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### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> Some small fixes in uv setup within actions Added experimental unit tests runs for py3.13 First typing improvement from pyright and pyright config. ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄
206 lines
6.9 KiB
Python
206 lines
6.9 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import typing as t
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import pytest
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import typing_extensions as te
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from pydantic import Field, Json
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from semantic_kernel.contents.chat_history import ChatHistory
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from semantic_kernel.core_plugins.conversation_summary_plugin import ConversationSummaryPlugin
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from semantic_kernel.core_plugins.http_plugin import HttpPlugin
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from semantic_kernel.core_plugins.math_plugin import MathPlugin
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from semantic_kernel.core_plugins.text_memory_plugin import TextMemoryPlugin
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from semantic_kernel.core_plugins.text_plugin import TextPlugin
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from semantic_kernel.core_plugins.time_plugin import TimePlugin
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from semantic_kernel.core_plugins.wait_plugin import WaitPlugin
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from semantic_kernel.core_plugins.web_search_engine_plugin import WebSearchEnginePlugin
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from semantic_kernel.functions.kernel_arguments import KernelArguments
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from semantic_kernel.functions.kernel_function import KernelFunction
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from semantic_kernel.functions.kernel_function_decorator import kernel_function
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from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata
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from semantic_kernel.functions.kernel_parameter_metadata import KernelParameterMetadata
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from semantic_kernel.kernel_pydantic import KernelBaseModel
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from semantic_kernel.memory.null_memory import NullMemory
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from semantic_kernel.memory.semantic_text_memory_base import SemanticTextMemoryBase
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from semantic_kernel.template_engine.blocks.block import Block
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from semantic_kernel.template_engine.blocks.block_types import BlockTypes
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from semantic_kernel.template_engine.blocks.code_block import CodeBlock
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from semantic_kernel.template_engine.blocks.function_id_block import FunctionIdBlock
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from semantic_kernel.template_engine.blocks.named_arg_block import NamedArgBlock
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from semantic_kernel.template_engine.blocks.text_block import TextBlock
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from semantic_kernel.template_engine.blocks.val_block import ValBlock
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from semantic_kernel.template_engine.blocks.var_block import VarBlock
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KernelBaseModelFieldT = t.TypeVar("KernelBaseModelFieldT", bound=KernelBaseModel)
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class _Serializable(t.Protocol):
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"""A serializable object."""
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def json(self) -> Json:
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"""Return a JSON representation of the object."""
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raise NotImplementedError
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@classmethod
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def parse_raw(cls: t.Type[te.Self], json: Json) -> te.Self:
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"""Return the constructed object from a JSON representation."""
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raise NotImplementedError
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@pytest.fixture()
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def kernel_factory() -> t.Callable[[t.Type[_Serializable]], _Serializable]:
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"""Return a factory for various objects in semantic-kernel."""
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def create_kernel_function() -> KernelFunction:
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"""Return an KernelFunction."""
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@kernel_function(name="function")
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def my_function(arguments: KernelArguments) -> str:
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return f"F({arguments['input']})"
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return KernelFunction.from_method(
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plugin_name="plugin",
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method=my_function,
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)
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def create_chat_history() -> ChatHistory:
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return ChatHistory()
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cls_obj_map = {
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Block: Block(content="foo"),
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CodeBlock: CodeBlock(content="foo"),
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FunctionIdBlock: FunctionIdBlock(content="foo.bar"),
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TextBlock: TextBlock(content="baz"),
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ValBlock: ValBlock(content="'qux'"),
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VarBlock: VarBlock(content="$quux"),
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NamedArgBlock: NamedArgBlock(content="foo='bar'"),
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# PromptTemplateEngine: PromptTemplateEngine(),
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KernelParameterMetadata: KernelParameterMetadata(
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name="foo",
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description="bar",
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default_value="baz",
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type_="string",
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is_required=True,
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schema_data=KernelParameterMetadata.infer_schema(None, "str", "baz", "bar"),
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),
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KernelFunctionMetadata: KernelFunctionMetadata(
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name="foo",
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plugin_name="bar",
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description="baz",
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parameters=[
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KernelParameterMetadata(
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name="qux",
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description="bar",
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default_value="baz",
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type_="str",
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schema_data=KernelParameterMetadata.infer_schema(None, "str", "baz", "bar"),
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)
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],
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is_prompt=True,
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is_asynchronous=False,
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),
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ChatHistory: create_chat_history(),
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NullMemory: NullMemory(),
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KernelFunction: create_kernel_function(),
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}
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def constructor(cls: t.Type[_Serializable]) -> _Serializable:
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"""Return a serializable object."""
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return cls_obj_map[cls]
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return constructor
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PROTOCOLS = [
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ConversationSummaryPlugin,
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HttpPlugin,
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MathPlugin,
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TextMemoryPlugin,
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TextPlugin,
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TimePlugin,
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WaitPlugin,
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WebSearchEnginePlugin,
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]
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BASE_CLASSES = [
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SemanticTextMemoryBase,
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]
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STATELESS_CLASSES = [
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NullMemory,
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]
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ENUMS = [
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BlockTypes,
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]
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PYDANTIC_MODELS = [
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Block,
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CodeBlock,
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FunctionIdBlock,
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TextBlock,
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ValBlock,
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VarBlock,
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NamedArgBlock,
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KernelParameterMetadata,
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KernelFunctionMetadata,
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ChatHistory,
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]
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KERNEL_FUNCTION_OPTIONAL = [KernelFunction]
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KERNEL_FUNCTION_REQUIRED = [
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pytest.param(
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KernelFunction,
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marks=pytest.mark.xfail(reason="Need to implement Pickle serialization."),
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)
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]
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class TestUsageInPydanticFields:
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@pytest.mark.parametrize(
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"kernel_type",
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BASE_CLASSES + PROTOCOLS + ENUMS + PYDANTIC_MODELS + STATELESS_CLASSES + KERNEL_FUNCTION_OPTIONAL,
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)
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def test_usage_as_optional_field(
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self,
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kernel_type: t.Type[KernelBaseModelFieldT],
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) -> None:
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"""Semantic Kernel objects should be valid Pydantic fields.
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Otherwise, they cannot be used in Pydantic models.
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"""
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class TestModel(KernelBaseModel):
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"""A test model."""
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field: kernel_type | None = None
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assert_serializable(TestModel(), TestModel)
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@pytest.mark.parametrize("kernel_type", PYDANTIC_MODELS + STATELESS_CLASSES + KERNEL_FUNCTION_REQUIRED)
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def test_usage_as_required_field(
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self,
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kernel_factory: t.Callable[[t.Type[KernelBaseModelFieldT]], KernelBaseModelFieldT],
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kernel_type: t.Type[KernelBaseModelFieldT],
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) -> None:
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"""Semantic Kernel objects should be valid Pydantic fields.
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Otherwise, they cannot be used in Pydantic models.
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"""
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class TestModel(KernelBaseModel):
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"""A test model."""
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field: kernel_type = Field(default_factory=lambda: kernel_factory(kernel_type))
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assert_serializable(TestModel(), TestModel)
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assert_serializable(TestModel(field=kernel_factory(kernel_type)), TestModel)
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def assert_serializable(obj: _Serializable, obj_type) -> None:
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"""Assert that an object is serializable, uses both dump and dump_json methods."""
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assert obj is not None
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serialized = obj.model_dump_json()
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assert isinstance(serialized, str)
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assert obj_type.model_validate_json(serialized).model_dump() == obj.model_dump()
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