Prefix all models with provider for consistency (#593)

Co-authored-by: Samuel Colvin <[email protected]>

docs/models.md

@@ -184,10 +184,14 @@ You can then use [`GeminiModel`][pydantic_ai.models.gemini.GeminiModel] by name:
 ```python {title="gemini_model_by_name.py"}
 from pydantic_ai import Agent
 
-agent = Agent('gemini-1.5-flash')
+agent = Agent('google-gla:gemini-1.5-flash')
 ...
 ```
 
+!!! note
+    The `google-gla` provider prefix represents the [Google **G**enerative **L**anguage **A**PI](https://ai.google.dev/api/all-methods) for `GeminiModel`s.
+    `google-vertex` is used with [Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models) for `VertexAIModel`s.
+
 Or initialise the model directly with just the model name:
 
 ```python {title="gemini_model_init.py"}

examples/pydantic_ai_examples/sql_gen.py

@@ -93,7 +93,7 @@ class InvalidRequest(BaseModel):
 
 Response: TypeAlias = Union[Success, InvalidRequest]
 agent: Agent[Deps, Response] = Agent(
-    'gemini-1.5-flash',
+    'google-gla:gemini-1.5-flash',
     # Type ignore while we wait for PEP-0747, nonetheless unions will work fine everywhere else
     result_type=Response,  # type: ignore
     deps_type=Deps,

examples/pydantic_ai_examples/stream_markdown.py

@@ -25,7 +25,7 @@
 
 # models to try, and the appropriate env var
 models: list[tuple[KnownModelName, str]] = [
-    ('gemini-1.5-flash', 'GEMINI_API_KEY'),
+    ('google-gla:gemini-1.5-flash', 'GEMINI_API_KEY'),
     ('openai:gpt-4o-mini', 'OPENAI_API_KEY'),
     ('groq:llama-3.1-70b-versatile', 'GROQ_API_KEY'),
 ]

pydantic_ai_slim/pydantic_ai/models/__init__.py

@@ -48,13 +48,12 @@
     'groq:mixtral-8x7b-32768',
     'groq:gemma2-9b-it',
     'groq:gemma-7b-it',
-    'gemini-1.5-flash',
-    'gemini-1.5-pro',
-    'gemini-2.0-flash-exp',
-    'vertexai:gemini-1.5-flash',
-    'vertexai:gemini-1.5-pro',
-    # since mistral models are supported by other providers (e.g. ollama), and some of their models (e.g. "codestral")
-    # don't start with "mistral", we add the "mistral:" prefix to all to be explicit
+    'google-gla:gemini-1.5-flash',
+    'google-gla:gemini-1.5-pro',
+    'google-gla:gemini-2.0-flash-exp',
+    'google-vertex:gemini-1.5-flash',
+    'google-vertex:gemini-1.5-pro',
+    'google-vertex:gemini-2.0-flash-exp',
     'mistral:mistral-small-latest',
     'mistral:mistral-large-latest',
     'mistral:codestral-latest',
@@ -76,9 +75,9 @@
     'ollama:qwen2',
     'ollama:qwen2.5',
     'ollama:starcoder2',
-    'claude-3-5-haiku-latest',
-    'claude-3-5-sonnet-latest',
-    'claude-3-opus-latest',
+    'anthropic:claude-3-5-haiku-latest',
+    'anthropic:claude-3-5-sonnet-latest',
+    'anthropic:claude-3-opus-latest',
     'test',
 ]
 """Known model names that can be used with the `model` parameter of [`Agent`][pydantic_ai.Agent].
