Feat/llm config (#724)

* feature: Add LlmConfig to easily configure and pass LLM configs to different strategies

* pulled in next branch and resolved conflicts

* feat: Add gemini and deepseek providers. Make ignore_cache in llm content filter to true by default to avoid confusions

* Refactor: Update LlmConfig in LLMExtractionStrategy class and deprecate old params

* updated tests, docs and readme

docs/md_v2/core/markdown-generation.md

@@ -175,14 +175,13 @@ prune_filter = PruningContentFilter(
 For intelligent content filtering and high-quality markdown generation, you can use the **LLMContentFilter**. This filter leverages LLMs to generate relevant markdown while preserving the original content's meaning and structure:
 
 ```python
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
+from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, LlmConfig
 from crawl4ai.content_filter_strategy import LLMContentFilter
 
 async def main():
     # Initialize LLM filter with specific instruction
     filter = LLMContentFilter(
-        provider="openai/gpt-4o",  # or your preferred provider
-        api_token="your-api-token",  # or use environment variable
+        llmConfig = LlmConfig(provider="openai/gpt-4o",api_token="your-api-token"), #or use environment variable
         instruction="""
         Focus on extracting the core educational content.
         Include: