Google Gen AI SDK

Related topics

• Google Gen AI SDK works with Vertex AI From the official documentation: “Set environment variables to use the Google Gen AI SDK with Vertex AI:”
• Gemini Enterprise Agent Platform works with Google Gen AI SDK From the official documentation: “Set environment variables to use the Google Gen AI SDK with Gemini Enterprise Agent Platform”
• Agent Platform works with Google Gen AI SDK From the official documentation: “Learn the basics of using the Google Gen AI SDK to send queries to Gemini models with Agent Platform.”
• Colab Enterprise is an alternative to Google Gen AI SDK From the official documentation: “You can create a supervised fine-tuning job by using the Google Cloud console, the Google Gen AI SDK, the REST API, or Colab Enterprise.”
• Google Gen AI SDK is an alternative to Vertex AI SDK From the official documentation: “If your Gemini 1.x application uses the Vertex AI SDK, switch to the Google Gen AI SDK.”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
• Model Armor works with Vertex AI From the official documentation: “The following example enables Model Armor on a Vertex AI endpoint.”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• customer-managed encryption keys secures Cloud Storage From the official documentation: “CMEKs encrypt data at rest in Cloud SQL, Cloud Storage, and within GKE clusters.”
• BigQuery works with Gemini Enterprise Agent Platform From the official documentation: “The BigQuery dataset stores all versions for the associated Gemini Enterprise Agent Platform dataset.”
• customer-managed encryption keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
• Cloud Storage works with customer-managed encryption keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
• Cloud Storage works with Identity and Access Management From the official documentation: “To learn how to use IAM with Cloud Storage, see [Using IAM Permissions](/storage/docs/access-control/using-iam-permissions).”
• customer-managed encryption keys secures Gemini Enterprise Agent Platform From the official documentation: “Enable customer-managed encryption keys (CMEK) for the Gemini Enterprise Agent Platform to gain more control over data encryption and key management.”
• Vertex AI is part of Gemini Enterprise Agent Platform From the official documentation: “Vertex AI's services are now part of Gemini Enterprise Agent Platform.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• BigQuery works with Colab Enterprise From the official documentation: “You can use Colab Enterprise from within the Google Cloud console, with features built into both Agent Platform and BigQuery.”
• Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• Colab Enterprise is part of Gemini Enterprise Agent Platform From the official documentation: “Colab Enterprise is a part of Gemini Enterprise Agent Platform.”
• Gemini Enterprise Agent Platform works with Model Armor From the official documentation: “If you use floor settings for the [Agent Platform integration](/model-armor/model-armor-vertex-integration), all Model Armor features are available in the following locations.”
• Identity and Access Management secures Vertex AI From the official documentation: “A Vertex AI model with an active endpoint that you have Identity and Access Management (IAM) permission to access.”
• Model Armor secures Vertex AI From the official documentation: “The following example enables Model Armor on a Vertex AI endpoint.”
• VPC Service Controls secures Gemini Enterprise Agent Platform From the official documentation: “The API for Agent Platform can be protected by VPC Service Controls and the product can be used normally inside service perimeters.”
• Agent Platform works with Cloud Storage From the official documentation: “Load the model's `state_dict` object into Cloud Storage by using a Agent Platform custom job:”
• BigQuery works with Vertex AI From the official documentation: “The page provides guidance for getting predictions from Vertex AI, based on retail [data exported into BigQuery](/retail/docs/export-data-into-bq).”
• Cloud Storage works with Colab Enterprise From the official documentation: “Colab Enterprise stores the results in Cloud Storage for you to review and share with others.”
• Cloud Storage works with Gemini Enterprise Agent Platform From the official documentation: “This page describes how to use Gemini Enterprise Agent Platform to export your image AutoML Edge models to Cloud Storage.”
• customer-managed encryption keys is part of Cloud Storage From the official documentation: “[Cloud Storage](/storage/docs/introduction) provides features such as customer-managed encryption, lifecycle management, and aging and retention policies.”
• customer-managed encryption keys secures Colab Enterprise From the official documentation: “This guide describes how to use CMEK for Colab Enterprise.”
