Add gemini as a partner provider

packages/jupyter-ai-magics/jupyter_ai_magics/partner_providers/gemini.py

@@ -0,0 +1,13 @@
+from jupyter_ai_magics.providers import BaseProvider, EnvAuthStrategy
+from langchain_google_genai import GoogleGenerativeAI
+
+
+class GeminiProvider(BaseProvider, GoogleGenerativeAI):
+    id = "gemini"
+    name = "Gemini"
+    models = [
+        "gemini-pro",
+    ]
+    model_id_key = "model"
+    auth_strategy = EnvAuthStrategy(name="GOOGLE_API_KEY")
+    pypi_package_deps = ["langchain-google-genai"]

packages/jupyter-ai-magics/jupyter_ai_magics/providers.py

@@ -39,7 +39,7 @@
     SagemakerEndpoint,
     Together,
 )
-from langchain_google_genai import GoogleGenerativeAI
+
 
 # this is necessary because `langchain.pydantic_v1.main` does not include
 # `ModelMetaclass`, as it is not listed in `__all__` by the `pydantic.main`
@@ -901,18 +901,3 @@ class QianfanProvider(BaseProvider, QianfanChatEndpoint):
     model_id_key = "model_name"
     pypi_package_deps = ["qianfan"]
     auth_strategy = MultiEnvAuthStrategy(names=["QIANFAN_AK", "QIANFAN_SK"])
-
-
-class GeminiProvider(BaseProvider, GoogleGenerativeAI):
-    id = "gemini"
-    name = "Gemini"
-    models = [
-        "gemini-pro",
-    ]
-    model_id_key = "model_name"
-    pypi_package_deps = ["langchain-google-genai"]
-    auth_strategy = EnvAuthStrategy(name="GOOGLE_API_KEY")
-
-    @classmethod
-    def is_api_key_exc(cls, e: Exception):
-        return False

packages/jupyter-ai-magics/pyproject.toml

@@ -65,6 +65,7 @@ amazon-bedrock-chat = "jupyter_ai_magics:BedrockChatProvider"
 qianfan = "jupyter_ai_magics:QianfanProvider"
 nvidia-chat = "jupyter_ai_magics.partner_providers.nvidia:ChatNVIDIAProvider"
 together-ai = "jupyter_ai_magics:TogetherAIProvider"
+gemini = "jupyter_ai_magics.partner_providers.gemini:GeminiProvider"
 
 [project.entry-points."jupyter_ai.embeddings_model_providers"]
 bedrock = "jupyter_ai_magics:BedrockEmbeddingsProvider"