Use GoogleModel instead of GeminiModel on inference

pydantic_ai_slim/pydantic_ai/models/__init__.py

@@ -555,9 +555,9 @@ def infer_model(model: Model | KnownModelName | str) -> Model:
 
         return OpenAIModel(model_name, provider=provider)
     elif provider in ('google-gla', 'google-vertex'):
-        from .gemini import GeminiModel
+        from .google import GoogleModel
 
-        return GeminiModel(model_name, provider=provider)
+        return GoogleModel(model_name, provider=provider)
     elif provider == 'groq':
         from .groq import GroqModel
 

pydantic_ai_slim/pydantic_ai/providers/google.py

@@ -84,7 +84,7 @@ def __init__(
         """
         if client is None:
             # NOTE: We are keeping GEMINI_API_KEY for backwards compatibility.
-            api_key = api_key or os.environ.get('GOOGLE_API_KEY')
+            api_key = api_key or os.getenv('GOOGLE_API_KEY') or os.getenv('GEMINI_API_KEY')
 
             if vertexai is None:  # pragma: lax no cover
                 vertexai = bool(location or project or credentials)

tests/models/test_google.py

@@ -307,18 +307,6 @@ async def test_google_model_thinking_config(allow_model_requests: None, google_p
     assert result.output == snapshot('The capital of France is **Paris**.')
 
 
-@pytest.mark.skipif(
-    not os.getenv('CI', False), reason='Requires properly configured local google vertex config to pass'
-)
-async def test_google_model_vertex_labels(allow_model_requests: None):  # pragma: lax no cover
-    provider = GoogleProvider(location='global', project='pydantic-ai')
-    model = GoogleModel('gemini-2.0-flash', provider=provider)
-    settings = GoogleModelSettings(google_labels={'environment': 'test', 'team': 'analytics'})
-    agent = Agent(model=model, system_prompt='You are a helpful chatbot.', model_settings=settings)
-    result = await agent.run('What is the capital of France?')
-    assert result.output == snapshot('The capital of France is Paris.\n')
-
-
 async def test_google_model_gla_labels_raises_value_error(allow_model_requests: None, google_provider: GoogleProvider):
     model = GoogleModel('gemini-2.0-flash', provider=google_provider)
     settings = GoogleModelSettings(google_labels={'environment': 'test', 'team': 'analytics'})
@@ -360,6 +348,18 @@ async def test_google_model_vertex_provider(allow_model_requests: None):
     assert result.output == snapshot('The capital of France is Paris.\n')
 
 
+@pytest.mark.skipif(
+    not os.getenv('CI', False), reason='Requires properly configured local google vertex config to pass'
+)
+async def test_google_model_vertex_labels(allow_model_requests: None):  # pragma: lax no cover
+    provider = GoogleProvider(location='global', project='pydantic-ai')
+    model = GoogleModel('gemini-2.0-flash', provider=provider)
+    settings = GoogleModelSettings(google_labels={'environment': 'test', 'team': 'analytics'})
+    agent = Agent(model=model, system_prompt='You are a helpful chatbot.', model_settings=settings)
+    result = await agent.run('What is the capital of France?')
+    assert result.output == snapshot('The capital of France is Paris.\n')
+
+
 async def test_google_model_iter_stream(allow_model_requests: None, google_provider: GoogleProvider):
     model = GoogleModel('gemini-2.0-flash', provider=google_provider)
     agent = Agent(model=model, system_prompt='You are a helpful chatbot.')

tests/models/test_model.py

@@ -7,29 +7,15 @@
 
 from ..conftest import TestEnv
 
+# TODO(Marcelo): We need to add Vertex AI to the test cases.
+
 TEST_CASES = [
     ('OPENAI_API_KEY', 'openai:gpt-3.5-turbo', 'gpt-3.5-turbo', 'openai', 'openai', 'OpenAIModel'),
     ('OPENAI_API_KEY', 'gpt-3.5-turbo', 'gpt-3.5-turbo', 'openai', 'openai', 'OpenAIModel'),
     ('OPENAI_API_KEY', 'o1', 'o1', 'openai', 'openai', 'OpenAIModel'),
     ('AZURE_OPENAI_API_KEY', 'azure:gpt-3.5-turbo', 'gpt-3.5-turbo', 'azure', 'azure', 'OpenAIModel'),
-    ('GEMINI_API_KEY', 'google-gla:gemini-1.5-flash', 'gemini-1.5-flash', 'google-gla', 'gemini', 'GeminiModel'),
-    ('GEMINI_API_KEY', 'gemini-1.5-flash', 'gemini-1.5-flash', 'google-gla', 'gemini', 'GeminiModel'),
-    (
-        'GEMINI_API_KEY',
-        'google-vertex:gemini-1.5-flash',
-        'gemini-1.5-flash',
-        'google-vertex',
-        'vertexai',
-        'GeminiModel',
-    ),
-    (
-        'GEMINI_API_KEY',
-        'vertexai:gemini-1.5-flash',
-        'gemini-1.5-flash',
-        'google-vertex',
-        'vertexai',
-        'GeminiModel',
-    ),
+    ('GEMINI_API_KEY', 'google-gla:gemini-1.5-flash', 'gemini-1.5-flash', 'google-gla', 'google', 'GoogleModel'),
+    ('GEMINI_API_KEY', 'gemini-1.5-flash', 'gemini-1.5-flash', 'google-gla', 'google', 'GoogleModel'),
     (
         'ANTHROPIC_API_KEY',
         'anthropic:claude-3-5-haiku-latest',

tests/test_agent.py

@@ -1536,11 +1536,14 @@ def empty(m: list[ModelMessage], _info: AgentInfo) -> ModelResponse:
 
 
 def test_model_requests_blocked(env: TestEnv):
-    env.set('GEMINI_API_KEY', 'foobar')
-    agent = Agent('google-gla:gemini-1.5-flash', output_type=tuple[str, str], defer_model_check=True)
+    try:
+        env.set('GEMINI_API_KEY', 'foobar')
+        agent = Agent('google-gla:gemini-1.5-flash', output_type=tuple[str, str], defer_model_check=True)
 
-    with pytest.raises(RuntimeError, match='Model requests are not allowed, since ALLOW_MODEL_REQUESTS is False'):
-        agent.run_sync('Hello')
+        with pytest.raises(RuntimeError, match='Model requests are not allowed, since ALLOW_MODEL_REQUESTS is False'):
+            agent.run_sync('Hello')
+    except ImportError:  # pragma: lax no cover
+        pytest.skip('google-genai not installed')
 
 
 def test_override_model(env: TestEnv):