A Vertex AI
extension
is a structured
API wrapper that connects a model to an API for processing real-time data or
performing real-world actions.
The difference between Extensions and Functions is in the execution of the Tool. Extensions are automatically executed by Vertex AI. Whereas functions must be manually executed by the user or client.
To streamline the extension creation process, we provide prebuilt Extensions by Google for common use cases, such as code interpretation and Vertex AI Search. If your use case doesn't align with these templates, you can create your own custom extension.
Use-cases and benefits
The following are some possible extensions use cases:
- Generate and run code.
- Query websites and synthesize information.
- Answer questions based on information within a collection of enterprise-specific data.
- Query and analyze datastores.
Vertex AI extensions provide the following benefits:
- Enterprise controls: Identity and Access Management (IAM) permissions and security controls.
- Data security: Contractual agreements that your private data won't be leaked or used in model training
- Performance agreements: Contractual agreements that the platform delivers specific features and uptimes.
- Private extensions: Authorized users in your organization or a trusted partner can use extensions to access sensitive internal data and actions, such as searching internal knowledge bases or completing HR actions.
- Google product integrations: Integration with Google products like Vertex AI Search, BigQuery and specialized models.
Extensions by Google
Google provides the following prebuilt extensions:
What's next
- Create, register, and run extensions.
- Register and use Google-provided extensions
- Use Reasoning Engine.