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Fix linting

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This commit is contained in:
yangdx
2025-04-10 03:58:04 +08:00
parent 8d858da4d0
commit 496f87a1e6
2 changed files with 7 additions and 8 deletions
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3
lightrag/operate.py
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@@ -148,7 +148,7 @@ async def _handle_entity_relation_summary(
# Use LLM function with cache # Use LLM function with cache
summary = await use_llm_func_with_cache( summary = await use_llm_func_with_cache(
use_prompt, use_prompt,
use_llm_func, use_llm_func,
llm_response_cache=llm_response_cache, llm_response_cache=llm_response_cache,
max_tokens=summary_max_tokens, max_tokens=summary_max_tokens,
@@ -446,7 +446,6 @@ async def extract_entities(
pipeline_status_lock=None, pipeline_status_lock=None,
llm_response_cache: BaseKVStorage | None = None, llm_response_cache: BaseKVStorage | None = None,
) -> None: ) -> None:
use_llm_func: callable = global_config["llm_model_func"] use_llm_func: callable = global_config["llm_model_func"]
entity_extract_max_gleaning = global_config["entity_extract_max_gleaning"] entity_extract_max_gleaning = global_config["entity_extract_max_gleaning"]

12
lightrag/utils.py
View File

@@ -913,18 +913,18 @@ def lazy_external_import(module_name: str, class_name: str) -> Callable[..., Any
async def use_llm_func_with_cache( async def use_llm_func_with_cache(
input_text: str, input_text: str,
use_llm_func: callable, use_llm_func: callable,
llm_response_cache: 'BaseKVStorage | None' = None, llm_response_cache: "BaseKVStorage | None" = None,
max_tokens: int = None, max_tokens: int = None,
history_messages: list[dict[str, str]] = None, history_messages: list[dict[str, str]] = None,
cache_type: str = "extract" cache_type: str = "extract",
) -> str: ) -> str:
"""Call LLM function with cache support """Call LLM function with cache support
If cache is available and enabled (determined by handle_cache based on mode), If cache is available and enabled (determined by handle_cache based on mode),
retrieve result from cache; otherwise call LLM function and save result to cache. retrieve result from cache; otherwise call LLM function and save result to cache.
Args: Args:
input_text: Input text to send to LLM input_text: Input text to send to LLM
use_llm_func: LLM function to call use_llm_func: LLM function to call
@@ -932,7 +932,7 @@ async def use_llm_func_with_cache(
max_tokens: Maximum tokens for generation max_tokens: Maximum tokens for generation
history_messages: History messages list history_messages: History messages list
cache_type: Type of cache cache_type: Type of cache
Returns: Returns:
LLM response text LLM response text
""" """