Refactor keyword_extraction from kwargs to explicit parameter

• Add keyword_extraction param to functions
• Remove kwargs.pop() calls
• Update function signatures
• Improve parameter documentation
• Make parameter handling consistent

lightrag/llm/openai.py

@@ -140,6 +140,7 @@ async def openai_complete_if_cache(
     token_tracker: Any | None = None,
     stream: bool | None = None,
     timeout: int | None = None,
+    keyword_extraction: bool = False,
     **kwargs: Any,
 ) -> str:
     """Complete a prompt using OpenAI's API with caching support and Chain of Thought (COT) integration.
@@ -171,12 +172,13 @@ async def openai_complete_if_cache(
         enable_cot: Whether to enable Chain of Thought (COT) processing. Default is False.
         stream: Whether to stream the response. Default is False.
         timeout: Request timeout in seconds. Default is None.
+        keyword_extraction: Whether to enable keyword extraction mode. When True, triggers
+            special response formatting for keyword extraction. Default is False.
         **kwargs: Additional keyword arguments to pass to the OpenAI API.
             Special kwargs:
             - openai_client_configs: Dict of configuration options for the AsyncOpenAI client.
                 These will be passed to the client constructor but will be overridden by
                 explicit parameters (api_key, base_url).
-            - keyword_extraction: Will be removed from kwargs before passing to OpenAI.
 
     Returns:
         The completed text (with integrated COT content if available) or an async iterator
@@ -197,7 +199,6 @@ async def openai_complete_if_cache(
 
     # Remove special kwargs that shouldn't be passed to OpenAI
     kwargs.pop("hashing_kv", None)
-    kwargs.pop("keyword_extraction", None)
 
     # Extract client configuration options
     client_configs = kwargs.pop("openai_client_configs", {})
@@ -521,7 +522,6 @@ async def openai_complete(
 ) -> Union[str, AsyncIterator[str]]:
     if history_messages is None:
         history_messages = []
-    keyword_extraction = kwargs.pop("keyword_extraction", None)
     if keyword_extraction:
         kwargs["response_format"] = "json"
     model_name = kwargs["hashing_kv"].global_config["llm_model_name"]
@@ -530,6 +530,7 @@ async def openai_complete(
         prompt,
         system_prompt=system_prompt,
         history_messages=history_messages,
+        keyword_extraction=keyword_extraction,
         **kwargs,
     )
 
@@ -544,7 +545,6 @@ async def gpt_4o_complete(
 ) -> str:
     if history_messages is None:
         history_messages = []
-    keyword_extraction = kwargs.pop("keyword_extraction", None)
     if keyword_extraction:
         kwargs["response_format"] = GPTKeywordExtractionFormat
     return await openai_complete_if_cache(
@@ -553,6 +553,7 @@ async def gpt_4o_complete(
         system_prompt=system_prompt,
         history_messages=history_messages,
         enable_cot=enable_cot,
+        keyword_extraction=keyword_extraction,
         **kwargs,
     )
 
@@ -567,7 +568,6 @@ async def gpt_4o_mini_complete(
 ) -> str:
     if history_messages is None:
         history_messages = []
-    keyword_extraction = kwargs.pop("keyword_extraction", None)
     if keyword_extraction:
         kwargs["response_format"] = GPTKeywordExtractionFormat
     return await openai_complete_if_cache(
@@ -576,6 +576,7 @@ async def gpt_4o_mini_complete(
         system_prompt=system_prompt,
         history_messages=history_messages,
         enable_cot=enable_cot,
+        keyword_extraction=keyword_extraction,
         **kwargs,
     )
 
@@ -590,13 +591,13 @@ async def nvidia_openai_complete(
 ) -> str:
     if history_messages is None:
         history_messages = []
-    kwargs.pop("keyword_extraction", None)
     result = await openai_complete_if_cache(
         "nvidia/llama-3.1-nemotron-70b-instruct",  # context length 128k
         prompt,
         system_prompt=system_prompt,
         history_messages=history_messages,
         enable_cot=enable_cot,
+        keyword_extraction=keyword_extraction,
         base_url="https://integrate.api.nvidia.com/v1",
         **kwargs,
     )