From 2d048b5eb09bc80553ad3c34c6e5abac9e25f4e1 Mon Sep 17 00:00:00 2001
From: GG <1592860538@qq.com>
Date: Tue, 17 Dec 2024 16:44:42 +0800
Subject: [PATCH] =?UTF-8?q?fix(llm):=20hashing=5Fkv=E5=88=9D=E5=A7=8B?=
 =?UTF-8?q?=E5=8C=96=E4=BF=AE=E5=A4=8D?=
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-hybrid模式对hashing_kv的依赖不止global_config，干脆复用llm_response_cache的初始化结构
---
 lightrag/lightrag.py | 27 ++++++++++++++++++++++++---
 1 file changed, 24 insertions(+), 3 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index a32cf621..69820d9a 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -252,7 +252,14 @@ def __post_init__(self):
         self.llm_model_func = limit_async_func_call(self.llm_model_max_async)(
             partial(
                 self.llm_model_func,
-                hashing_kv=self.llm_response_cache,
+                hashing_kv=self.llm_response_cache
+                if self.llm_response_cache
+                and hasattr(self.llm_response_cache, "global_config")
+                else self.key_string_value_json_storage_cls(
+                    namespace="llm_response_cache",
+                    global_config=asdict(self),
+                    embedding_func=None,
+                ),
                 **self.llm_model_kwargs,
             )
         )
@@ -515,7 +522,14 @@ async def aquery(self, query: str, param: QueryParam = QueryParam()):
                 self.text_chunks,
                 param,
                 asdict(self),
-                hashing_kv=self.llm_response_cache,
+                hashing_kv=self.llm_response_cache
+                if self.llm_response_cache
+                and hasattr(self.llm_response_cache, "global_config")
+                else self.key_string_value_json_storage_cls(
+                    namespace="llm_response_cache",
+                    global_config=asdict(self),
+                    embedding_func=None,
+                ),
             )
         elif param.mode == "naive":
             response = await naive_query(
@@ -524,7 +538,14 @@ async def aquery(self, query: str, param: QueryParam = QueryParam()):
                 self.text_chunks,
                 param,
                 asdict(self),
-                hashing_kv=self.llm_response_cache,
+                hashing_kv=self.llm_response_cache
+                if self.llm_response_cache
+                and hasattr(self.llm_response_cache, "global_config")
+                else self.key_string_value_json_storage_cls(
+                    namespace="llm_response_cache",
+                    global_config=asdict(self),
+                    embedding_func=None,
+                ),
             )
         else:
             raise ValueError(f"Unknown mode {param.mode}")