A Board Game agent built using Sanity Context and Vercel's AI SDK
Blog post from Sanity
The tutorial explores the creation of a board game recommendation agent using Sanity's Context feature and GPT-4o, providing a step-by-step guide to building an AI-driven system that queries board game data from the BoardGameGeek API and returns recommendations based on specified criteria. It details the setup of a Sanity project, the creation of a board game schema, and the configuration of the system to parse and ingest data using GROQ queries. The tutorial emphasizes the importance of a structured approach to building the agent, which operates without a frontend interface and can be adapted for various datasets. It also highlights the significance of precise data structuring to enhance the agent's functionality, demonstrating how the agent processes and responds to queries with real-time data from the Content Lake.
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