Rust AI: Building LLM Applications With Rig

A Rust Foundation livestream introduced Rig, an open-source Rust library that provides a unified interface for large language model providers such as OpenAI, Anthropic, and Gemini, helping developers build applications without depending on provider-specific APIs. Rig structures applications around provider clients, models, agents, preambles, and Rust-based tools that can perform tasks such as file operations, database queries, calculations, or shell commands, with support for asynchronous requests, streaming, agent delegation, and stateful tool context. The session demonstrated these capabilities through Rat Code, a terminal coding agent built with Rig and Ratatui that registers file and shell tools and streams model responses in its interface. Rig also supports retrieval-augmented generation through vector-store integrations and local inference through Ollama, llama.cpp, and Candle, including options to embed model weights or run supported models in WebAssembly. To test changing provider integrations despite nondeterministic model outputs, Rig records live HTTP interactions as cassettes that can be replayed in CI, while production users may separately schedule live-model tests to assess output quality.

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