• Identity and Access Management secures Gemini Enterprise Agent Platform From the official documentation: “Agent Platform uses IAM to manage access to resources.”
• Identity and Access Management works with VPC Service Controls From the official documentation: “VPC Service Controls perimeters and Identity and Access Management (IAM) roles work together.”
• Model Armor secures Gemini Enterprise Agent Platform From the official documentation: “This document describes how to configure Model Armor to protect Gemini models on Gemini Enterprise Agent Platform by screening prompts and responses.”
• VPC Service Controls secures Colab Enterprise From the official documentation: “This page describes how to use VPC Service Controls to set up a Colab Enterprise notebook within a service perimeter.”
• Agent Platform works with BigQuery From the official documentation: “BigQuery and Agent Platform are tightly integrated, letting you access and analyze your data directly within the Agent Platform platform.”
• Agent Platform works with Model Armor From the official documentation: “Model Armor integrates with Agent Platform and Google Cloud MCP servers to screen requests and responses from Gemini models and Google Cloud remote MCP servers based on the floor settings you define.”
• Agent Platform works with VPC Service Controls From the official documentation: “If you use Agent Platform in a VPC-SC environment, you must create an ingress rule in your perimeter to allow ingress from the Reasoning Engine Service Agent (`service-PROJECT_NUMBER@gcp-sa-aiplatform-re.iam.gserviceaccount.com`) into the `storage.googleapis.com` service and…”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Colab Enterprise works with Gemini Enterprise Agent Platform From the official documentation: “To learn more about using the side panel with your Agent Platform tuning jobs, see [Interact with Agent Platform to tune a model](/colab/docs/tuning).”
• Colab Enterprise depends on Vertex AI From the official documentation: “Colab Enterprise provides a notebook-centric, zero-configuration experience, with compute resources managed by Vertex AI, and integrates with other Google Cloud services like BigQuery.”
• customer-managed encryption keys is part of Agent Platform From the official documentation: “See Agent Engine [Customer-managed encryption keys (CMEK)](/gemini-enterprise-agent-platform/scale/runtime/manage-agent-access#cmek) for more details.”
• Gemini Enterprise Agent Platform depends on Cloud Storage From the official documentation: “Certain tasks in Agent Platform require that you use additional Google Cloud products besides Agent Platform. For example, in most cases, you must use Cloud Storage and Artifact Registry when you create a custom training pipeline.”
• Gemini Enterprise Agent Platform depends on Identity and Access Management From the official documentation: “Agent Platform uses IAM to manage access to resources.”
• Gemini Enterprise Agent Platform works with Identity and Access Management From the official documentation: “Learn more about [Gemini Enterprise Agent Platform access control with IAM](/gemini-enterprise-agent-platform/machine-learning/general/access-control).”
• Gemini Enterprise Agent Platform works with VPC Service Controls From the official documentation: “For information on using Gemini Enterprise Agent Platform VPC Service Controls, see [VPC Service Controls with Gemini Enterprise Agent Platform](/gemini-enterprise-agent-platform/machine-learning/general/vpc-service-controls).”
• Identity and Access Management secures Agent Platform From the official documentation: “Agent Platform uses Identity and Access Management (IAM) for authorization.”
• Identity and Access Management secures Colab Enterprise From the official documentation: “This page describes how to use [Identity and Access Management (IAM)](/iam) to manage access to Colab Enterprise resources.”
• Identity and Access Management secures Model Armor From the official documentation: “Model Armor uses Identity and Access Management (IAM) to control access to resources.”
• Model Armor depends on Identity and Access Management From the official documentation: “Model Armor uses Identity and Access Management (IAM) to control access to resources.”
• VPC Service Controls secures Agent Platform From the official documentation: “(Optional) To mitigate the risk of data exfiltration from Agent Platform, enable VPC Service Controls and specify a VPC network when you create a cluster.”
• VPC Service Controls secures Model Armor From the official documentation: “The API for Model Armor can be protected by VPC Service Controls and the product can be used normally inside service perimeters.”