    
+    print("""
+To enable HTTPS preservation in your crawl4ai code:
+
+```python
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
+
+async with AsyncWebCrawler() as crawler:
+    config = CrawlerRunConfig(
+        preserve_https_for_internal_links=True  # Enable HTTPS preservation
+    )
+    
+    result = await crawler.arun(
+        url="https://example.com",
+        config=config
+    )
+    
+    # All internal links will maintain HTTPS even if 
+    # the server redirects to HTTP
+```
+
+This is especially useful for:
+- Sites that redirect HTTPS to HTTP but still support HTTPS
+- Security-conscious crawling where you want to stay on HTTPS
+- Avoiding mixed content issues in downstream processing
+""")
+
+if __name__ == "__main__":
+    # Run all demonstrations
+    demonstrate_issue()
+    demonstrate_solution() 
+    test_edge_cases()
+    usage_example()
+    
+    print("\n" + "=" * 60)
+    print("✅ All tests complete!")
+    print("=" * 60)