0xPlaygrounds/rig

⚙️🦀 Build modular and scalable LLM Applications in Rust

What it solves

Rig provides a unified, ergonomic way to build LLM-powered applications in Rust, reducing the boilerplate required to integrate multiple model providers and vector stores. It allows developers to create scalable and modular AI agents without being locked into a specific provider's API.

How it works

Rig separates its architecture into two main components: rig-core, which handles provider-neutral contracts for messages, completion models, and vector stores, and rig-agent, which provides the orchestration layer for building agents with prompt streaming, typed hooks, and state management. This structure allows developers to use a portable core for basic needs or the full agent runtime for complex workflows.

Who it’s for

Rust developers who want to build production-ready AI agents, chatbots, and RAG applications with a modular architecture that supports a wide variety of LLM providers and vector databases.

Highlights

  • Unified Interface: Access to 20+ model providers and 10+ vector stores through a single API.
  • Agentic Workflows: Support for multi-turn streaming, prompting, and a serializable state machine for agent runs.
  • Browser Support: Compatible with Browser-WASM (wasm32-unknown-unknown) for the portable core and classic runtime.
  • Broad Capability Support: Handles LLM completion, embeddings, transcription, audio generation, and image generation.
  • Standardized: Full compatibility with the GenAI Semantic Convention.

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