Unbody’s Approach to Expanding Weaviate’s Generative Capabilities

Unbody, an AI-native development stack, initially adopted Weaviate, an AI-native vector database, to unify AI and product development workflows, but faced limitations with its generative capabilities as demands evolved. While Weaviate's generative module, including Retrieval Augmented Generation (RAG), initially served user needs, issues arose with static configurations, limited syntax flexibility, and text-only input constraints. In response, Unbody developed a custom Generative API, enhancing flexibility by decoupling the generative module from the database, allowing dynamic model selection, multi-modal input, and advanced data transformation capabilities. This solution introduced a sophisticated templating engine, enabling richer interactions and custom workflows, and set the stage for future enhancements such as structured output, streaming support, and broader model and provider integration, aimed at improving performance and functionality.

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