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Google AI + Weaviate

New Documentation

The model provider integration pages are new and still undergoing improvements. We appreciate any feedback on this forum thread.

Google AI offers a wide range of models for natural language processing and generation. Weaviate seamlessly integrates with Google AI Studio and Google Vertex AI APIs, allowing users to leverage Google AI's models directly within the Weaviate database.

These integrations empower developers to build sophisticated AI-driven applications with ease.

Integrations with Google AI

Embedding integration illustration

Google AI's embedding models transform text data into high-dimensional vector representations, capturing semantic meaning and context.

Weaviate integrates with Google AI's embedding models to enable seamless vectorization of data. This integration allows users to perform semantic and hybrid search operations without the need for additional preprocessing or data transformation steps.

Google AI embedding integration page

Generative AI models for RAG

Single prompt RAG integration generates individual outputs per search result

Google AI's generative AI models can generate human-like text based on given prompts and contexts.

Weaviate's generative AI integration enables users to perform retrieval augmented generation (RAG) directly within the Weaviate database. This combines Weaviate's efficient storage and fast retrieval capabilities with Google AI's generative AI models to generate personalized and context-aware responses.

Google AI generative AI integration page


These integrations enable developers to leverage Google AI's powerful models directly within Weaviate.

In turn, they simplify the process of building AI-driven applications to speed up your development process, so that you can focus on creating innovative solutions.

Get started

You must provide a valid Google AI API credentials to Weaviate for these integrations. Weaviate integrates with both Google AI Studio or Google Vertex AI.

Go to the relevant integration page to learn how to configure Weaviate with the Google models and start using them in your applications.

If you have any questions or feedback, let us know in the user forum.