Fix: unexpected keyword argument error.

README.md

@@ -114,7 +114,7 @@ print(rag.query("What are the top themes in this story?", param=QueryParam(mode=
 * LightRAG also supports Open AI-like chat/embeddings APIs:
 ```python
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         "solar-mini",

examples/lightrag_api_openai_compatible_demo.py

@@ -33,7 +33,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         LLM_MODEL,

examples/lightrag_api_oracle_demo.py

@@ -50,7 +50,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         LLM_MODEL,

examples/lightrag_azure_openai_demo.py

@@ -30,7 +30,7 @@ os.mkdir(WORKING_DIR)
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     client = AzureOpenAI(
         api_key=AZURE_OPENAI_API_KEY,

examples/lightrag_lmdeploy_demo.py

@@ -12,7 +12,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def lmdeploy_model_complete(
-    prompt=None, system_prompt=None, history_messages=[], **kwargs
+    prompt=None, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     model_name = kwargs["hashing_kv"].global_config["llm_model_name"]
     return await lmdeploy_model_if_cache(

examples/lightrag_openai_compatible_demo.py

@@ -12,7 +12,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         "solar-mini",

examples/lightrag_oracle_demo.py

@@ -27,7 +27,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         CHATMODEL,

examples/lightrag_siliconcloud_demo.py

@@ -12,7 +12,7 @@ if not os.path.exists(WORKING_DIR):
 
 
 async def llm_model_func(
-    prompt, system_prompt=None, history_messages=[], **kwargs
+    prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
 ) -> str:
     return await openai_complete_if_cache(
         "Qwen/Qwen2.5-7B-Instruct",