What is Vertex AI Engine

Vertex AI Agent Engine (formerly known as LangChain on Vertex AI or Vertex AI Reasoning Engine) is a set of services that enables developers to deploy, manage, and scale AI agents in production. Agent Engine handles the infrastructure to scale agents in production so you can focus on creating applications. Vertex AI Agent Engine offers the following services that you can use individually or in combination:

Managed runtime:

Deploy and scale agents with a managed runtime and end-to-end management capabilities.

Customize the agent's container image with build-time installation scripts for system dependencies.

Use security features including VPC-SC compliance and configuration of authentication and IAM.

Access models and tools such as function calling.

Deploy agents built using different Python frameworks:

Context management:

Sessions (Preview): Agent Engine Sessions lets you store individual interactions between users and agents, providing definitive sources for conversation context.

Memory Bank (Preview): Agent Engine Memory Bank lets you store and retrieve information from sessions to personalize agent interactions.

Quality and evaluation (Preview):

Evaluate agent quality with the integrated Gen AI Evaluation service.

Example Store (Preview): Store and dynamically retrieve few-shot examples to improve agent performance.

Optimize agents with Gemini model training runs.

Observability:

Understand agent behavior with Google Cloud Trace (supporting OpenTelemetry), Cloud Monitoring, and Cloud Logging.

Create and deploy on Vertex AI Agent Engine

Note: For a streamlined, IDE-based development and deployment experience with Vertex AI Agent Engine, consider the agent-starter-pack. It provides ready-to-use templates, a built-in UI for experimentation, and simplifies deployment, operations, evaluation, customization, and observability.

The workflow for building an agent on Vertex AI Agent Engine is:

Steps Description

1. Set up the environment Set up your Google project and install the latest version of the Vertex AI SDK for Python.

2. Develop an agent Develop an agent that can be deployed on Vertex AI Agent Engine.

3. Deploy the agent Deploy the agent on the Vertex AI Agent Engine managed runtime.

4. Use the agent Query the agent by sending an API request.

5. Manage the deployed agent Manage and delete agents that you have deployed to Vertex AI Agent Engine.