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Allow configuration of LLM parameters through environment variables

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yangdx 2025-01-29 23:39:47 +08:00
parent 20d6355a4a
commit e29682eef8
1 changed files with 2 additions and 2 deletions
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lightrag/lightrag.py
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@ -158,8 +158,8 @@ class LightRAG:
# LLM
llm_model_func: callable = None # This must be set (we do want to separate llm from the corte, so no more default initialization)
llm_model_name: str = "meta-llama/Llama-3.2-1B-Instruct" # 'meta-llama/Llama-3.2-1B'#'google/gemma-2-2b-it'
llm_model_max_token_size: int = 32768
llm_model_max_async: int = 16
llm_model_max_token_size: int = int(os.getenv("MAX_TOKENS", "32768"))
llm_model_max_async: int = int(os.getenv("MAX_ASYNC", "16"))
llm_model_kwargs: dict = field(default_factory=dict)
# storage