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Remove query params from cache key generation for keyword extration

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This commit is contained in:
yangdx 2025-08-14 02:36:01 +08:00
parent 9a62101e9d
commit 331dcf0509
2 changed files with 10 additions and 18 deletions
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14
lightrag/operate.py
View file

@ -1747,7 +1747,7 @@ async def kg_query(
query_param.user_prompt or "",
query_param.enable_rerank,
)
cached_response, quantized, min_val, max_val = await handle_cache(
cached_response = await handle_cache(
hashing_kv, args_hash, query, query_param.mode, cache_type="query"
)
if cached_response is not None:
@ -1922,18 +1922,10 @@ async def extract_keywords_only(
args_hash = compute_args_hash(
param.mode,
text,
param.response_type,
param.top_k,
param.chunk_top_k,
param.max_entity_tokens,
param.max_relation_tokens,
param.max_total_tokens,
param.hl_keywords or [],
param.ll_keywords or [],
param.user_prompt or "",
param.enable_rerank,
)
cached_response, quantized, min_val, max_val = await handle_cache(
cached_response = await handle_cache(
hashing_kv, args_hash, text, param.mode, cache_type="keywords"
)
if cached_response is not None:
@ -3020,7 +3012,7 @@ async def naive_query(
query_param.user_prompt or "",
query_param.enable_rerank,
)
cached_response, quantized, min_val, max_val = await handle_cache(
cached_response = await handle_cache(
hashing_kv, args_hash, query, query_param.mode, cache_type="query"
)
if cached_response is not None:

14
lightrag/utils.py
View file

@ -762,27 +762,27 @@ async def handle_cache(
prompt,
mode="default",
cache_type=None,
):
) -> str|None:
"""Generic cache handling function with flattened cache keys"""
if hashing_kv is None:
return None, None, None, None
return None
if mode != "default": # handle cache for all type of query
if not hashing_kv.global_config.get("enable_llm_cache"):
return None, None, None, None
return None
else: # handle cache for entity extraction
if not hashing_kv.global_config.get("enable_llm_cache_for_entity_extract"):
return None, None, None, None
return None
# Use flattened cache key format: {mode}:{cache_type}:{hash}
flattened_key = generate_cache_key(mode, cache_type, args_hash)
cache_entry = await hashing_kv.get_by_id(flattened_key)
if cache_entry:
logger.debug(f"Flattened cache hit(key:{flattened_key})")
return cache_entry["return"], None, None, None
return cache_entry["return"]
logger.debug(f"Cache missed(mode:{mode} type:{cache_type})")
return None, None, None, None
return None
@dataclass
@ -1409,7 +1409,7 @@ async def use_llm_func_with_cache(
# Generate cache key for this LLM call
cache_key = generate_cache_key("default", cache_type, arg_hash)
cached_return, _1, _2, _3 = await handle_cache(
cached_return = await handle_cache(
llm_response_cache,
arg_hash,
_prompt,