Remove typings stubs (#3673)

Author: dsfaccini

Makefile

@@ -43,7 +43,6 @@ typecheck-pyright:
 .PHONY: typecheck-mypy
 typecheck-mypy:
 	uv run mypy
-	uv run mypy typings/ --strict
 
 .PHONY: typecheck
 typecheck: typecheck-pyright ## Run static type checking

pydantic_ai_slim/pydantic_ai/models/outlines.py

@@ -52,15 +52,15 @@
     from outlines.inputs import Chat, Image
     from outlines.models.base import AsyncModel as OutlinesAsyncBaseModel, Model as OutlinesBaseModel
     from outlines.models.llamacpp import LlamaCpp, from_llamacpp
-    from outlines.models.mlxlm import MLXLM, from_mlxlm
+    from outlines.models.mlxlm import MLXLM, from_mlxlm  # pyright: ignore[reportUnknownVariableType]
     from outlines.models.sglang import AsyncSGLang, SGLang, from_sglang
     from outlines.models.transformers import (
         Transformers,
         from_transformers,
     )
     from outlines.models.vllm_offline import (
         VLLMOffline,
-        from_vllm_offline,
+        from_vllm_offline,  # pyright: ignore[reportUnknownVariableType]
     )
     from outlines.types.dsl import JsonSchema
     from PIL import Image as PILImage
@@ -72,7 +72,7 @@
 
 if TYPE_CHECKING:
     import llama_cpp
-    import mlx.nn as nn
+    import mlx.nn as nn  # pyright: ignore[reportMissingImports]
     import transformers
 
 
@@ -157,7 +157,7 @@ def from_llamacpp(
     @classmethod
     def from_mlxlm(  # pragma: no cover
         cls,
-        mlx_model: nn.Module,
+        mlx_model: nn.Module,  # pyright: ignore[reportUnknownParameterType, reportUnknownMemberType]
         mlx_tokenizer: transformers.tokenization_utils.PreTrainedTokenizer,
         *,
         provider: Literal['outlines'] | Provider[OutlinesBaseModel] = 'outlines',
@@ -174,7 +174,7 @@ def from_mlxlm(  # pragma: no cover
             profile: The model profile to use. Defaults to a profile picked by the provider.
             settings: Default model settings for this model instance.
         """
-        outlines_model: OutlinesBaseModel = from_mlxlm(mlx_model, mlx_tokenizer)
+        outlines_model: OutlinesBaseModel = from_mlxlm(mlx_model, mlx_tokenizer)  # pyright: ignore[reportUnknownArgumentType]
         return cls(outlines_model, provider=provider, profile=profile, settings=settings)
 
     @classmethod
@@ -393,7 +393,9 @@ def _format_vllm_offline_inference_kwargs(  # pragma: no cover
         self, model_settings: dict[str, Any]
     ) -> dict[str, Any]:
         """Select the model settings supported by the vLLMOffline model."""
-        from vllm.sampling_params import SamplingParams
+        from vllm.sampling_params import (  # pyright: ignore[reportMissingImports]
+            SamplingParams,  # pyright: ignore[reportUnknownVariableType]
+        )
 
         supported_args = [
             'max_tokens',

pyproject.toml

@@ -147,7 +147,6 @@ include = [
     "clai/**/*.py",
     "tests/**/*.py",
     "docs/**/*.py",
-    "typings/**/*.pyi",
 ]
 
 [tool.ruff.lint]
@@ -195,10 +194,8 @@ quote-style = "single"
 "examples/**/*.py" = ["D101", "D103"]
 "tests/**/*.py" = ["D"]
 "docs/**/*.py" = ["D"]
-"typings/**/*.pyi" = ["F401", "PYI044", "PYI035", "ANN401"]
 
 [tool.pyright]
-stubPath = "typings"
 pythonVersion = "3.12"
 typeCheckingMode = "strict"
 reportMissingTypeStubs = false
@@ -228,7 +225,6 @@ exclude = [
 [tool.mypy]
 files = "tests/typed_agent.py,tests/typed_graph.py"
 strict = true
-mypy_path = "typings"
 
 [tool.pytest.ini_options]
 testpaths = ["tests", "docs/.hooks"]

tests/models/test_outlines.py

@@ -54,11 +54,11 @@
     import llama_cpp
 
 with try_import() as vllm_imports_successful:
-    import vllm
+    import vllm  # pyright: ignore[reportMissingImports]
 
