Refactor LLM cache config to use argparse and add status display
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@@ -50,9 +50,6 @@ from .auth import auth_handler
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# This update allows the user to put a different.env file for each lightrag folder
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load_dotenv(".env", override=True)
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# Read entity extraction cache config
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enable_llm_cache = os.getenv("ENABLE_LLM_CACHE_FOR_EXTRACT", "false").lower() == "true"
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# Initialize config parser
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config = configparser.ConfigParser()
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config.read("config.ini")
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@@ -326,7 +323,7 @@ def create_app(args):
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vector_db_storage_cls_kwargs={
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"cosine_better_than_threshold": args.cosine_threshold
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},
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enable_llm_cache_for_entity_extract=enable_llm_cache, # Read from environment variable
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enable_llm_cache_for_entity_extract=args.enable_llm_cache, # Read from args
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embedding_cache_config={
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"enabled": True,
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"similarity_threshold": 0.95,
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@@ -355,7 +352,7 @@ def create_app(args):
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vector_db_storage_cls_kwargs={
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"cosine_better_than_threshold": args.cosine_threshold
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},
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enable_llm_cache_for_entity_extract=enable_llm_cache, # Read from environment variable
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enable_llm_cache_for_entity_extract=args.enable_llm_cache, # Read from args
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embedding_cache_config={
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"enabled": True,
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"similarity_threshold": 0.95,
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@@ -419,6 +416,7 @@ def create_app(args):
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"doc_status_storage": args.doc_status_storage,
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"graph_storage": args.graph_storage,
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"vector_storage": args.vector_storage,
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"enable_llm_cache": args.enable_llm_cache,
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},
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"update_status": update_status,
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}
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