Class ReasoningEngine (1.49.0)

ReasoningEngine(reasoning_engine_name: str)

Represents a Vertex AI Reasoning Engine resource.

Properties

create_time

Time this resource was created.

display_name

Display name of this resource.

encryption_spec

Customer-managed encryption key options for this Vertex AI resource.

If this is set, then all resources created by this Vertex AI resource will be encrypted with the provided encryption key.

gca_resource

The underlying resource proto representation.

labels

User-defined labels containing metadata about this resource.

Read more about labels at https://goo.gl/xmQnxf

name

Name of this resource.

resource_name

Fully-qualified resource name.

update_time

Time this resource was last updated.

Methods

ReasoningEngine

ReasoningEngine(reasoning_engine_name: str)

Retrieves a Reasoning Engine resource.

Parameter
Name	Description
`reasoning_engine_name`	`str` Required. A fully-qualified resource name or ID such as "projects/123/locations/us-central1/reasoningEngines/456" or "456" when project and location are initialized or passed.

create

create(
    reasoning_engine: vertexai.reasoning_engines._reasoning_engines.Queryable,
    *,
    requirements: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None,
    reasoning_engine_name: typing.Optional[str] = None,
    display_name: typing.Optional[str] = None,
    description: typing.Optional[str] = None,
    gcs_dir_name: str = "reasoning_engine",
    sys_version: typing.Optional[str] = None,
    extra_packages: typing.Optional[typing.Sequence[str]] = None
) -> vertexai.reasoning_engines._reasoning_engines.ReasoningEngine

Creates a new ReasoningEngine.

The Reasoning Engine will be an instance of the reasoning_engine that was passed in, running remotely on Vertex AI.

Sample src_dir contents (e.g. ./user_src_dir):

user_src_dir/
|-- main.py
|-- requirements.txt
|-- user_code/
|   |-- utils.py
|   |-- ...
|-- ...

To build a Reasoning Engine:

remote_app = ReasoningEngine.create(
    local_app,
    requirements=[
        # I.e. the PyPI dependencies listed in requirements.txt
        "google-cloud-aiplatform==1.25.0",
        "langchain==0.0.242",
        ...
    ],
    extra_packages=[
        "./user_src_dir/main.py", # a single file
        "./user_src_dir/user_code", # a directory
        ...
    ],
)

Parameters
Name	Description
`reasoning_engine`	`ReasoningEngineInterface` Required. The Reasoning Engine to be created.
`requirements`	`Union[str, Sequence[str]]` Optional. The set of PyPI dependencies needed. It can either be the path to a single file (requirements.txt), or an ordered list of strings corresponding to each line of the requirements file.
`reasoning_engine_name`	`str` Optional. A fully-qualified resource name or ID such as "projects/123/locations/us-central1/reasoningEngines/456" or "456" when project and location are initialized or passed. If specifying the ID, it should be 4-63 characters. Valid characters are lowercase letters, numbers and hyphens ("-"), and it should start with a number or a lower-case letter. If not provided, Vertex AI will generate a value for this ID.
`display_name`	`str` Optional. The user-defined name of the Reasoning Engine. The name can be up to 128 characters long and can comprise any UTF-8 character.
`description`	`str` Optional. The description of the Reasoning Engine.
`gcs_dir_name`	`CreateReasoningEngineOptions` Optional. The GCS bucket directory under `staging_bucket` to use for staging the artifacts needed.
`sys_version`	`str` Optional. The Python system version used. Currently supports any of "3.8", "3.9", "3.10", "3.11". If not specified, it defaults to the "{major}.{minor}" attributes of sys.version_info.
`extra_packages`	`Sequence[str]` Optional. The set of extra user-provided packages (if any).

Exceptions
Type	Description
`ValueError`	If `sys.version` is not supported by ReasoningEngine.
`ValueError`	If the `project` was not set using `vertexai.init`.
`ValueError`	If the `location` was not set using `vertexai.init`.
`ValueError`	If the `staging_bucket` was not set using vertexai.init.
`ValueError`	If the `staging_bucket` does not start with "gs://".
`FileNotFoundError`	If `extra_packages` includes a file or directory
`tha`	does not exist.:

Returns
Type	Description
`ReasoningEngine`	The Reasoning Engine that was created.

delete

delete(sync: bool = True) -> None

Deletes this Vertex AI resource. WARNING: This deletion is permanent.

Parameter
Name	Description
`sync`	`bool` Whether to execute this deletion synchronously. If False, this method will be executed in concurrent Future and any downstream object will be immediately returned and synced when the Future has completed.

list

list(
    filter: typing.Optional[str] = None,
    order_by: typing.Optional[str] = None,
    project: typing.Optional[str] = None,
    location: typing.Optional[str] = None,
    credentials: typing.Optional[google.auth.credentials.Credentials] = None,
    parent: typing.Optional[str] = None,
) -> typing.List[google.cloud.aiplatform.base.VertexAiResourceNoun]

List all instances of this Vertex AI Resource.

Example Usage:

aiplatform.BatchPredictionJobs.list( filter='state="JOB_STATE_SUCCEEDED" AND display_name="my_job"', )

aiplatform.Model.list(order_by="create_time desc, display_name")

Parameters
Name	Description
`filter`	`str` Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported.
`order_by`	`str` Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: `display_name`, `create_time`, `update_time`
`project`	`str` Optional. Project to retrieve list from. If not set, project set in aiplatform.init will be used.
`location`	`str` Optional. Location to retrieve list from. If not set, location set in aiplatform.init will be used.
`credentials`	`auth_credentials.Credentials` Optional. Custom credentials to use to retrieve list. Overrides credentials set in aiplatform.init.
`parent`	`str` Optional. The parent resource name if any to retrieve list from.

operation_schemas

operation_schemas() -> typing.Sequence[typing.Dict[str, typing.Any]]

Returns the (Open)API schemas for the Reasoning Engine.

query

query(**kwargs) -> typing.Dict[str, typing.Any]

Runs the Reasoning Engine to serve the user query.

This will be based on the .query(...) method of the python object that was passed in when creating the Reasoning Engine.

Returns
Type	Description
`dict[str, Any]`	The response from serving the user query.

to_dict

to_dict() -> typing.Dict[str, typing.Any]

Returns the resource proto as a dictionary.

wait

wait()

Helper method that blocks until all futures are complete.