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✨ If you would like to help spread the word about Rig, please consider starring the repo!

[!WARNING] Here be dragons! As we plan to ship a torrent of features in the following months, future updates will contain breaking changes. With Rig evolving, we'll annotate changes and highlight migration paths as we encounter them.

Table of contents
What is Rig?
High-level features
Who's using Rig?
Get Started
- Simple example
Integrations

What is Rig?

Rig is a Rust library for building scalable, modular, and ergonomic LLM-powered applications.

More information about this crate can be found in the official & crate (API Reference) documentations.

Features

Agentic workflows that can handle multi-turn streaming and prompting
Full GenAI Semantic Convention compatibility
20+ model providers, all under one singular unified interface
10+ vector store integrations, all under one singular unified interface
Full support for LLM completion and embedding workflows
Support for transcription, audio generation and image generation model capabilities
Integrate LLMs in your app with minimal boilerplate
Full WASM compatibility (core library only)

Who is using Rig?

Below is a non-exhaustive list of companies and people who are using Rig:

St Jude - Using Rig for a chatbot utility as part of proteinpaint, a genomics visualisation tool.
Coral Protocol - Using Rig extensively, both internally as well as part of the Coral Rust SDK.
VT Code - VT Code is a Rust-based terminal coding agent with semantic code intelligence via Tree-sitter and ast-grep. VT Code uses rig for simplifying LLM calls and implement model picker.
Dria - a decentralised AI network. Currently using Rig as part of their compute node.
Nethermind - Using Rig as part of their Neural Interconnected Nodes Engine framework.
Neon - Using Rig for their app.build V2 reboot in Rust.
Listen - A framework aiming to become the go-to framework for AI portfolio management agents. Powers the Listen app.
Cairnify - helps users find documents, links, and information instantly through an intelligent search bar. Rig provides the agentic foundation behind Cairnify’s AI search experience, enabling tool-calling, reasoning, and retrieval workflows.
Ryzome - Ryzome is a visual AI workspace that lets you build interconnected canvases of thoughts, research, and AI agents to orchestrate complex knowledge work.
deepwiki-rs - Turn code into clarity. Generate accurate technical docs and AI-ready context in minutes—perfectly structured for human teams and intelligent agents.
Cortex Memory - The production-ready memory system for intelligent agents. A complete solution for memory management, from extraction and vector search to automated optimization, with a REST API, MCP, CLI, and insights dashboard out-of-the-box.
Ironclaw - A secure personal AI assistant

For a full list, check out our ECOSYSTEM.md file.

Are you also using Rig? Open an issue to have your name added!

Get Started

bash

cargo add rig-core

Simple example

rust

use rig::client::{CompletionClient, ProviderClient};
use rig::completion::Prompt;
use rig::providers::openai;

#[tokio::main]
async fn main() -> Result<(), anyhow::Error> {
    // Create OpenAI client
    let client = openai::Client::from_env();

    // Create agent with a single context prompt
    let comedian_agent = client
        .agent("gpt-5.2")
        .preamble("You are a comedian here to entertain the user using humour and jokes.")
        .build();

    // Prompt the agent and print the response
    let response = comedian_agent.prompt("Entertain me!").await?;

    println!("{response}");

    Ok(())
}

Note using #[tokio::main] requires you enable tokio's macros and rt-multi-thread features or just full to enable all features (cargo add tokio --features macros,rt-multi-thread).

You can find more examples each crate's examples (ie. rig/rig-core/examples) directory. More detailed use cases walkthroughs are regularly published on our Dev.to Blog and added to Rig's official documentation (docs.rig.rs).

Supported Integrations

Vector stores are available as separate companion-crates:

MongoDB: rig-mongodb
LanceDB: rig-lancedb
Neo4j: rig-neo4j
Qdrant: rig-qdrant
SQLite: rig-sqlite
SurrealDB: rig-surrealdb
Milvus: rig-milvus
ScyllaDB: rig-scylladb
AWS S3Vectors: rig-s3vectors
HelixDB: rig-helixdb

The following providers are available as separate companion-crates:

AWS Bedrock: rig-bedrock
Fastembed: rig-fastembed
Google Vertex: rig-vertexai

We also have some other associated crates that have additional functionality you may find helpful when using Rig:

rig-onchain-kit - the Rig Onchain Kit. Intended to make interactions between Solana/EVM and Rig much easier to implement.