Fix linting

lightrag/api/lightrag_server.py

@@ -512,9 +512,7 @@ def create_app(args):
 
         return optimized_azure_openai_model_complete
 
-    def create_optimized_gemini_llm_func(
-        config_cache: LLMConfigCache, args
-    ):
+    def create_optimized_gemini_llm_func(config_cache: LLMConfigCache, args):
         """Create optimized Gemini LLM function with cached configuration"""
 
         async def optimized_gemini_model_complete(

lightrag/llm/binding_options.py

@@ -228,7 +228,7 @@ class BindingOptions:
                 argdef = {
                     "argname": f"{args_prefix}-{field.name}",
                     "env_name": f"{env_var_prefix}{field.name.upper()}",
-                "type": _resolve_optional_type(field.type),
+                    "type": _resolve_optional_type(field.type),
                     "default": default_value,
                     "help": f"{cls._binding_name} -- " + help.get(field.name, ""),
                 }
@@ -498,7 +498,7 @@ class GeminiLLMOptions(BindingOptions):
         "candidate_count": "Number of candidates returned per request",
         "presence_penalty": "Penalty for token presence (-2.0 to 2.0)",
         "frequency_penalty": "Penalty for token frequency (-2.0 to 2.0)",
-        "stop_sequences": 'Stop sequences (JSON array of strings, e.g., \'["END"]\')',
+        "stop_sequences": "Stop sequences (JSON array of strings, e.g., '[\"END\"]')",
         "response_mime_type": "Desired MIME type for the response (e.g., application/json)",
         "safety_settings": "JSON object with Gemini safety settings overrides",
         "system_instruction": "Default system instruction applied to every request",

lightrag/llm/gemini.py

@@ -191,7 +191,9 @@ async def gemini_complete_if_cache(
                     usage = getattr(chunk, "usage_metadata", None)
                     if usage is not None:
                         usage_container["usage"] = usage
-                    text_piece = getattr(chunk, "text", None) or _extract_response_text(chunk)
+                    text_piece = getattr(chunk, "text", None) or _extract_response_text(
+                        chunk
+                    )
                     if text_piece:
                         loop.call_soon_threadsafe(queue.put_nowait, text_piece)
                 loop.call_soon_threadsafe(queue.put_nowait, None)

requirements-offline-llm.txt

@@ -10,9 +10,9 @@
 # LLM provider dependencies (with version constraints matching pyproject.toml)
 aioboto3>=12.0.0,<16.0.0
 anthropic>=0.18.0,<1.0.0
+google-genai>=1.0.0,<2.0.0
 llama-index>=0.9.0,<1.0.0
 ollama>=0.1.0,<1.0.0
 openai>=1.0.0,<3.0.0
-google-genai>=1.0.0,<2.0.0
 voyageai>=0.2.0,<1.0.0
 zhipuai>=2.0.0,<3.0.0

requirements-offline.txt

@@ -13,13 +13,13 @@ anthropic>=0.18.0,<1.0.0
 
 # Storage backend dependencies
 asyncpg>=0.29.0,<1.0.0
+google-genai>=1.0.0,<2.0.0
 
 # Document processing dependencies
 llama-index>=0.9.0,<1.0.0
 neo4j>=5.0.0,<7.0.0
 ollama>=0.1.0,<1.0.0
 openai>=1.0.0,<3.0.0
-google-genai>=1.0.0,<2.0.0
 openpyxl>=3.0.0,<4.0.0
 pycryptodome>=3.0.0,<4.0.0
 pymilvus>=2.6.2,<3.0.0