feat(gemini): simplify config for Gemini clients (#679)

The cross_encoder for Gemini already supported passing in a custom client.

I replicated the same input pattern to embedder and llm_client.

The value is, you can support custom API endpoints and other options like below:

        cross_encoder=GeminiRerankerClient(
            client=genai.Client(
                api_key=os.environ.get('GOOGLE_GENAI_API_KEY'),
                http_options=types.HttpOptions(api_version='v1alpha')),
            config=LLMConfig(
                model="gemini-2.5-flash-lite-preview-06-17"
            )
        ))

graphiti_core/cross_encoder/gemini_reranker_client.py

@@ -41,6 +41,9 @@ DEFAULT_MODEL = 'gemini-2.5-flash-lite-preview-06-17'
 
 
 class GeminiRerankerClient(CrossEncoderClient):
+    """
+    Google Gemini Reranker Client
+    """
     def __init__(
         self,
         config: LLMConfig | None = None,
@@ -57,7 +60,6 @@ class GeminiRerankerClient(CrossEncoderClient):
             config (LLMConfig | None): The configuration for the LLM client, including API key, model, base URL, temperature, and max tokens.
             client (genai.Client | None): An optional async client instance to use. If not provided, a new genai.Client is created.
         """
-
         if config is None:
             config = LLMConfig()
 

graphiti_core/embedder/gemini.py

@@ -46,16 +46,27 @@ class GeminiEmbedder(EmbedderClient):
     """
     Google Gemini Embedder Client
     """
+    def __init__(
+        self,
+        config: GeminiEmbedderConfig | None = None,
+        client: 'genai.Client | None' = None,
+    ):
+        """
+        Initialize the GeminiEmbedder with the provided configuration and client.
 
-    def __init__(self, config: GeminiEmbedderConfig | None = None):
+        Args:
+            config (GeminiEmbedderConfig | None): The configuration for the GeminiEmbedder, including API key, model, base URL, temperature, and max tokens.
+            client (genai.Client | None): An optional async client instance to use. If not provided, a new genai.Client is created.
+        """
         if config is None:
             config = GeminiEmbedderConfig()
+
         self.config = config
 
-        # Configure the Gemini API
+        if client is None:
-        self.client = genai.Client(
+            self.client = genai.Client(api_key=config.api_key)
-            api_key=config.api_key,
+        else:
-        )
+            self.client = client
 
     async def create(
         self, input_data: str | list[str] | Iterable[int] | Iterable[Iterable[int]]

graphiti_core/llm_client/gemini_client.py

@@ -76,6 +76,7 @@ class GeminiClient(LLMClient):
         cache: bool = False,
         max_tokens: int = DEFAULT_MAX_TOKENS,
         thinking_config: types.ThinkingConfig | None = None,
+        client: 'genai.Client | None' = None,
     ):
         """
         Initialize the GeminiClient with the provided configuration, cache setting, and optional thinking config.
@@ -85,7 +86,7 @@ class GeminiClient(LLMClient):
             cache (bool): Whether to use caching for responses. Defaults to False.
             thinking_config (types.ThinkingConfig | None): Optional thinking configuration for models that support it.
                 Only use with models that support thinking (gemini-2.5+). Defaults to None.
-
+            client (genai.Client | None): An optional async client instance to use. If not provided, a new genai.Client is created.
         """
         if config is None:
             config = LLMConfig()
@@ -93,10 +94,12 @@ class GeminiClient(LLMClient):
         super().__init__(config, cache)
 
         self.model = config.model
-        # Configure the Gemini API
+
-        self.client = genai.Client(
+        if client is None:
-            api_key=config.api_key,
+            self.client = genai.Client(api_key=config.api_key)
-        )
+        else:
+            self.client = client
+
         self.max_tokens = max_tokens
         self.thinking_config = thinking_config