     # We try to load the vllm model to ensure it is available
     try:  # pragma: no lax cover
-        vllm.LLM('microsoft/Phi-3-mini-4k-instruct')
+        vllm.LLM('microsoft/Phi-3-mini-4k-instruct')  # pyright: ignore[reportUnknownMemberType]
     except RuntimeError as e:  # pragma: lax no cover
         if 'Found no NVIDIA driver' in str(e) or 'Device string must not be empty' in str(e):
             # Treat as import failure
@@ -69,7 +69,7 @@
     import openai
 
 with try_import() as mlxlm_imports_successful:
-    import mlx_lm
+    import mlx_lm  # pyright: ignore[reportMissingImports]
 
 
 pytestmark = [
@@ -104,60 +104,64 @@ class MockOutlinesAsyncModel(OutlinesAsyncBaseModel):
         only implemented because they are abstract methods in the OutlinesAsyncModel class.
         """
 
-        async def __call__(self, model_input: Any, output_type: Any, backend: Any, **inference_kwargs: Any) -> str:
+        async def __call__(self, model_input: Any, output_type: Any, backend: Any, **inference_kwargs: Any) -> str:  # pyright: ignore[reportIncompatibleMethodOverride]
             return 'test'
 
-        async def stream(self, model_input: Any, output_type: Any, backend: Any, **inference_kwargs: Any):
+        async def stream(self, model_input: Any, output_type: Any, backend: Any, **inference_kwargs: Any):  # pyright: ignore[reportIncompatibleMethodOverride]
             for _ in range(2):
                 yield 'test'
 
-        async def generate(self, model_input: Any, output_type: Any, **inference_kwargs: Any): ...  # pragma: no cover
+        async def generate(  # pyright: ignore[reportIncompatibleMethodOverride]  # pragma: no cover
+            self, model_input: Any, output_type: Any, **inference_kwargs: Any
+        ): ...
 
-        async def generate_batch(
+        async def generate_batch(  # pyright: ignore[reportIncompatibleMethodOverride]  # pragma: no cover
             self, model_input: Any, output_type: Any, **inference_kwargs: Any
-        ): ...  # pragma: no cover
+        ): ...
 
-        async def generate_stream(
+        async def generate_stream(  # pyright: ignore[reportIncompatibleMethodOverride]  # pragma: no cover
             self, model_input: Any, output_type: Any, **inference_kwargs: Any
-        ): ...  # pragma: no cover
+        ): ...
 
     return OutlinesModel(MockOutlinesAsyncModel(), provider=OutlinesProvider())
 
 
 @pytest.fixture
 def transformers_model() -> OutlinesModel:
-    hf_model = transformers.AutoModelForCausalLM.from_pretrained(
+    hf_model = transformers.AutoModelForCausalLM.from_pretrained(  # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType]
         'erwanf/gpt2-mini',
         device_map='cpu',
     )
-    hf_tokenizer = transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini')
+    hf_tokenizer = transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini')  # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType]
     chat_template = '{% for message in messages %}{{ message.role }}: {{ message.content }}{% endfor %}'
     hf_tokenizer.chat_template = chat_template
     outlines_model = outlines.models.transformers.from_transformers(
-        hf_model,
-        hf_tokenizer,
+        hf_model,  # pyright: ignore[reportUnknownArgumentType]
+        hf_tokenizer,  # pyright: ignore[reportUnknownArgumentType]
     )
     return OutlinesModel(outlines_model, provider=OutlinesProvider())
 
 
 @pytest.fixture
 def transformers_multimodal_model() -> OutlinesModel:
-    hf_model = transformers.LlavaForConditionalGeneration.from_pretrained(
+    hf_model = transformers.LlavaForConditionalGeneration.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
         'trl-internal-testing/tiny-LlavaForConditionalGeneration',
         device_map='cpu',
     )
-    hf_processor = transformers.AutoProcessor.from_pretrained('trl-internal-testing/tiny-LlavaForConditionalGeneration')
+    hf_processor = transformers.AutoProcessor.from_pretrained(  # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType]
+        'trl-internal-testing/tiny-LlavaForConditionalGeneration'
+    )
     outlines_model = outlines.models.transformers.from_transformers(
         hf_model,
-        hf_processor,
+        hf_processor,  # pyright: ignore[reportUnknownArgumentType]
     )
     return OutlinesModel(outlines_model, provider=OutlinesProvider())
 
 
 @pytest.fixture
 def llamacpp_model() -> OutlinesModel:
     outlines_model_llamacpp = outlines.models.llamacpp.from_llamacpp(
-        llama_cpp.Llama.from_pretrained(
+        llama_cpp.Llama.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
             repo_id='M4-ai/TinyMistral-248M-v2-Instruct-GGUF',
             filename='TinyMistral-248M-v2-Instruct.Q4_K_M.gguf',
         )
@@ -167,7 +171,7 @@ def llamacpp_model() -> OutlinesModel:
 
 @pytest.fixture
 def mlxlm_model() -> OutlinesModel:  # pragma: no cover
-    outlines_model = outlines.models.mlxlm.from_mlxlm(*mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'))
+    outlines_model = outlines.models.mlxlm.from_mlxlm(*mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'))  # pyright: ignore[reportUnknownMemberType, reportArgumentType, reportUnknownArgumentType]
     return OutlinesModel(outlines_model, provider=OutlinesProvider())
 
