Hi, I'm trying to automate the process of creating App Builder agents, I'm following this documentation here , I managed to create the datastore uploads the files, however when I try to create the app via script as shown in the documentation I am not having success I receive the following error:
raise _InactiveRpcError(state) # pytype: disable=not-instantiable
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
grpc._channel._InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
status = StatusCode.INTERNAL
details = "Internal error encountered. Please try again. If the issue persists, please contact our support team."
debug_error_string = "UNKNOWN:Error received from peer ipv4:142.251.129.74:443 {created_time:"2024-07-03T20:13:48.5523557+00:00", grpc_status:13, grpc_message:"Internal error encountered. Please try agair.py", line 66, in create_engine_sample
raise exceptions.from_grpc_error(exc) from exc
google.api_core.exceptions.InternalServerError: 500 Internal error encountered. Please try again. If the issue persists, please contact our support team.
I can't understand what I'm doing wrong or if something is missing, the error isn't clear about the problem I'm facing, below is an example of the code I'm using:
from typing import List
from google.api_core.client_options import ClientOptions
from google.cloud import discoveryengine_v1 as discoveryengine
from google.oauth2 import service_account
# Caminho para a chave JSON da conta de serviço
GOOGLE_APPLICATION_CREDENTIALS = './chave.json'
project_id = "projetoxpto"
location = "global" # Values: "global"
engine_id = "agente_rodrigo_martins"
data_store_ids = ["base_1719884343347"] # Certifique-se de que este data store existe
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",
)
print(f'Chegou no discoveryengine...\n')
engine = discoveryengine.Engine(
display_name="app criado via script",
# 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_CHAT,
# For search apps only
search_engine_config=discoveryengine.Engine.SearchEngineConfig(
# Options: SEARCH_TIER_STANDARD, SEARCH_TIER_ENTERPRISE
search_tier=discoveryengine.SearchTier.SEARCH_TIER_STANDARD,
# Options: SEARCH_ADD_ON_LLM, SEARCH_ADD_ON_UNSPECIFIED
search_add_ons=[discoveryengine.SearchAddOn.SEARCH_ADD_ON_UNSPECIFIED],
),
# For generic recommendation apps only
# similar_documents_config=discoveryengine.Engine.SimilarDocumentsEngineConfig,
data_store_ids=data_store_ids,
)
# Make the request
print(f'Chegou no CreateEngineRequest...\n')
request = discoveryengine.CreateEngineRequest(
parent=parent,
engine=engine,
engine_id=engine_id,
)
# Make the request
print(f'Chegou no create_engine...\n')
operation = client.create_engine(request=request,timeout=3600)
print(f"Waiting for operation to complete: {operation.operation.name}")
response = operation.result()
# Once 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
create_engine_sample(project_id,location,engine_id, data_store_ids)
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