Rig
ActiveDescription
Build modular and scalable LLM Applications in Rust. Provides agent orchestration, tool-use, RAG pipelines, and other core capabilities for high-performance AI agent systems.
Key Features
- 20+ LLM provider integrations under a unified interface
- 10+ vector store integrations for RAG workflows
- Agentic workflows with multi-turn streaming and tool-use
- Full OpenAI Semantic Convention compatibility for observability
- Support for completions, embeddings, transcription, audio, and image generation
- WASM compatibility for the core library
Use Cases
💡 Building high-performance Rust-based AI agents and chatbots
💡 Creating RAG pipelines with pluggable vector stores
💡 Developing multi-provider LLM applications with minimal boilerplate
💡 Building production AI services that need WASM deployment
Categories
Quick Start
Add Rig to your project: `cargo add rig`. Create an OpenAI client with `openai::Client::from_env()`, build an agent with `client.agent(openai::GPT_5_2).preamble("...").build()`, then prompt it with `.prompt("...").await`. See docs.rig.rs for full API reference.