mirror of
https://github.com/microsoft/semantic-kernel.git
synced 2026-10-12 02:19:06 +00:00
Eduard van Valkenburg
cbfd7e9330
### 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.
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This PR adds support for ndarray's as the content carrier for all binary
content types (binary, image, audio) as that is more optimized for
larger content.
It also does some fixes to the initialization of those content types and
the underlying data uri type.
Also some fixes for unspecified default param in pydantic Field,
language servers do not recognize `Field("default value")` as having a
default, so changed those occurances to `Field(default="default value")`
### 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 😄
70 lines
2.6 KiB
Python
70 lines
2.6 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from typing import Any
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from pydantic import Field
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from semantic_kernel.const import DEFAULT_FULLY_QUALIFIED_NAME_SEPARATOR
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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.utils.validation import FUNCTION_NAME_REGEX, PLUGIN_NAME_REGEX
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class KernelFunctionMetadata(KernelBaseModel):
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"""The kernel function metadata."""
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name: str = Field(..., pattern=FUNCTION_NAME_REGEX)
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plugin_name: str | None = Field(default=None, pattern=PLUGIN_NAME_REGEX)
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description: str | None = Field(default=None)
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parameters: list[KernelParameterMetadata] = Field(default_factory=list)
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is_prompt: bool
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is_asynchronous: bool | None = Field(default=True)
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return_parameter: KernelParameterMetadata | None = None
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additional_properties: dict[str, Any] | None = Field(default=None)
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@property
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def fully_qualified_name(self) -> str:
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"""Get the fully qualified name of the function.
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A fully qualified name is the name of the combination of the plugin name and
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the function name, separated by a hyphen, if the plugin name is present.
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Otherwise, it is just the function name.
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Returns:
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The fully qualified name of the function.
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"""
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return self.custom_fully_qualified_name(DEFAULT_FULLY_QUALIFIED_NAME_SEPARATOR)
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def custom_fully_qualified_name(self, separator: str) -> str:
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"""Get the fully qualified name of the function with a custom separator.
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Args:
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separator (str): The custom separator.
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Returns:
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The fully qualified name of the function with a custom separator.
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"""
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return f"{self.plugin_name}{separator}{self.name}" if self.plugin_name else self.name
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def __eq__(self, other: object) -> bool:
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"""Compare to another KernelFunctionMetadata instance.
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Args:
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other (KernelFunctionMetadata): The other KernelFunctionMetadata instance.
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Returns:
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True if the two instances are equal, False otherwise.
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"""
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if not isinstance(other, KernelFunctionMetadata):
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return False
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return (
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self.name == other.name
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and self.plugin_name == other.plugin_name
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and self.description == other.description
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and self.parameters == other.parameters
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and self.is_prompt == other.is_prompt
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and self.is_asynchronous == other.is_asynchronous
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and self.return_parameter == other.return_parameter
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)
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