SAMVectorsearch

SAM model of the Vectorsearch kind, generated from the Smarter platform’s JSON Schema.

Do not edit: run scripts/generate_sam_models.py. See smarter.models.sam.

class smarter.models.sam.vectorsearch.SAMDependency(*, kind: str, name: str, **extra_data: Any)

Bases: SAMModel

A resource that depends on the resource that a manifest describes.

kind: str

Kind[String]: The SAM kind of the resource that depends on this resource, e.g. LLMClient.

Read only.

name: str

Name[String]: The name of the resource that depends on this resource.

Read only.

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

class smarter.models.sam.vectorsearch.SAMVectorsearchMetadata(*, annotations: None | list[dict[str, str | int | float | bool | date | datetime | UUID | bytes | list | dict[str, Any]]] = None, description: str | None, name: str, tags: list[str] | None = None, version: str | None, **extra_data: Any)

Bases: SAMModel

Smarter API Vectorsearch Manifest - Metadata class.

annotations: None | list[dict[str, str | int | float | bool | date | datetime | UUID | bytes | list | dict[str, Any]]]

The manifest annotations.

Used for storing arbitrary metadata as

key-value pairs. Example: [{‘smarter.sh/test-manifest/project-name’: ‘Scooby dooby do’}]. The key should be a valid url-friendly string. The value accepts multi-line string values (YAML block scalars) and various scalar types including str, int, float, bool, datetime.date, datetime.datetime, decimal.Decimal, uuid.UUID, bytes, list, dict.

description: str | None

The description for this resource.

Be brief. Keep it under 255 characters.

name: str

The camelCase name of the manifest resource.

tags: list[str] | None

The tags of the manifest.

Used for generic resource categorization and search. Example: [‘tag1’, ‘tag2’]

version: str | None

The semantic version of the manifest.

Example: 0.1.0

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

class smarter.models.sam.vectorsearch.SAMVectorsearchStatus(*, accountNumber: str, created: datetime, dependencies: list[SAMDependency] | None = None, modified: datetime, recordLocator: str, username: str, **extra_data: Any)

Bases: SAMModel

Smarter API Vectorsearch Manifest - Status class.

accountNumber: str

Vectorsearch.status.account_number: The account owner of this Vectorsearch.

Read only.

created: datetime

The date in which this resource was created.

Read only.

dependencies: list[SAMDependency] | None

Dependencies[List]: The resources that depend on this resource, and that must be deleted, or stop referring to it, before it can be deleted.

Lists only the resources that you can read. Read only.

modified: datetime

The date in which this resource was most recently changed.

Read only.

recordLocator: str

RecordLocator[String]: An optional identifier used to locate the resource record associated with this manifest.

Read only.

username: str

Vectorsearch.status.username: The Smarter user who created this Vectorsearch.

Read only.

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

class smarter.models.sam.vectorsearch.VectorsearchSearchType(*values)

Bases: Enum

Supported retrieval strategies for a Vectorsearch query.

class smarter.models.sam.vectorsearch.SAMVectorsearchSpecConfig(*, auth_secret_name: str | None = None, fetch_k: Annotated[int, Gt(gt=0)] | None = None, is_enabled: bool | None = True, k: Annotated[int, Gt(gt=0)] | None = 4, lambda_mult: Annotated[float, None, Interval(gt=None, ge=0.0, lt=None, le=1.0), None, None] | None = None, metadata_filter: dict[str, Any] | None = None, score_threshold: Annotated[float, None, Interval(gt=None, ge=0.0, lt=None, le=1.0), None, None] | None = None, search_type: VectorsearchSearchType | None = 'similarity', vectorstore_name: str, **extra_data: Any)

Bases: SAMModel

Smarter API Vectorsearch Manifest Vectorsearch.spec.config.

auth_secret_name: str | None

Optional name of the Secret used to authenticate against the Vectorstore, if required.

fetch_k: PositiveInt | None

Number of candidate documents to fetch before MMR re-ranking.

Only valid when search_type=’mmr’.

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

is_enabled: bool | None

Whether this Vectorsearch is active and eligible to be queried.

k: PositiveInt | None

Number of top results to return from the search.

lambda_mult: confloat(ge=0.0, le=1.0) | None

Diversity vs.

relevance trade-off for MMR (0.0=max diversity, 1.0=max relevance). Only valid when search_type=’mmr’.

metadata_filter: dict[str, Any] | None

Optional metadata filter applied to the Vectorstore query, e.g. {‘source’: ‘faq’}.

score_threshold: confloat(ge=0.0, le=1.0) | None

Minimum relevance score a result must meet to be included.

Only valid when search_type=’similarity_score_threshold’.

search_type: VectorsearchSearchType | None

The retrieval strategy to use when querying the Vectorstore.

vectorstore_name: str

The name of the locally-hosted Vectorstore this search queries against.

class smarter.models.sam.vectorsearch.SAMVectorsearchSpec(*, config: SAMVectorsearchSpecConfig, **extra_data: Any)

Bases: SAMModel

Smarter API Vectorsearch Manifest Vectorsearch.spec.

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

config: SAMVectorsearchSpecConfig

Vectorsearch.spec.config[object].

The configuration for the Vectorsearch.

class smarter.models.sam.vectorsearch.SAMVectorsearch(*, apiVersion: str, kind: str, metadata: SAMVectorsearchMetadata, spec: SAMVectorsearchSpec, status: SAMVectorsearchStatus | None = None, **extra_data: Any)

Bases: SAMModel

Smarter API Manifest - Vectorsearch.

model_config = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'regex_engine': 'python-re', 'use_attribute_docstrings': True}

Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].

apiVersion: str

ApiVersion[String]: Required.

The API version of the AbstractSAMBase.

kind: str

Kind[String]: Required.

The kind of resource described by the manifest.

metadata: SAMVectorsearchMetadata

Vectorsearch.metadata[obj]: Required, the Vectorsearch metadata.

spec: SAMVectorsearchSpec

Vectorsearch.spec[obj]: Required, the Vectorsearch specification.

status: SAMVectorsearchStatus | None

Vectorsearch.status[obj]: Optional, Read-only.

Stateful status information about the Vectorsearch.