refactor(llm): rename LlmConfig to LLMConfig for consistency

Rename LlmConfig to LLMConfig across the codebase to follow consistent naming conventions.
Update all imports and usages to use the new name.
Update documentation and examples to reflect the change.

BREAKING CHANGE: LlmConfig has been renamed to LLMConfig. Users need to update their imports and usage.

docs/examples/tutorial_v0.5.py

@@ -17,7 +17,7 @@ from crawl4ai.configs import ProxyConfig
 from crawl4ai import RoundRobinProxyStrategy
 from crawl4ai.content_filter_strategy import LLMContentFilter
 from crawl4ai import DefaultMarkdownGenerator
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
 from crawl4ai.processors.pdf import PDFCrawlerStrategy, PDFContentScrapingStrategy
 from pprint import pprint
@@ -284,9 +284,9 @@ async def llm_content_filter():
     PART 5: LLM Content Filter
     
     This function demonstrates:
-    - Configuring LLM providers via LlmConfig
+    - Configuring LLM providers via LLMConfig
     - Using LLM to generate focused markdown
-    - LlmConfig for configuration
+    - LLMConfig for configuration
     
     Note: Requires a valid API key for the chosen LLM provider
     """
@@ -296,7 +296,7 @@ async def llm_content_filter():
     
     # Create LLM configuration
     # Replace with your actual API key or set as environment variable
-    llm_config = LlmConfig(
+    llm_config = LLMConfig(
         provider="gemini/gemini-1.5-pro", 
         api_token="env:GEMINI_API_KEY"  # Will read from GEMINI_API_KEY environment variable
     )
@@ -309,7 +309,7 @@ async def llm_content_filter():
     # Create markdown generator with LLM filter
     markdown_generator = DefaultMarkdownGenerator(
         content_filter=LLMContentFilter(
-            llmConfig=llm_config,
+            llm_config=llm_config,
             instruction="Extract key concepts and summaries"
         )
     )
@@ -381,7 +381,7 @@ async def llm_schema_generation():
     PART 7: LLM Schema Generation
     
     This function demonstrates:
-    - Configuring LLM providers via LlmConfig
+    - Configuring LLM providers via LLMConfig
     - Using LLM to generate extraction schemas
     - JsonCssExtractionStrategy
     
@@ -406,9 +406,9 @@ async def llm_schema_generation():
         <div class="rating">4.7/5</div>
     </div>
     """
-    print("\n📊 Setting up LlmConfig...")
+    print("\n📊 Setting up LLMConfig...")
     # Create LLM configuration
-    llm_config = LlmConfig(
+    llm_config = LLMConfig(
         provider="gemini/gemini-1.5-pro", 
         api_token="env:GEMINI_API_KEY"
     )
@@ -416,7 +416,7 @@ async def llm_schema_generation():
     print("  This would use the LLM to analyze HTML and create an extraction schema")
     schema = JsonCssExtractionStrategy.generate_schema(
     html=sample_html,
-    llmConfig = llm_config,
+    llm_config = llm_config,
     query="Extract product name and price"
     )
     print("\n✅ Generated Schema:")