@@ -274,6 +273,15 @@ def infer_model(model: Model | KnownModelName) -> Model:
         from .openai import OpenAIModel
 
         return OpenAIModel(model[7:])
+    elif model.startswith(('gpt', 'o1')):
+        from .openai import OpenAIModel
+
+        return OpenAIModel(model)
+    elif model.startswith('google-gla'):
+        from .gemini import GeminiModel
+
+        return GeminiModel(model[11:])  # pyright: ignore[reportArgumentType]
+    # backwards compatibility with old model names (ex, gemini-1.5-flash -> google-gla:gemini-1.5-flash)
     elif model.startswith('gemini'):
         from .gemini import GeminiModel
 
@@ -283,6 +291,11 @@ def infer_model(model: Model | KnownModelName) -> Model:
         from .groq import GroqModel
 
         return GroqModel(model[5:])  # pyright: ignore[reportArgumentType]
+    elif model.startswith('google-vertex'):
+        from .vertexai import VertexAIModel
+
+        return VertexAIModel(model[14:])  # pyright: ignore[reportArgumentType]
+    # backwards compatibility with old model names (ex, vertexai:gemini-1.5-flash -> google-vertex:gemini-1.5-flash)
     elif model.startswith('vertexai:'):
         from .vertexai import VertexAIModel
 
@@ -295,6 +308,11 @@ def infer_model(model: Model | KnownModelName) -> Model:
         from .ollama import OllamaModel
 
         return OllamaModel(model[7:])
+    elif model.startswith('anthropic'):
+        from .anthropic import AnthropicModel
+
+        return AnthropicModel(model[10:])
+    # backwards compatibility with old model names (ex, claude-3-5-sonnet-latest -> anthropic:claude-3-5-sonnet-latest)
     elif model.startswith('claude'):
         from .anthropic import AnthropicModel
 

pydantic_ai_slim/pydantic_ai/models/anthropic.py

@@ -136,7 +136,7 @@ async def agent_model(
         )
 
     def name(self) -> str:
-        return self.model_name
+        return f'anthropic:{self.model_name}'
 
     @staticmethod
     def _map_tool_definition(f: ToolDefinition) -> ToolParam:

pydantic_ai_slim/pydantic_ai/models/gemini.py

@@ -111,7 +111,7 @@ async def agent_model(
         )
 
     def name(self) -> str:
-        return self.model_name
+        return f'google-gla:{self.model_name}'
 
 
 class AuthProtocol(Protocol):

pydantic_ai_slim/pydantic_ai/models/vertexai.py

@@ -164,7 +164,7 @@ async def ainit(self) -> tuple[str, BearerTokenAuth]:
         return url, auth
 
     def name(self) -> str:
-        return f'vertexai:{self.model_name}'
+        return f'google-vertex:{self.model_name}'
 
 
 # pyright: reportUnknownMemberType=false

tests/models/test_anthropic.py

@@ -45,7 +45,7 @@
 def test_init():
     m = AnthropicModel('claude-3-5-haiku-latest', api_key='foobar')
     assert m.client.api_key == 'foobar'
-    assert m.name() == 'claude-3-5-haiku-latest'
+    assert m.name() == 'anthropic:claude-3-5-haiku-latest'
 
 
 @dataclass

tests/models/test_model.py

@@ -1,43 +1,84 @@
+from importlib import import_module
+
 import pytest
 
 from pydantic_ai import UserError
 from pydantic_ai.models import infer_model
-from pydantic_ai.models.gemini import GeminiModel
 
-from ..conftest import TestEnv, try_import
+from ..conftest import TestEnv
+
+TEST_CASES = [
+    ('OPENAI_API_KEY', 'openai:gpt-3.5-turbo', 'openai:gpt-3.5-turbo', 'openai', 'OpenAIModel'),
+    ('OPENAI_API_KEY', 'gpt-3.5-turbo', 'openai:gpt-3.5-turbo', 'openai', 'OpenAIModel'),
+    ('OPENAI_API_KEY', 'o1', 'openai:o1', 'openai', 'OpenAIModel'),
+    ('GEMINI_API_KEY', 'google-gla:gemini-1.5-flash', 'google-gla:gemini-1.5-flash', 'gemini', 'GeminiModel'),
+    ('GEMINI_API_KEY', 'gemini-1.5-flash', 'google-gla:gemini-1.5-flash', 'gemini', 'GeminiModel'),
+    (
+        'GEMINI_API_KEY',
+        'google-vertex:gemini-1.5-flash',
+        'google-vertex:gemini-1.5-flash',
+        'vertexai',
+        'VertexAIModel',
+    ),
+    (
+        'GEMINI_API_KEY',
+        'vertexai:gemini-1.5-flash',
+        'google-vertex:gemini-1.5-flash',
+        'vertexai',
+        'VertexAIModel',
+    ),
+    (
+        'ANTHROPIC_API_KEY',
+        'anthropic:claude-3-5-haiku-latest',
+        'anthropic:claude-3-5-haiku-latest',
+        'anthropic',
+        'AnthropicModel',
