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/examples/extraction_strategies_examples.py

@@ -11,6 +11,7 @@ import asyncio
 import os
 
 from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
+from crawl4ai.async_configs import LlmConfig
 from crawl4ai.extraction_strategy import (
     LLMExtractionStrategy,
     JsonCssExtractionStrategy,
@@ -60,22 +61,19 @@ async def main():
 
     # 1. LLM Extraction with different input formats
     markdown_strategy = LLMExtractionStrategy(
-        provider="openai/gpt-4o-mini",
-        api_token=os.getenv("OPENAI_API_KEY"),
+        llmConfig = LlmConfig(provider="openai/gpt-4o-mini", api_token=os.getenv("OPENAI_API_KEY")),
         instruction="Extract product information including name, price, and description",
     )
 
     html_strategy = LLMExtractionStrategy(
         input_format="html",
-        provider="openai/gpt-4o-mini",
-        api_token=os.getenv("OPENAI_API_KEY"),
+        llmConfig=LlmConfig(provider="openai/gpt-4o-mini", api_token=os.getenv("OPENAI_API_KEY")),
         instruction="Extract product information from HTML including structured data",
     )
 
     fit_markdown_strategy = LLMExtractionStrategy(
         input_format="fit_markdown",
-        provider="openai/gpt-4o-mini",
-        api_token=os.getenv("OPENAI_API_KEY"),
+        llmConfig=LlmConfig(provider="openai/gpt-4o-mini",api_token=os.getenv("OPENAI_API_KEY")),
         instruction="Extract product information from cleaned markdown",
     )