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/quickstart_async.config.py

@@ -1,5 +1,7 @@
 import os, sys
 
+from crawl4ai.async_configs import LlmConfig
+
 sys.path.append(
     os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 )
@@ -209,8 +211,7 @@ async def extract_structured_data_using_llm(
         word_count_threshold=1,
         page_timeout=80000,
         extraction_strategy=LLMExtractionStrategy(
-            provider=provider,
-            api_token=api_token,
+            llmConfig=LlmConfig(provider=provider,api_token=api_token),
             schema=OpenAIModelFee.model_json_schema(),
             extraction_type="schema",
             instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens.