RAG can be Rigged

Cyril Scetbon explores the integration of SurrealDB and Rig.rs to create a knowledge agent capable of embedding and querying word definitions efficiently. SurrealDB, a Rust-based database combining document, graph, relational, and vector models, complements Rig.rs, a toolkit for building language model-native agents. The process involves setting up a project, ingesting and embedding documents in SurrealDB, and using Rig to create an agent that applies OpenAI's models for natural language processing. This setup allows the agent to respond to queries based on stored embeddings while avoiding fabricating answers. The article emphasizes the advantages of using Rust-native tools like SurrealDB for flexible and efficient data handling in language model applications, encouraging developers to streamline their workflows by leveraging the comprehensive capabilities of Rig and SurrealDB.