 
@@ -181,7 +185,7 @@ def sglang_model() -> OutlinesModel:
 
 @pytest.fixture
 def vllm_model_offline() -> OutlinesModel:  # pragma: no cover
-    outlines_model = outlines.models.vllm_offline.from_vllm_offline(vllm.LLM('microsoft/Phi-3-mini-4k-instruct'))
+    outlines_model = outlines.models.vllm_offline.from_vllm_offline(vllm.LLM('microsoft/Phi-3-mini-4k-instruct'))  # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType]
     return OutlinesModel(outlines_model, provider=OutlinesProvider())
 
 
@@ -195,19 +199,19 @@ def binary_image() -> BinaryImage:
 outlines_parameters = [
     pytest.param(
         'from_transformers',
-        lambda: (
-            transformers.AutoModelForCausalLM.from_pretrained(
+        lambda: (  # pyright: ignore[reportUnknownLambdaType]
+            transformers.AutoModelForCausalLM.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
                 'erwanf/gpt2-mini',
                 device_map='cpu',
             ),
-            transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini'),
+            transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini'),  # pyright: ignore[reportUnknownMemberType]
         ),
         marks=skip_if_transformers_imports_unsuccessful,
     ),
     pytest.param(
         'from_llamacpp',
         lambda: (
-            llama_cpp.Llama.from_pretrained(
+            llama_cpp.Llama.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
                 repo_id='M4-ai/TinyMistral-248M-v2-Instruct-GGUF',
                 filename='TinyMistral-248M-v2-Instruct.Q4_K_M.gguf',
             ),
@@ -216,7 +220,7 @@ def binary_image() -> BinaryImage:
     ),
     pytest.param(
         'from_mlxlm',
-        lambda: mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'),
+        lambda: mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'),  # pyright: ignore[reportUnknownMemberType, reportUnknownLambdaType]
         marks=skip_if_mlxlm_imports_unsuccessful,
     ),
     pytest.param(
@@ -226,7 +230,7 @@ def binary_image() -> BinaryImage:
     ),
     pytest.param(
         'from_vllm_offline',
-        lambda: (vllm.LLM('microsoft/Phi-3-mini-4k-instruct'),),
+        lambda: (vllm.LLM('microsoft/Phi-3-mini-4k-instruct'),),  # pyright: ignore[reportUnknownLambdaType, reportUnknownMemberType]
         marks=skip_if_vllm_imports_unsuccessful,
     ),
 ]
@@ -254,19 +258,19 @@ def test_init(model_loading_function_name: str, args: Callable[[], tuple[Any]])
 pydantic_ai_parameters = [
     pytest.param(
         'from_transformers',
-        lambda: (
-            transformers.AutoModelForCausalLM.from_pretrained(
+        lambda: (  # pyright: ignore[reportUnknownLambdaType]
+            transformers.AutoModelForCausalLM.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
                 'erwanf/gpt2-mini',
                 device_map='cpu',
             ),
-            transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini'),
+            transformers.AutoTokenizer.from_pretrained('erwanf/gpt2-mini'),  # pyright: ignore[reportUnknownMemberType]
         ),
         marks=skip_if_transformers_imports_unsuccessful,
     ),
     pytest.param(
         'from_llamacpp',
         lambda: (
-            llama_cpp.Llama.from_pretrained(
+            llama_cpp.Llama.from_pretrained(  # pyright: ignore[reportUnknownMemberType]
                 repo_id='M4-ai/TinyMistral-248M-v2-Instruct-GGUF',
                 filename='TinyMistral-248M-v2-Instruct.Q4_K_M.gguf',
             ),
@@ -275,7 +279,7 @@ def test_init(model_loading_function_name: str, args: Callable[[], tuple[Any]])
     ),
     pytest.param(
         'from_mlxlm',
-        lambda: mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'),
+        lambda: mlx_lm.load('mlx-community/SmolLM-135M-Instruct-4bit'),  # pyright: ignore[reportUnknownMemberType, reportUnknownLambdaType]
         marks=skip_if_mlxlm_imports_unsuccessful,
     ),
     pytest.param(
@@ -285,7 +289,7 @@ def test_init(model_loading_function_name: str, args: Callable[[], tuple[Any]])
     ),
     pytest.param(
         'from_vllm_offline',
-        lambda: (vllm.LLM('microsoft/Phi-3-mini-4k-instruct'),),
+        lambda: (vllm.LLM('microsoft/Phi-3-mini-4k-instruct'),),  # pyright: ignore[reportUnknownLambdaType, reportUnknownMemberType]
         marks=skip_if_vllm_imports_unsuccessful,
     ),
 ]