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.

tests/20241401/test_llm_filter.py

@@ -1,7 +1,7 @@
 import os
 import asyncio
 from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 from crawl4ai.content_filter_strategy import LLMContentFilter
 
 async def test_llm_filter():
@@ -23,7 +23,7 @@ async def test_llm_filter():
 
         # Initialize LLM filter with focused instruction
         filter = LLMContentFilter(
-            llmConfig=LlmConfig(provider="openai/gpt-4o",api_token=os.getenv('OPENAI_API_KEY')),
+            llm_config=LLMConfig(provider="openai/gpt-4o",api_token=os.getenv('OPENAI_API_KEY')),
             instruction="""
             Focus on extracting the core educational content about Python classes.
             Include:
@@ -43,7 +43,7 @@ async def test_llm_filter():
         )
         
         filter = LLMContentFilter(
-            llmConfig = LlmConfig(provider="openai/gpt-4o",api_token=os.getenv('OPENAI_API_KEY')),
+            llm_config = LLMConfig(provider="openai/gpt-4o",api_token=os.getenv('OPENAI_API_KEY')),
             chunk_token_threshold=2 ** 12 * 2, # 2048 * 2
             instruction="""
             Extract the main educational content while preserving its original wording and substance completely. Your task is to:

tests/async/test_chunking_and_extraction_strategies.py

@@ -7,7 +7,7 @@ import json
 parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.append(parent_dir)
 
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 from crawl4ai.async_webcrawler import AsyncWebCrawler
 from crawl4ai.chunking_strategy import RegexChunking
 from crawl4ai.extraction_strategy import LLMExtractionStrategy
@@ -49,7 +49,7 @@ async def test_llm_extraction_strategy():
     async with AsyncWebCrawler(verbose=True) as crawler:
         url = "https://www.nbcnews.com/business"
         extraction_strategy = LLMExtractionStrategy(
-            llmConfig=LlmConfig(provider="openai/gpt-4o-mini",api_token=os.getenv("OPENAI_API_KEY")),
+            llm_config=LLMConfig(provider="openai/gpt-4o-mini",api_token=os.getenv("OPENAI_API_KEY")),
             instruction="Extract only content related to technology",
         )
         result = await crawler.arun(

tests/docker/test_docker.py

@@ -7,7 +7,7 @@ from crawl4ai import (
     BrowserConfig, CrawlerRunConfig, DefaultMarkdownGenerator,
     PruningContentFilter, JsonCssExtractionStrategy, LLMContentFilter, CacheMode
 )
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 from crawl4ai.docker_client import Crawl4aiDockerClient
 
 class Crawl4AiTester:
@@ -143,7 +143,7 @@ async def test_with_client():
             cache_mode=CacheMode.BYPASS,
             markdown_generator=DefaultMarkdownGenerator(
                 content_filter=LLMContentFilter(
-                    llmConfig=LlmConfig(provider="openai/gpt-40"),
+                    llm_config=LLMConfig(provider="openai/gpt-40"),
                     instruction="Extract key technical concepts"
                 )
             ),

tests/docker/test_serialization.py

@@ -2,7 +2,7 @@ import inspect
 from typing import Any, Dict
 from enum import Enum
 
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 
 def to_serializable_dict(obj: Any) -> Dict:
     """
@@ -224,7 +224,7 @@ if __name__ == "__main__":
     config3 = CrawlerRunConfig(
         markdown_generator=DefaultMarkdownGenerator(
             content_filter=LLMContentFilter(
-                llmConfig = LlmConfig(provider="openai/gpt-4"),
+                llm_config = LLMConfig(provider="openai/gpt-4"),
                 instruction="Extract key technical concepts",
                 chunk_token_threshold=2000,
                 overlap_rate=0.1

tests/test_web_crawler.py

@@ -1,5 +1,5 @@
 import unittest, os
-from crawl4ai.async_configs import LlmConfig
+from crawl4ai.types import LLMConfig
 from crawl4ai.web_crawler import WebCrawler
 from crawl4ai.chunking_strategy import (
     RegexChunking,
@@ -43,7 +43,7 @@ class TestWebCrawler(unittest.TestCase):
             word_count_threshold=5,
             chunking_strategy=FixedLengthWordChunking(chunk_size=100),
             extraction_strategy=LLMExtractionStrategy(
-                llmConfig=LlmConfig(provider="openai/gpt-3.5-turbo", api_token=os.getenv("OPENAI_API_KEY"))
+                llm_config=LLMConfig(provider="openai/gpt-3.5-turbo", api_token=os.getenv("OPENAI_API_KEY"))
             ),
             bypass_cache=True,
         )