OpenAI + Weaviate
For Azure OpenAI integration docs, see this page instead.
OpenAI offers a wide range of models for natural language processing and generation. Weaviate seamlessly integrates with OpenAI's APIs, allowing users to leverage OpenAI's models directly from the Weaviate database.
These integrations empower developers to build sophisticated AI-driven applications with ease.
Integrations with OpenAI
Embedding models for semantic search
OpenAI's embedding models transform text data into high-dimensional vector representations, capturing semantic meaning and context.
Weaviate integrates with OpenAI'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.
OpenAI embedding integration page
Generative AI models for RAG
OpenAI'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 from the Weaviate database. This combines Weaviate's efficient storage and fast retrieval capabilities with OpenAI's generative AI models to generate personalized and context-aware responses.
OpenAI generative AI integration page
Summary
These integrations enable developers to leverage OpenAI'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 OpenAI API key to Weaviate for these integrations. Go to OpenAI to sign up and obtain an API key.
Then, go to the relevant integration page to learn how to configure Weaviate with the OpenAI models and start using them in your applications.
Questions and feedback
If you have any questions or feedback, let us know in the user forum.