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Trouble running custom TFX component on Vertex AI (Kubeflow Runner) — Executor import error
I’m trying to run a simple custom TFX component using the Kubeflow Runner on GCP Vertex AI.
I’ve defined the component in two ways: Using the @component decorator, and as a fully custom component (...
1
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0
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593
views
Vertex AI Agent Deployment Fails with ModuleNotFoundError: No module named 'data_science'
Context
I'm trying to deploy a custom multi-agent app on Vertex AI Reasoning Engine (using Google ADK / Agent Builder). I'm using a .whl file that includes my entire custom agent code, organized under ...
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votes
1
answer
541
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Vertex AI Data Store indexing doesn't start
Summary:
Vertex AI Data Store indexing hangs on Document ingestion is working in progress. Document parsing and indexing will start later. for each document.
Details:
I use Airbyte to put Confluence ...
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0
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42
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Error while reading shap file from GCS bucket using vertex pipeline
I tried running this code:
import shap
from gcp_shared_utils.connectors.bucket import get_bucket_uri
def read_explainerfile(self, bucket_name):
try:
bucket = self.client....
-1
votes
1
answer
234
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Force Vertex AI outbound traffic through a custom shared VPC
I have a vertex ai pipeline that I want to force its outbound internet traffic through a custom shared VPC for whitelisting purposes. I enabled the "VPC Service Controls for peerings" as ...
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1
answer
122
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Timestamp issue while creating the model using pipeline in Vertex AI
I am currently utilizing the XGBoost classifier within a pipeline that includes normalization and the XGBoost model itself. The model has been successfully developed in the Notebook environment.
The ...
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2
answers
741
views
Latency issue using TextEmbeddingModel
I'm using Vertex AI's TextEmbeddingModel to calculate embeddings, and the first call shows significantly higher latency than the rest, likely due to caching. However, this isn't context-caching, and ...
1
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0
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443
views
how to define a task group name when using kfp v2 dsl.If() and how to use Boolean in a pythonic way?
Great to see that with kfp v2 we can now have if .. else block and use Boolean. While I am trying to migrate my v1 pipelines, I have few question
I am using kfp 2.7.0 and google-cloud-pipeline-...
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0
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403
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How to deploy a custom model in a private service endpoint in GCP Vertex AI
I have a custom tensorflow model that I need to deploy to a private endpoint in GCP Vertex AI. The GCP documentation is lengthy and not with clear steps on how to do it. Can you please help and ...
2
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0
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1k
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Vertex AI service account unable to access resources from an internal step
I am trying to tune a text-bison model with a custom dataset. During the prompt validation step, I am getting an error due to the vertex AI service agent being unable to access the bucket from the ...
0
votes
1
answer
317
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The difference between the machine type in Vertex ai workbench instance and aiplatform SDK?
What is the difference between the machine type which we set in Vertex ai workbench for Notebook and the machine type in python SDK of aiplatform.CustomTrainingJob run method? The machine type is ...
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0
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33
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The variable is returning empty in my Python script [duplicate]
I am working on a Python script and using GCP Cloud Build to run it. Instead of hardcoding some of the variables, I am trying to use a Cloud Build YAML file to define the variables there and then use ...
1
vote
2
answers
937
views
Import custom prediction routine to vertex AI pipeline
I have created a custom prediction routine on Vertex AI, uploaded the model, and am able to generate predictions with it through the UI. Now, I would like to incorporate this into a Vertex AI Pipeline,...
1
vote
1
answer
545
views
Vertex AI docker in docker: Cannot connect to the Docker daemon
So I am using kubeflow Containerized Python Components to create a Vertex AI training pipeline. As the last step of the pipeline, I would like to build and push a custom prediction container image ...
0
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1
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1k
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How to run a vertex AI pipeline across multiple projects?
In order to run a pipeline from my local machine, I do:
from google.cloud import aiplatform
aiplatform.init(project="my-project")
job = aiplatform.PipelineJob(
display_name="...