fix lint

lightrag/llm/openai.py

@@ -50,34 +50,38 @@ def create_openai_async_client(
     client_configs: dict[str, Any] = None,
 ) -> AsyncOpenAI:
     """Create an AsyncOpenAI client with the given configuration.
-    
+
     Args:
         api_key: OpenAI API key. If None, uses the OPENAI_API_KEY environment variable.
         base_url: Base URL for the OpenAI API. If None, uses the default OpenAI API URL.
         client_configs: Additional configuration options for the AsyncOpenAI client.
             These will override any default configurations but will be overridden by
             explicit parameters (api_key, base_url).
-            
+
     Returns:
         An AsyncOpenAI client instance.
     """
     if not api_key:
         api_key = os.environ["OPENAI_API_KEY"]
-        
+
     default_headers = {
         "User-Agent": f"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_8) LightRAG/{__api_version__}",
         "Content-Type": "application/json",
     }
-    
+
     if client_configs is None:
         client_configs = {}
-        
+
     # Create a merged config dict with precedence: explicit params > client_configs > defaults
-    merged_configs = {**client_configs, "default_headers": default_headers, "api_key": api_key}
+    merged_configs = {
-    
+        **client_configs,
+        "default_headers": default_headers,
+        "api_key": api_key,
+    }
+
     if base_url is not None:
         merged_configs["base_url"] = base_url
-        
+
     return AsyncOpenAI(**merged_configs)
 
 
@@ -99,7 +103,7 @@ async def openai_complete_if_cache(
     **kwargs: Any,
 ) -> str:
     """Complete a prompt using OpenAI's API with caching support.
-    
+
     Args:
         model: The OpenAI model to use.
         prompt: The prompt to complete.
@@ -114,10 +118,10 @@ async def openai_complete_if_cache(
                 explicit parameters (api_key, base_url).
             - hashing_kv: Will be removed from kwargs before passing to OpenAI.
             - keyword_extraction: Will be removed from kwargs before passing to OpenAI.
-            
+
     Returns:
         The completed text or an async iterator of text chunks if streaming.
-        
+
     Raises:
         InvalidResponseError: If the response from OpenAI is invalid or empty.
         APIConnectionError: If there is a connection error with the OpenAI API.
@@ -133,18 +137,16 @@ async def openai_complete_if_cache(
 
     # Extract client configuration options
     client_configs = kwargs.pop("openai_client_configs", {})
-    
+
     # Create the OpenAI client
     openai_async_client = create_openai_async_client(
-        api_key=api_key,
+        api_key=api_key, base_url=base_url, client_configs=client_configs
-        base_url=base_url,
-        client_configs=client_configs
     )
 
     # Remove special kwargs that shouldn't be passed to OpenAI
     kwargs.pop("hashing_kv", None)
     kwargs.pop("keyword_extraction", None)
-    
+
     # Prepare messages
     messages: list[dict[str, Any]] = []
     if system_prompt:
@@ -337,7 +339,7 @@ async def openai_embed(
     client_configs: dict[str, Any] = None,
 ) -> np.ndarray:
     """Generate embeddings for a list of texts using OpenAI's API.
-    
+
     Args:
         texts: List of texts to embed.
         model: The OpenAI embedding model to use.
@@ -346,10 +348,10 @@ async def openai_embed(
         client_configs: Additional configuration options for the AsyncOpenAI client.
             These will override any default configurations but will be overridden by
             explicit parameters (api_key, base_url).
-            
+
     Returns:
         A numpy array of embeddings, one per input text.
-        
+
     Raises:
         APIConnectionError: If there is a connection error with the OpenAI API.
         RateLimitError: If the OpenAI API rate limit is exceeded.
@@ -357,11 +359,9 @@ async def openai_embed(
     """
     # Create the OpenAI client
     openai_async_client = create_openai_async_client(
-        api_key=api_key,
+        api_key=api_key, base_url=base_url, client_configs=client_configs
-        base_url=base_url,
-        client_configs=client_configs
     )
-    
+
     response = await openai_async_client.embeddings.create(
         model=model, input=texts, encoding_format="float"
     )