gmakstutis/LightRAG
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Convert embedding_token_limit from property to field with __post_init__

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• Remove property decorator
• Add field with init=False
• Set value in __post_init__ method
• embedding_token_limit is now in config dictionary
This commit is contained in:
yangdx 2025-11-14 20:58:41 +08:00
parent 14a6c24ed7
commit f0254773c6
1 changed files with 8 additions and 6 deletions
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14
lightrag/lightrag.py
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@ -277,12 +277,8 @@ class LightRAG:
embedding_func: EmbeddingFunc | None = field(default=None)
"""Function for computing text embeddings. Must be set before use."""
@property
def embedding_token_limit(self) -> int | None:
"""Get the token limit for embedding model from embedding_func."""
if self.embedding_func and hasattr(self.embedding_func, "max_token_size"):
return self.embedding_func.max_token_size
return None
embedding_token_limit: int | None = field(default=None, init=False)
"""Token limit for embedding model. Set automatically from embedding_func.max_token_size in __post_init__."""
embedding_batch_num: int = field(default=int(os.getenv("EMBEDDING_BATCH_NUM", 10)))
"""Batch size for embedding computations."""
@ -533,6 +529,12 @@ class LightRAG:
queue_name="Embedding func",
)(self.embedding_func)
# Initialize embedding_token_limit from embedding_func
if self.embedding_func and hasattr(self.embedding_func, "max_token_size"):
self.embedding_token_limit = self.embedding_func.max_token_size
else:
self.embedding_token_limit = None
# Initialize all storages
self.key_string_value_json_storage_cls: type[BaseKVStorage] = (
self._get_storage_class(self.kv_storage)