+    ),
+    (
+        'ANTHROPIC_API_KEY',
+        'claude-3-5-haiku-latest',
+        'anthropic:claude-3-5-haiku-latest',
+        'anthropic',
+        'AnthropicModel',
+    ),
+    (
+        'GROQ_API_KEY',
+        'groq:llama-3.3-70b-versatile',
+        'groq:llama-3.3-70b-versatile',
+        'groq',
+        'GroqModel',
+    ),
+    ('OLLAMA_API_KEY', 'ollama:llama3', 'ollama:llama3', 'ollama', 'OllamaModel'),
+    (
+        'MISTRAL_API_KEY',
+        'mistral:mistral-small-latest',
+        'mistral:mistral-small-latest',
+        'mistral',
+        'MistralModel',
+    ),
+]
 
-with try_import() as openai_imports_successful:
-    from pydantic_ai.models.openai import OpenAIModel
 
-with try_import() as vertexai_imports_successful:
-    from pydantic_ai.models.vertexai import VertexAIModel
+@pytest.mark.parametrize('mock_api_key, model_name, expected_model_name, module_name, model_class_name', TEST_CASES)
+def test_infer_model(
+    env: TestEnv, mock_api_key: str, model_name: str, expected_model_name: str, module_name: str, model_class_name: str
+):
+    try:
+        model_module = import_module(f'pydantic_ai.models.{module_name}')
+        expected_model = getattr(model_module, model_class_name)
+    except ImportError:
+        pytest.skip(f'{model_name} dependencies not installed')
 
+    env.set(mock_api_key, 'via-env-var')
 
-@pytest.mark.skipif(not openai_imports_successful(), reason='openai not installed')
-def test_infer_str_openai(env: TestEnv):
-    env.set('OPENAI_API_KEY', 'via-env-var')
-    m = infer_model('openai:gpt-3.5-turbo')
-    assert isinstance(m, OpenAIModel)
-    assert m.name() == 'openai:gpt-3.5-turbo'
+    m = infer_model(model_name)  # pyright: ignore[reportArgumentType]
+    assert isinstance(m, expected_model)
+    assert m.name() == expected_model_name
 
     m2 = infer_model(m)
     assert m2 is m
 
 
-def test_infer_str_gemini(env: TestEnv):
-    env.set('GEMINI_API_KEY', 'via-env-var')
-    m = infer_model('gemini-1.5-flash')
-    assert isinstance(m, GeminiModel)
-    assert m.name() == 'gemini-1.5-flash'
-
-
-@pytest.mark.skipif(not vertexai_imports_successful(), reason='google-auth not installed')
-def test_infer_vertexai(env: TestEnv):
-    m = infer_model('vertexai:gemini-1.5-flash')
-    assert isinstance(m, VertexAIModel)
-    assert m.name() == 'vertexai:gemini-1.5-flash'
-
-
 def test_infer_str_unknown():
     with pytest.raises(UserError, match='Unknown model: foobar'):
         infer_model('foobar')  # pyright: ignore[reportArgumentType]

tests/models/test_vertexai.py

@@ -40,7 +40,7 @@ async def test_init_service_account(tmp_path: Path, allow_model_requests: None):
         'publishers/google/models/gemini-1.5-flash:'
     )
     assert model.auth is not None
-    assert model.name() == snapshot('vertexai:gemini-1.5-flash')
+    assert model.name() == snapshot('google-vertex:gemini-1.5-flash')
 
 
 class NoOpCredentials:
@@ -67,7 +67,7 @@ async def test_init_env(mocker: MockerFixture, allow_model_requests: None):
         'publishers/google/models/gemini-1.5-flash:'
     )
     assert model.auth is not None
-    assert model.name() == snapshot('vertexai:gemini-1.5-flash')
+    assert model.name() == snapshot('google-vertex:gemini-1.5-flash')
 
     await model.agent_model(function_tools=[], allow_text_result=True, result_tools=[])
     assert model.url is not None

tests/test_agent.py

@@ -780,15 +780,15 @@ def empty(m: list[ModelMessage], _info: AgentInfo) -> ModelResponse:
 
 def test_model_requests_blocked(env: TestEnv, set_event_loop: None):
     env.set('GEMINI_API_KEY', 'foobar')
-    agent = Agent('gemini-1.5-flash', result_type=tuple[str, str], defer_model_check=True)
+    agent = Agent('google-gla:gemini-1.5-flash', result_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')
 
 
 def test_override_model(env: TestEnv, set_event_loop: None):
     env.set('GEMINI_API_KEY', 'foobar')
-    agent = Agent('gemini-1.5-flash', result_type=tuple[int, str], defer_model_check=True)
+    agent = Agent('google-gla:gemini-1.5-flash', result_type=tuple[int, str], defer_model_check=True)
 
     with agent.override(model='test'):
         result = agent.run_sync('Hello')