Create an app

Create an app

Explore further

For detailed documentation that includes this code sample, see the following:

• Create a search app

Code sample

Python

For more information, see the Vertex AI Agent Builder Python API reference documentation.

To authenticate to Vertex AI Agent Builder, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from typing import List

from google.api_core.client_options import ClientOptions
from google.cloud import discoveryengine_v1 as discoveryengine

# TODO(developer): Uncomment these variables before running the sample.
# project_id = "YOUR_PROJECT_ID"
# location = "YOUR_LOCATION" # Values: "global"
# engine_id = "YOUR_ENGINE_ID"
# data_store_ids = ["YOUR_DATA_STORE_ID"]


def create_engine_sample(
    project_id: str, location: str, engine_id: str, data_store_ids: List[str]
) -> str:
    #  For more information, refer to:
    # https://cloud.google.com/generative-ai-app-builder/docs/locations#specify_a_multi-region_for_your_data_store
    client_options = (
        ClientOptions(api_endpoint=f"{location}-discoveryengine.googleapis.com")
        if location != "global"
        else None
    )

    # Create a client
    client = discoveryengine.EngineServiceClient(client_options=client_options)

    # The full resource name of the collection
    # e.g. projects/{project}/locations/{location}/collections/default_collection
    parent = client.collection_path(
        project=project_id,
        location=location,
        collection="default_collection",
    )

    engine = discoveryengine.Engine(
        display_name="Test Engine",
        # Options: GENERIC, MEDIA, HEALTHCARE_FHIR
        industry_vertical=discoveryengine.IndustryVertical.GENERIC,
        # Options: SOLUTION_TYPE_RECOMMENDATION, SOLUTION_TYPE_SEARCH, SOLUTION_TYPE_CHAT, SOLUTION_TYPE_GENERATIVE_CHAT
        solution_type=discoveryengine.SolutionType.SOLUTION_TYPE_SEARCH,
        # For search apps only
        search_engine_config=discoveryengine.Engine.SearchEngineConfig(
            # Options: SEARCH_TIER_STANDARD, SEARCH_TIER_ENTERPRISE
            search_tier=discoveryengine.SearchTier.SEARCH_TIER_ENTERPRISE,
            # Options: SEARCH_ADD_ON_LLM, SEARCH_ADD_ON_UNSPECIFIED
            search_add_ons=[discoveryengine.SearchAddOn.SEARCH_ADD_ON_LLM],
        ),
        # For generic recommendation apps only
        # similar_documents_config=discoveryengine.Engine.SimilarDocumentsEngineConfig,
        data_store_ids=data_store_ids,
    )

    request = discoveryengine.CreateEngineRequest(
        parent=parent,
        engine=engine,
        engine_id=engine_id,
    )

    # Make the request
    operation = client.create_engine(request=request)

    print(f"Waiting for operation to complete: {operation.operation.name}")
    response = operation.result()

    # After the operation is complete,
    # get information from operation metadata
    metadata = discoveryengine.CreateEngineMetadata(operation.metadata)

    # Handle the response
    print(response)
    print(metadata)

    return operation.operation.name

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