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/content-selection.md

@@ -211,7 +211,7 @@ if __name__ == "__main__":
 import asyncio
 import json
 from pydantic import BaseModel, Field
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, LlmConfig
 from crawl4ai.extraction_strategy import LLMExtractionStrategy
 
 class ArticleData(BaseModel):
@@ -220,8 +220,7 @@ class ArticleData(BaseModel):
 
 async def main():
     llm_strategy = LLMExtractionStrategy(
-        provider="openai/gpt-4",
-        api_token="sk-YOUR_API_KEY",
+        llmConfig = LlmConfig(provider="openai/gpt-4",api_token="sk-YOUR_API_KEY")
         schema=ArticleData.schema(),
         extraction_type="schema",
         instruction="Extract 'headline' and a short 'summary' from the content."