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https://github.com/microsoft/semantic-kernel.git
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Eduard van Valkenburg
9e99933a27
### 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. --> - Added static code checking to pre-commit (check-ast and nbqa-check-ast) - Added Bandit security checking to pre-commit - Added pre-commit step to python-lint workflow, if it works, can delete seperate mypy, ruff and black tests ### 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 😄
79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from numpy import ndarray
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from semantic_kernel.memory.memory_record import MemoryRecord
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from semantic_kernel.utils.experimental_decorator import experimental_class
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@experimental_class
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class MemoryQueryResult:
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is_reference: bool
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external_source_name: str | None
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id: str
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description: str | None
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text: str | None
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additional_metadata: str | None
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relevance: float
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embedding: ndarray | None
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def __init__(
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self,
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is_reference: bool,
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external_source_name: str | None,
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id: str,
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description: str | None,
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text: str | None,
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additional_metadata: str | None,
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embedding: ndarray | None,
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relevance: float,
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) -> None:
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"""Initialize a new instance of MemoryQueryResult.
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Args:
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is_reference (bool): Whether the record is a reference record.
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external_source_name (Optional[str]): The name of the external source.
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id (str): A unique for the record.
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description (Optional[str]): The description of the record.
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text (Optional[str]): The text of the record.
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additional_metadata (Optional[str]): Custom metadata for the record.
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embedding (ndarray): The embedding of the record.
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relevance (float): The relevance of the record to a known query.
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Returns:
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None: None.
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"""
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self.is_reference = is_reference
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self.external_source_name = external_source_name
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self.id = id
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self.description = description
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self.text = text
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self.additional_metadata = additional_metadata
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self.relevance = relevance
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self.embedding = embedding
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@staticmethod
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def from_memory_record(
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record: MemoryRecord,
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relevance: float,
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) -> "MemoryQueryResult":
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"""Create a new instance of MemoryQueryResult from a MemoryRecord.
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Args:
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record (MemoryRecord): The MemoryRecord to create the MemoryQueryResult from.
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relevance (float): The relevance of the record to a known query.
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Returns:
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MemoryQueryResult: The created MemoryQueryResult.
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"""
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return MemoryQueryResult(
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is_reference=record._is_reference,
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external_source_name=record._external_source_name,
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id=record._id,
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description=record._description,
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text=record._text,
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additional_metadata=record._additional_metadata,
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embedding=record._embedding,
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relevance=relevance,
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)
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