mirror of
https://github.com/microsoft/semantic-kernel.git
synced 2026-10-12 11:19:56 +00:00
Eduard van Valkenburg
003cc4c010
### 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. --> Overhaul of the VectorStores to get it matching with dotnet and the latest development there. Closes: - #11938 - #11598 - #11597 - #11517 - #10561 - #10391 - #9911 - #9892 - #10867 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Many changes, some highlights: - Moved from different vector fields types, to a single with a enum first VectorStoreField() - Renamed several items - Made embeddinggenerrator a part of the vector field spec and do automatic vectorization from there or from the same param on a collection - Adds hybrid search using the same setup - Removed the intermediate TextSeachVectorSearch object need, by allowing `create_search_function` directly on a collection Will write out full changes in a migration guide in the docs. ### 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 - [ ] I didn't break anyone 😄
87 lines
2.7 KiB
Python
87 lines
2.7 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
|
|
|
|
import sys
|
|
|
|
from numpy import ndarray
|
|
|
|
from semantic_kernel.memory.memory_record import MemoryRecord
|
|
|
|
if sys.version_info >= (3, 13):
|
|
from warnings import deprecated
|
|
else:
|
|
from typing_extensions import deprecated
|
|
|
|
|
|
@deprecated("This class will be removed in a future version.")
|
|
class MemoryQueryResult:
|
|
"""The memory query result."""
|
|
|
|
is_reference: bool
|
|
external_source_name: str | None
|
|
id: str
|
|
description: str | None
|
|
text: str | None
|
|
additional_metadata: str | None
|
|
relevance: float
|
|
embedding: ndarray | None
|
|
|
|
def __init__(
|
|
self,
|
|
is_reference: bool,
|
|
external_source_name: str | None,
|
|
id: str,
|
|
description: str | None,
|
|
text: str | None,
|
|
additional_metadata: str | None,
|
|
embedding: ndarray | None,
|
|
relevance: float,
|
|
) -> None:
|
|
"""Initialize a new instance of MemoryQueryResult.
|
|
|
|
Args:
|
|
is_reference (bool): Whether the record is a reference record.
|
|
external_source_name (Optional[str]): The name of the external source.
|
|
id (str): A unique for the record.
|
|
description (Optional[str]): The description of the record.
|
|
text (Optional[str]): The text of the record.
|
|
additional_metadata (Optional[str]): Custom metadata for the record.
|
|
embedding (ndarray): The embedding of the record.
|
|
relevance (float): The relevance of the record to a known query.
|
|
|
|
Returns:
|
|
None: None.
|
|
"""
|
|
self.is_reference = is_reference
|
|
self.external_source_name = external_source_name
|
|
self.id = id
|
|
self.description = description
|
|
self.text = text
|
|
self.additional_metadata = additional_metadata
|
|
self.relevance = relevance
|
|
self.embedding = embedding
|
|
|
|
@staticmethod
|
|
def from_memory_record(
|
|
record: MemoryRecord,
|
|
relevance: float,
|
|
) -> "MemoryQueryResult":
|
|
"""Create a new instance of MemoryQueryResult from a MemoryRecord.
|
|
|
|
Args:
|
|
record (MemoryRecord): The MemoryRecord to create the MemoryQueryResult from.
|
|
relevance (float): The relevance of the record to a known query.
|
|
|
|
Returns:
|
|
MemoryQueryResult: The created MemoryQueryResult.
|
|
"""
|
|
return MemoryQueryResult(
|
|
is_reference=record._is_reference,
|
|
external_source_name=record._external_source_name,
|
|
id=record._id,
|
|
description=record._description,
|
|
text=record._text,
|
|
additional_metadata=record._additional_metadata,
|
|
embedding=record._embedding,
|
|
relevance=relevance,
|
|
)
|